1The Impact of Farmer-Field-Schools on Knowledge and Productivity:A Study of Potato Farmers in the Peruvian Andes1byErin Godtland†, Elisabeth Sadoulet*, Alain de Janvry*,Rinku Murgai**, and Oscar Ortiz‡November 2003Using survey-data from Peru, this paper evaluates the impact of a pilot farmerfield-school (FFS) program on farmers’ knowledge of integrated pestmanagement (IPM) practices related to potato cultivation. We use bothregression analysis controlling for participation and a propensity score matchingapproach to create a comparison group similar to the FFS participants inobservable characteristics. Results are robust across the two approaches as wellas with different matching methods. We find that farmers who participate in theprogram have significantly more knowledge about IPM practices than those inthe non-participant comparison group. We also find that improved knowledgeabout IPM practices has a significant impact on productivity in potatoproduction.† U.S. General Accounting Office, godtlande@gao.gov.* University of California at Berkeley, sadoulet@are.berkeley.edu, alain@are.berkeley.edu.** Development Economics Research Group, The World Bank, rmurgai@worldbank.org‡ International Potato Center, Consultative Group on Agricultural Research, o.ortiz@cgiar.org.1 We are especially indebted to the farmers of San Miguel and the extension and research staff at CIP and CARE-Peru, who

generously offered their time and expertise on behalf of this project. This research was made possible by financial support fromthe World Bank Research Committee RPO No. 683-56 and the Development Research Group. The views expressed in thisarticle are those of the authors and should not be attributed to the World Bank or any affiliated organization. The authors takefull responsibility for any errors.2I. IntroductionThe design of agricultural extension programs in developing countries has been the subject of heateddebate. Guided by these debates, extension services have undergone several transformations in the past few decades(Byerlee, 1994). The main transformation, until recently, was a shift from the transfer-of-technology approach to theTraining-and-Visit, or T&V, system. Under T&V, the extension system was reoriented from a desk-boundbureaucracy with multiple economic and social objectives to a field-based cadre of agents who focused mainly ontechnology diffusion (Picciotto and Anderson, 1997). T&V extension agents would meet with a small group of“contact” farmers who were expected to disseminate information to the members of their respective communitiesand convey farmer’s opinions back to the agents, thus creating a feedback mechanism absent in the prior system(Birkhaeuser, et al, 1991). For nearly three decades, international aid donors, such as the World Bank, promotedT&V as the most cost-efficient extension system.T&V did, however, have its critics. With continued budgetary crises of less developed countries, someargued that it was too expensive and impossible to implement over extensive regions. Highly dispersed farmerscould never establish frequent contact with extension agents. And their needs varied widely and could not be

addressed with a single, inflexible technology package (Picciotto and Anderson, 1997; Feder, Willett, and Zijp,2001).2In recent years, a number of development agencies have promoted farmer field schools (FFS) as apotentially more effective approach to extend knowledge to farmers. FFS programs were first introduced in EastAsia, in the late eighties, as a way of diffusing knowledge-intensive integrated pest management (IPM) practices forrice.3 FFS have since been adapted to work with other crops and diseases, and have spread rapidly across Asia,Africa, and Latin America (Nelson et al., 2001). The FFS approach represents a paradigm shift in agriculturalextension: the training program utilizes participatory methods “to help farmers develop their analytical skills, criticalthinking, and creativity, and help them learn to make better decisions” (Kenmore, 2002). Extension agents, who areviewed as facilitators rather than instructors, conduct learning activities in the field on relevant agricultural practices.Through interactive learning and field-experimentation, FFS programs teach farmers how to experiment andproblem-solve independently, with the expectation that they will thus require fewer extension services and will beable to adapt the technologies to their own specific environmental and cultural needs (Vasquez-Caicedo et al., 2000).Participants are encouraged to share their knowledge with other farmers, and are sometimes trained to teach thecourses themselves, thus reducing the need for external support.FFS are costly undertakings, making a careful measurement of their impact important. However, empiricalevidence on their effectiveness has been mixed. Results of previous impact evaluations have varied greatlyaccording to the setting, the evaluation methods, and the yardstick used to assess impact. The few studies that

2 An abundance of empirical research exists on the effectiveness of T&V. See Birkhaeuser et al. (1991) for a review of studies onthe economic impact of these and other agricultural extension programs.3 IPM is knowledge-intensive because in order to effectively implement IPM – which employs natural predators to combat pests– farmers must be able to understand the origins, cycles, and natural enemies of pests.3examine the impact of FFS on farmers’ knowledge generally find that FFS participants tend to have higherknowledge test scores after program participation or relative to a group of non-participants.4 Some studies show thatFFS participants use less pesticide and have higher yields compared to non-participants, while others find littleevidence of impact on these outcomes. At the same time, there appears to be little evidence of diffusion ofknowledge from FFS graduates to other farmers.5A major drawback of most previous studies is that they do not properly control for potential differencesbetween FFS participants and farmers in the comparison group, making it difficult to draw definitive conclusions.These differences could arise from the non-random placement of the program or from the voluntary nature ofparticipation in FFS. For example, FFS villages might be chosen for their relative advantages in land fertility orclimate. Or farmers who voluntarily participate in FFS might be more productive, on average, than those who donot participate. Selective placement (through individual choice or purposive targeting) means that data on nonparticipantsdoes not reveal well the likely achievements of participants in the absence of the program. Unlessproper account of non-random farmer and village selection is taken, comparison of outcomes between FFSparticipants and non-participants is likely to yield biased estimates of program impact.6

This paper uses data from a survey of potato farmers in Cajamarca, Peru, to examine the impact of a pilotFFS program on farmers’ knowledge (as measured by a knowledge test score) and the impact of knowledge onproductivity. To deal with selection bias, we use propensity score matching (PSM) methods to build a statisticalcomparison group of farmers comparable to FFS graduates. This allows us to ensure that bias in the impact estimatedue to selection on observables is minimized. Any remaining bias in the matching estimator can thus be attributed tounobserved characteristics. That said, our application is well suited to PSM since the design of the program in Peruentailed considerable rationing of participation. The sample of non-participants is very likely to include people whowanted to participate but were unable to do so due to the non-availability of the program. Matching methods havebeen quite widely used in evaluations but there have as yet been no applications of matching to the assessment ofagricultural extension programs.Our empirical results indicate that farmers who participate in the program have significantly moreknowledge about IPM practices than those in the non-participant comparison group. We also find that improvedknowledge about IPM practices has a significant impact on productivity in potato production. Combining theseresults, we estimate that FFS participation can raise the average potato seed output/input ratio by a large amount,approximately 52% of the average value in a normal year. We should note that since the survey was conducted inthe first year of program implementation, we do not attempt to assess the extent of knowledge diffusion to nonparticipants.The paper proceeds as follows. Section II describes the FFS program in Peru and the data set. Section IIIexamines how farmers obtain information on potato cultivation, and their knowledge levels. In Section IV, we

4 See for example, Rola et al. (2002) in the Philippines, Van de Fliert et al. (1999) in Indonesia, and Preneetvatakul and Waibel(2002) in Thailand.5 For a summary of these studies, see Feder et al., (2003).4present the research strategy used to test the impact of FFS on knowledge. Sections V and VI apply thismethodology to measure impact on knowledge. Finally, Section VII estimates how knowledge affects productivitylevels in potato cultivation and Section VIII concludes.II. The Program and DataAs the home country for the headquarters of the International Potato Center (CIP), one of the CGIARcenters, Peru has long been a focal point for the development and deployment of improved potato varieties andcultivation practices. In 1998, CIP scientists, in collaboration with CARE-Peru, launched a pilot farmer field schoolprogram for potato farmers in the department of Cajamarca. This department lies in the northern part of the PeruvianAndes, which is known as the Green Andes. Unlike the dry flatlands of the Altiplano, the Green Andes arecharacterized by steeply sloped, hilly terrain with relatively higher precipitation levels. The elevation of the surveyregion ranges from 9,000 to 12,000 feet above sea level. The economy in the survey region is dominated by smallfarms with potato farming as the main activity. Potatoes constitute the bulk of households’ food consumption andare also their most lucrative market crop.The main aim of the FFS program was to introduce IPM techniques to Andean potato farmers. FFSparticipants were expected to attend 12 training sessions (typically once a week, with each session lasting for 3hours). As the training strategy was based on the principle of learning by discovery, during these sessions the

facilitator would organize various activities and experiments that the farmers could implement themselves. Thecurriculum was focused on the biology of late blight, the fungus that caused the Irish Potato Famine and continues totake huge tolls on potato production in Peru. Farmers were taught its symptoms, its reproductive cycle, itscontamination source, and the conditions that foster its growth. On the experimental plot (one per FFS community),they identified potato varieties that are resistant to late blight infection. They learned how to prevent and controllate blight with the use of improved varieties and fungicides. The program also introduced IPM for the Andeanpotato weevil and the potato tuber moth in less detail.There was a two-stage selection process that determined which farmers could participate in the program.First, CARE selected the villages in which to introduce the FFS program. These villages were chosen from a set ofvillages where CARE had already been implementing another rural development project named “Andino”. Thisproject worked with farmers groups to improve farm production by providing technical advice and access to credit,and by facilitating links to markets. Technical advice in Andino was imparted through conventional transfer-oftechnologyapproaches. The Andino villages (and consequently, the FFS villages) were not a random sample ofvillages in the region. Rather, CARE had conducted a diagnostic survey of all communities within the watershed,and based on this survey, classified communities into three types: subsistence, middle income, and high income.The target population for the Andino program was the set of middle-income communities and, from this targetgroup, 20 villages that were close to their respective district capitals were selected for participation. CARE planned6 The only study that properly controls for selection biases finds no evidence of FFS impact (Feder et al., 2003).

5to introduce FFS in all the Andino villages. However, at the time of the survey, field schools were operating only infour. These four villages constitute our ‘treatment villages’.Within the FFS villages, all farmers were invited to participate in the program. The only requirementimposed on participants was that they had to attend all the training sessions. In reality, although the call forparticipation was open to all community members, pre-existing groups took advantage of their already-existingorganization and formed an FFS group. As a result, a number of FFS participants were also participants in otherfarmer groups such as Andino. However, because of limits on the number of participants permitted in each school,the participation rate in FFS remained very low during the first year of implementation, with only 45 farmers out ofa population of 900 (or 5% of the farmers) participating in the program. Similar low participation rates of 2.5% areobserved for the Andino program in villages where it is offered.The main objective of this paper is to analyze the impact of FFS on knowledge by contrasting FFSparticipants to a matched control group of non-participants in either the FFS or the Andino program. A secondaryobjective is to analyze the impact of Andino on knowledge by contrasting Andino participants to the same group ofnon-participants. Because we have a large group of non-participants, these two tests of impact can be performed.We are, however, limited by the small number of observations in testing the difference in impact on knowledgebetween FFS and Andino. We report information on descriptive statistics comparing the gains in knowledgeachieved under the two programs, conduct statistical analysis of the impact of each program, and describe thedifferences in impact on knowledge, but do not have enough degrees of freedom to expect to achieve significance in

comparing these two levels of impact. For this reason, we report in detail results on the impact of FFS but onlysecondarily on the impact of Andino.The data for our analysis come from a 1999 survey of potato farmers in thirteen communities within theprovince of San Miguel located in the Department of Cajamarca. Ten of the thirteen villages included in the sampleare among the CARE Andino villages, including the four villages that were selected as FFS villages at the time ofthe survey. The sample includes all of the FFS and Andino participants and a random sample of non-participantfarmers from (a) the four villages that have FFS programs, (b) six villages which have experience with CAREthrough Andino but do not have farmer field schools, and (c) three control villages. The control villages werechosen to be similar to the FFS villages in observable characteristics such as agro-climatic conditions, distance todistrict capitals, and infrastructure. The distribution of households in the three types of villages is reported in Table1.6CARE villages CARE villages Non-CAREwith FFS program with Andino program villages TotalFFS participants 45 0 0 45Work with CARE, non-participants in FFS 9 62 2 73Do not work with CARE 39 181 148 368Total number of households in sample 93 243 150 486Total number of households in villages 900 2337 1278 4515Villages 4 6 3 13Table 1. Sample of HouseholdsThe survey was carried out over two household visits. The first visit gathered detailed plot-level data,including the costs and quantities of seed, chemical, and labor inputs for each agricultural activity (from land

preparation through harvest) during the year preceding the survey. It also included a knowledge test, which wasbased on the curriculum of the FFS. The second visit collected information on each household member’s educationlevel and marital status, off-farm activities and credit sources, and the household’s experience with agricultural andother extension services. The second visit also included a full household consumption recall for the last year and anitemized account of all household and farm assets.Examination of the potato output-seed ratio (the quantity of seed harvested divided by the quantity of seedplanted per hectare) in the sample suggests that the survey was conducted in a ‘normal’ year (see Figure 1).7According to potato experts, in Cajamarca, the distribution of output-seed ratios in Figure 1 is typical for the region.A ratio of 1-3 is very bad, 4-6 is bad, 7-9 is regular, 10-15 is good, and greater than 15 is excellent. The averageoutput ratio for the sample was 7.6 with a standard deviation of 4.2. Thirty-eight percent of the plots hadproductivity levels rated as bad or very bad. While ‘normal’, the wide dispersion in the output-seed ratios alsoillustrates the tremendous variation in productivity levels in the sample villages. This is the variable that we will useto measure the impact of knowledge on productivity.7 Tuber scientists call this measurement the multiplication ratio. It is one of the two most commonly used productivity measures,the other measure being yield estimates based on harvest sampling (Terrazas, et. al, 1998).7Figure 1. Histogram for Potato Output/Input RatiosPercentage of farmers0 5 10 15 200510

Potato output/input ratioPart of the variation in productivity arises from production losses due to late blight, as is evident in Table 2which shows the primary causes of production losses by plot during 1998, as reported by farmers in the sample. Itillustrates the need for a curriculum with a heavy emphasis on late blight. Although this was not a wet year, 47% ofthe potato plots in the sample experienced losses due to late blight. 19% experienced losses from frost. The Andeanpotato weevil, the potato tuber moth, and hail were not critical problems in the year the survey was conducted.Source of stress Late blightAndeanpotatoweevilPotatotuber moth Frost Hail% of plots affected 47.1 5.4 1.0 19.3 1.4% of plots with 0-25% loss 31.9 3.8 1.0 7.0 1.4% of plots with 26-50% loss 10.8 1.6 0 6.9 0% of plots with 51-75% loss 3.0 0 0 2.8 0% of plots with 76-100% loss 1.4 0 0 2.6 0Table 2. Agricultural Losses Caused by Common Pests and Weather ConditionsIII. Information Channels and Knowledge LevelsBefore evaluating the impact of FFS on farmers’ knowledge of IPM practices, it is useful to examine howfarmers in San Miguel typically obtain information on potato cultivation. The questionnaire requested farmers toname their primary sources of information on a number of tasks related to potato cultivation. Table 3 summarizesthese results. The majority of farmers get information on potato farming from family members. Farmers seekinformation on new technologies, such as new varieties and pesticides and fungicides from other neighbors in the

community. Given the traditional, rural environment, this makes sense. Using data from several surveys in India,8Foster and Rosenzweig (1995) note that information from neighbors on new technologies was as important asinformation from government extension services. In their study in Northern India, Feder and Slade (1986) also notethe extensive role of discussions among farmers as a main source of agricultural advice. Ortiz and Valdez (1993)found a similar role for neighbors for information in other Cajamarca communities. Agricultural economistsworking in developed countries have also noted this phenomenon (Birkhaeuser et al., 1991). For the selection ofimproved varieties and the control of pests and diseases, which are more technical issues, farmers not only citefamily members and neighbors as their primary sources of information, but also CARE (either FFS or conventionaltraining) as an important source. Feder and Slade (1986) similarly found that farmers in their sample are more likelyto seek information on complex agricultural practices from agricultural extension agents.Source of informationFamilymemberNeighbor in thecommunity or anearbycommunitySharecroppingpartnerMerchant /At themarket CAREOtherNGO Radio

OwnExperienceAgronomic practicesSoil preparation 96 3 0.0 0 0 0 0 2Planting 96 4 0.7 0 0 1 0 1Fertilizing 92 8 1 0 1 1 0 3Weeding and uphilling 94 4 5 0 0 0 0 3Seed selection 88 8 1 0.5 1 1 0 0Technical issuesImproved varieties 52 34 1 6 6 1 2 2Pesticide/fungicide use 73 24 2 3 1 2 1 5Late blight control 71 23 2 2 2 3 0 7Andean potato weevil control 28 9 0.7 1 1 2 0 5Potato tuber moth control 15 3 0 2 0 1 0 2Sources do not sum to 100% since respondents were permitted to list multiple sourcesTable 3. Sources of Information on Potato Cultivation (% of farmers who use the source)How accurate is the knowledge that farmers share with one another? The questionnaire included a test,designed by CIP extension experts, of farmers' knowledge about the control of the three major pests – late blight, theAndean potato weevil, and the potato tuber moth. Farmers were asked how to identify the pest and its cause, how itreproduces, and how to control it. For late blight, farmers were also asked what fungicides are used to control it,how to differentiate categories of pesticides in general and of fungicides in particular, and to name resistantvarieties. Finally, farmers were asked how they select pesticides/fungicides, whether they could identify themeaning of different warning labels on the pesticides, and what precautions they take in applying and storing theagro-chemicals. The scores for each topic category are presented in Table 4. In general, they are very low, withaverage scores that do not exceed twenty-five percent of the total score.

This low level of knowledge about important agricultural problems and solutions is what motivates severalNGOs to provide agricultural extension services to farmers in Cajamarca and throughout Peru. CARE-Peru worksextensively in the Cajamarca region to disseminate information on new technologies through conventional transfer9of-technology agricultural extension programs (Andino) and through experimental extension programs, such as FFS.Table 4 compares test scores of the farmers who participate in the FFS and Andino programs with farmers who donot participate in any program. Farmers who participate in the FFS have significantly higher scores on tests in everyarea. Farmers who worked with the Andino program also score significantly higher on the tests. Finally, FFSparticipants have higher scores than Andino program participants overall and in all test scores but one.Table 4. Agricultural Knowledge Test Score Comparisons Across Groups of FarmersP-valueAll FFS Andino Non- differencehouseholds participants participants participants1 FFS vs. AndinoNumber of observations 486 45 64 329Test scores: % of maximum scoreKnowledge on late blight 24 35 29 24 0.06Knowledge on Andean weevil 10 25 14 9 0.02Knowledge on potato tuber moth 6 15 17 6 0.60Pesticide knowledge 21 29 25 21 0.04Knowledge on resistant varieties 17 49 33 16 0.00Total test score 19 34 26 19 0.001 All differences between FFS and non-participants and between CARE and non-participants are significantly positive at 1%.IV. Empirical ApproachThe purpose of the estimation that follows is to measure the impact of FFS on knowledge levels of those

who participated in the program. This is the Average Treatment Effect on the Treated (ATE1), where the treatmentis participation in the program. The empirical problem we face is the typical one of filling in missing data on thecounter-factual: what would knowledge levels of FFS participants have been if they had not participated in theprogram? Our challenge is to identify a suitable comparison group of non-participants whose outcomes, on average,provide an unbiased estimate of the outcomes that program participants would have had in the absence of theprogram. Given the non-random selection of program villages and farmer self-selection, simple comparisons ofknowledge levels between participants and non-participants would yield biased estimates of program impact.Based on program design, there are three potential sources of bias in measuring program impact. First, FFSparticipants are likely to differ from non-participants in the distribution of their observed characteristics, leading to abias from “selection on observables”. Such a bias is likely to arise because the criteria used for FFS village selection(e.g., distance to the district capital) and participant selection can also be expected to have a direct effect onknowledge levels even in the absence of the program. We control for selection on observables in two ways. First,in the sample design, non-FFS villages were purposively selected to be similar to the FFS villages in terms ofobserved characteristics such as agro-climatic conditions, prevalence of potato farming, distance to the provincialcapital, etc. Table 5 reports average characteristics of households from FFS and non-FFS villages, including10demographic characteristics, assets, whether farmers are credit constrained8, and a measure of the severity of the ElNino shock endured the year before the survey (fraction of the plots that were not harvested because of El Nino

damage). It shows that the equality in means cannot be rejected for all but one characteristic. Second, as describedbelow, we use both regression and propensity score matching (PSM) methods to control for differences in observedcharacteristics between FFS participants and non-participants. These approaches provide an unbiased measure ofprogram impact under the assumption of conditional mean independence, whereby pre-program outcomes areindependent of participation given the variables used as controls in the regression or for matching. The fact that theFFS were part of a small pilot program makes it more likely that this assumption would be true: the sample of nonparticipantsvery likely includes farmers who wanted to participate but were unable to do so due to the nonavailabilityto them of the program. 9Farmers in FFS Villages Farmers in Non-FFS Villages P-values for equalityMean value Mean value of means between villagesNumber of Observations 93 393Education of household head (years) 2.4 2.4 0.78Age of household head 46.0 44.8 0.62Number of family members 4.8 5.3 0.13Dependency rate 1.1 1.1 0.99Total land ownership (10 hect.) 0.12 0.11 0.66Value of cattle assets (100 soles) 6.1 5.0 0.46Number of inherited livestock 0.11 0.44 0.02Value of household assets (100 soles) 1.3 0.6 0.47Value of farm assets (100 soles) 0.43 0.47 0.45Plots lost from El Nino the previous year 0.32 0.25 0.31Credit Constrained 0.31 0.25 0.42Exchange rate in 1999: 100 soles ≈ US$ 30.Table 5. Comparison of Household Characteristics in Villages With and Without FFSA second source of bias in program impact can arise if there is diffusion of knowledge in FFS communities.

In the presence of diffusion, comparing FFS participants with non-participants in the same village is likely tounderestimate program impact. Because the program had been in operation for only one year at the time of thesurvey, the extent of diffusion is likely to have been low. In any event, to avoid all bias from potential diffusionwithin FFS communities, we exclude non-participants in FFS communities from the comparison group. Hence, the8 Farmers were categorized as credit constrained if they answered that they did not currently have a loan because they did nothave access to, or did not have a guarantee for, loans from both formal banks and NGOs. There were no farmers who arecurrently receiving loans who responded that they could not obtain more and hence should be categorized as credit constrained.9 In the area that we observed, FFS was a small-scale program, with a very low participation rate (5% of the farmers in FFSvillages). If it were the case that all farmers that did not participate in the program were genuine non-participants in the sensethat they would not participate even in a fully developed program, then the average treatment effect of the presence of a FarmerField School in a village could be obtained by dividing the average treatment effect on participants by the rate of participation.On the other hand, if the very low participation rate in the program was largely due to the fact that the program itself could notexpand and hence was not introduced with the same level of information as a full fledged program, this calculation would lead toa large downward bias of the impact of a fully developed program.11sample that we retain P(FFS) nonFFSincludes FFS participants (P) from the FFS villages and non-FFSvillages farmers (excluding the participants to the Andino program).10A final source of bias is that FFS participants may differ from non-participants in the distribution ofunobserved characteristics (e.g., in farming ability that affects both the decision to participate in FFS and the desire

to seek out new knowledge), resulting in “selection on unobservables”. In the absence of a suitable instrument forprogram participation, we are unable to explicitly control for selection on unobservables. However, followingAltonji, Elder, and Taber (2002), we use an informal way of assessing the potential bias that could result fromunobservables and find that this bias is likely small compared to the estimated impact.The assumptions underlying the above discussion can be formally expressed as follows:Assumption 1. Stable Unit Treatment Value (SUTV) in the retained sample (excluding non-participants from theFFS villages)This assumes that the treatment only affects the outcomes of those who participate, i.e., there is nodiffusion of knowledge from FFS participants to control farmers in non-FFS villages.Assumption 2. Ignorability of treatment (participation in FFS): Conditional on observed village and individualcharacteristics xv , xi , outcomes y0, y1and participation w are independent.This assumption implies the weaker conditional mean independence:E y0 xv , xi ,w E y0 xv , xi and E y1 xv , xi ,w E y1 xv , xi , (1)where y0 and y1 are the outcomes of interest (farmers’ knowledge) without and with participation in the FFSprogram, w is a binary indicator of participation, and xv ,uv , xi , and ui denote observed and unobserved village andindividual characteristics, respectively.These two conditions allow us to build a statistical comparison group for FFS participants with similarfarmers from the non-FFS villages, and to estimate the impact of the FFS program by comparing the observedoutcome y1 of FFS participants with the outcome y0 of farmers in the comparison group. We use two different

estimators.4.1. Estimation by regressionThe first method is based on assuming a parametric expression for the conditional mean independence (1):E y0 x 0 x x 0 and E y1 x 1 x x 1 where x is the vector of covariates xv , xi with average value x .10 Note that this assumes that there is no diffusion from FFS farmers to farmers in non-FFS villages, which seems reasonable12This gives the expected knowledge outcome y conditional on a given set of covariates as:Ey x,w0 w xwx x. (2)where y 1 wy0 +wy1 is the observed outcome (equal to y1 for participants and y0 for non-participants).Subtracting the average values x from the covariates x ensures that the coefficient is the average treatment effect.Since the regression of y on x,w,wx xconsistently estimates the parameters, we can derive an estimate of theconditional average treatment effect:AT√EReg x√x x√,which can be averaged over the sample of participants, or any other group of farmers. In particular, √ is anestimation of the average treatment effect over the sample population, and the average treatment effect on the treatedis estimated by:ATE x x w √ Reg E √ √ 1 1.4.2. Estimation by matching on probability propensity scoresThis method, developed by Rosenbaum and Rubin (1983), is based on modeling the probability oftreatment given covariates, called the probability propensity score (PPS):px∫Pw 1 x.Suppose that two agents from the population have identical PPS. Then under the ignorability condition, the

average treatment effect, conditional on the PPS, is equal to the expected difference in the observed outcomesbetween participants and matched non-participants:Ey1 y0 pxEy w 1, pxEy w 0, px.Averaging over the distribution of propensity scores in the treated population gives the average treatmenteffect on the treated:ATEPSM y w p x y w p x w1 EE1, E0, 1.Implementation of this method relies on having an estimator for the PPS, which we discuss in the nextsection.V. Estimation of the probability propensity scoreWhile estimation of the average impact effect is done in the population that excludes the non-participantsfrom the FFS villages because of the required SUTV assumption, this need not be the case for the independentestimation of the PPS. In fact, it is within the FFS villages that we have a better identification of the covariates thatgiven the limited time that had elapsed between training and the date of the survey.13determine FFS participation, since farmers in these villages were all, to a certain extent, given the opportunity toparticipate.Using the sub-sample FFSof farmers living in the FFS villages, we estimate a flexible probit model ofparticipation, where covariates and various functions of these covariates are introduced. The estimated model canbe used to predict p√xfor the population P(FFS) nonFFSused for the estimation of the average treatmenteffect. As farmers from the non-FFS villages are not included in the estimation of the propensity score, this

constitutes an out-of-sample prediction. Its validity relies on the existence of sufficient overlap of the covariates,and on the assumption that the same participation model would apply in both samples were all villages offered theFFS program. The latter is an assumption of ignorability of the choice of village for participation.Assumption 3. Ignorability of the selection of FFS villages for participation choice: Conditional on observed villageand individual characteristics xv , xi , the choice of villages for the placement of an FFS and participation w areindependent.This assumption implies conditional mean independence:Pw 1 xv , xi ,presence of FFSPw 1 xv , xi.The results for the probit on FFS participation are reported in Table 6. They show the importance of age,the number of family members in a household, and wealth (land and household assets) in influencing FFSparticipation. The correlation of FFS participation with the availability of labor in the household was corroboratedby farmers during our fieldwork: many non-participants cited the lack of time and availability of labor as their mainconstraint in participating in the FFS program. In order to improve the prediction of treatment assignment (criticalto matching methods), the model is intentionally over-parameterized, using many variables and quadratic terms.14Coefficient p -valueEducation of household head -0.74 0.18Quadratic term for education 0.20 0.14Age of household head -0.02 0.05Number of family members 0.21 0.02Dependency rate -0.27 0.32Total land ownership (10 hect.) 0.70 0.03Quadratic term for land ownership 1.05 0.41Value of cattle assets (100 soles) 0.01 0.76

Number of inherited livestock 0.00 1.00Value of household assets (100 soles) 0.22 0.00Quadratic term for household assets -0.01 0.00Value of farm assets (100 soles) 0.24 0.66Quadratic term for farm assets -0.23 0.21% of losses from El Nino 1.61 0.12-2.21 0.00Credit constraint 0.16 0.69Constant 0.12 0.84Number of observations 93Pseudo-R2 0.18Prediction Table:NonparticipantParticipantPredicted non-participant 40 20 60Predicted participant 8 25 3348 45 93Correct prediction rate: 70%Table 6. Farmer Field School Participation ProbitDependent variable: participation (0/1)% of losses from El Nino squaredA similar procedure (results not reported) was applied to participants of the Andino program. Prediction ofparticipation, with 62 observed participants and 181 non-participants, has a 65% correct prediction rate. The samevariables are significant in explaining participation as in the FFS prediction. The only qualitative difference is agewhich acts negatively in FFS participation and positively in Andino participation, which is telling of the differencebetween the two approaches and who might benefit most. Education is insignificant in both cases.These parameters are used to predict the probability of participationg p√x, or PPS, for the sampleP(FFS) nonFFSwhich is then used to match FFS participants with observationally similar non-participants.

Different rules of thumb could be applied to define what constitutes an observationally similar group of nonparticipants.Smith and Todd (2000) demonstrate that program impact estimates calculated using PPS methods arehighly sensitive to which method is used, but robustness can be improved by restricting matches only to thoseparticipants and non-participants who have a common support in the distribution of propensity scores. Therefore, wederive impact estimates by applying the common support condition and further check robustness by using threedifferent methods for selecting matched non-participants.15The distributions of propensity scores for FFS participants and non-participants are plotted in Figure 2.The distribution with the darker bars is the distribution of p√xfor participants. For the purpose of matching,observations with very low or very high values of p√xare eliminated, as they may indicate a true value of 0 or 1.Observations outside the support of the two distributions of p√xfor participants and non-participants were alsoexcluded from the analysis. Fifty-one observations among the non-participants were dropped in total.Figure 2. Histogram of Probability Propensity Scores for FFS Participants and Non-participants012345678910

0 0.25 0.5 0.75 1Non-participantsFFS participantsPercentage of farmersProbability Propensity ScoreThe first method for constructing a matched comparison group involves choosing a propensity score cut-offpoint, above which all households are included in the comparison group (Revenga et. al., 1994). There are no strictrules on how to choose a cut-off point, and this is often arbitrary. We will use as a threshold the average PPS (0.60)among participants. The second method assembles a comparison group by matching each program participant withthe five non-participants who have the closest p√x(Jalan and Ravallion, 2003). The crucial component of thissecond method is to include non-participants with scores that are close to the participants' scores. We restrictedmatches to those within a 0.01 PPS distance from the FFS participant. After eliminating matches that were notwithin this range, the mean difference between matches was 0.005, with a maximum of 0.0099.11 Finally, the entiresample of non-participants (within the common support) can be used to construct a weighted match for eachparticipant. We use the non-parametric kernel regression method proposed by Heckman, Ishimura, and Todd (1998)for this construction.A “balancing test” reveals whether the comparison groups created with these techniques sufficientlyresemble the treatment groups by testing whether the means of the observable variables for each group aresignificantly different (Smith and Todd, 2000). For the first and second methods, the balancing test was performed16by dividing each comparison and treatment group into two strata, ordered by probability propensity scores. Within

each stratum, a t-test of equality of means in the two samples of participants and non-participants was conducted foreach variable included in the probit on farmer participation. The results of these tests are reported in Table 7. Thenull was not rejected for all but two and three variables, respectively, for the two methods. For the third method, wetest for the equality of means in the samples of participants and their (weighted) matches. The null was not rejectedfor all but two variables at the ten percent level. Overall, 7 out of the 55 test results suggest a rejection of theequality of means at less than 10%, which is about what could statistically be expected. These results can thereforebe taken to indicate no systematic differences between the experiment and comparison groups in their observedcharacteristics. Balancing tests for the propensity score matching of Andino participants similarly show nosystematic differences in observed characteristics with their comparison groups.Method 3: WeightsDefinition of control group Entire sample(with kernel-based weights)Strata 1 Strata 2 Strata 1 Strata 2Education of household head 0.81 0.74 0.42 0.77 0.64Age of household head 0.34 0.93 0.55 0.15 0.10Number of family members 0.04 0.65 0.58 0.47 0.44Dependency rate 0.15 0.54 0.27 0.19 0.15Total land ownership 0.49 0.47 0.31 0.52 0.36Value of cattle assets 0.81 0.48 0.82 0.85 0.38Number of inherited livestock 0.98 0.36 0.85 0.63 0.75Value of household assets 0.21 0.53 0.39 0.74 0.54Value of farm assets 0.13 0.83 0.30 0.48 0.28Losses from El Nino 0.13 0.55 0.76 0.73 0.18Credit constrained 0.92 0.28 0.45 0.36 0.85Number of observations 61 62 22 22 45Method 1: Cut-off point

p -values for equality of means of variables in the participant and control groupsTable 7. FFS: Balancing Test Results for Three PPS MethodsMethod 2: Matchingclosest PPS (within .01 PPS)All farmers with PPS ≥ 0.60 Average of five non-participants withVI. Impact of FFS on knowledge6.1. Estimation based on regression with control variablesTable 8 presents the results of a regression of knowledge test scores, controlling for FFS and Andinoparticipation and for community and household characteristics, described in equation (2). The regression can bedone with both types of participants since they have the same control group (the non-Andino participants in the non-FFS villages) and the regression has a full range of interactions. The sample of observations P(FFS) nonFFSconsists of all FFS participants from FFS villages and all non-FFS villages. It shows an estimated AverageTreatment Effect AT√EReg for FFS of 7.6 percentage points for the entire sample. Using these results, the average11 One FFS participant did not have a match within this range, and thus, the treatment group was reduced to 44 in this method.17of the impact over FFS participants gives an estimated value of 13.8 percentage points for the Average TreatmentEffect on the Treated ATE √1Reg .Impact of participation on knowledge increases with land ownership, the value of household assets, and thenumber of family members. It is interesting that deriving greater knowledge from participation in FFS is notaffected by the level of education of the household head.The estimated Average Treatment Effect for Andino is 5.6 percentage points and the Average Treatment

Effect on the treated is 7.7 percentage points. The effect on knowledge of traditional extension is thus apparentlylower than that of FFS, confirming the observation made on the basis of descriptive statistics in Table 4. However,due to the very small samples of participants to the two programs, it is difficult to establish statistical significancefor this difference: With an estimated value of 2.05 (standard error 3.56) for the difference between the two averagetreatment effects, the null hypothesis that it is equal to 0 cannot be rejected at the 5% level. On the other hand, theInverse Power calculation proposed by Andrews (1989) indicates that the data show no evidence that the truedifference is less than 5.9, at the 5% level, either.An interesting difference between the impact of the FFS andAndino programs is that in the case of Andino, knowledge is not affected by land ownership and family size anddoes not increase with the value of household assets. If control over land and household assets proxies for wealth, itsuggests that FFS is better taken advantage of by the wealthier, while traditional transfer-of-technology approachescater to less endowed farmers. The FFS extension method is thus better fit for younger farmers (participation) andfor farmers with greater endowments.18Table 8. Impact of FFS and Andino on Agricultural Knowledge Test ScoresDependent variable: test score1Coefficient p -valueParticipation in FFS 7.64 0.01Participation in Andino 5.59 0.00Community characteristicsDistance from Cajamarca (kms) -0.01 0.00Dairy delivery station in community (0/1) 1.11 0.22Household characteristicsEducation of household head 0.33 0.65

Age of household head -0.03 0.47Number of family members 0.07 0.69Total land ownership (hectares) 6.99 0.18Quadratic total land -7.88 0.03Value of cattle assets (100 soles) -0.01 0.91Number of inherited livestock 0.09 0.66Value of household assets (100 soles) 0.46 0.00Value of farm assets (100 soles) 0.42 0.67% of losses from El Nino 1.18 0.33Credit constrained 1.61 0.10Interaction terms: Participation in FFS xde-meaned community characteristicsDistance from Cajamarca 0.00 0.93Dairy delivery station in community -1.63 0.71de-meaned household characteristicsEducation of household head -0.66 0.75Age of household head -0.30 0.11Number of family members 1.33 0.68Total land ownership 84.0 0.08Quadratic total land -179 0.02Value of cattle assets 0.18 0.65Number of inherited livestock -0.41 0.62Value of household assets 3.33 0.05Value of farm assets -6.01 0.23% of losses from El Nino -10.3 0.01Credit constrained 2.90 0.48Interaction terms: Participation in Andino xde-meaned community characteristicsDistance from Cajamarca 0.02 0.36Dairy delivery station in community -0.29 0.92de-meaned household characteristicsEducation of household head 1.00 0.69Age of household head 0.04 0.67Number of family members 0.56 0.47Total land ownership 23.75 0.56

Quadratic total land -111.72 0.15Value of cattle assets 0.20 0.52Number of inherited livestock 0.31 0.67Value of household assets -1.09 0.00Value of farm assets 5.65 0.38% of losses from El Nino -0.08 0.99Credit constrained 0.20 0.96Constant 19.72 0.00Number of observations 438R-squared 0.171 For FFS, the sample consists of FFS participants and farmers from non-FFS villages.19The validity of this method is based on the assumption that there is no selection bias due to unobservablesinfluencing both the choice of participation in FFS as well as the outcome. While we have argued that this is areasonable assumption for a pilot program such as FFS, we also use an informal calculation proposed by Altonji,Elder, and Taber (2002) to evaluate the potential bias that would be implied by selection on the unobservables. Theidea is the following. Consider a simplified model without interaction terms:y 0 w x, (3)where y is the knowledge score, w is an indicator of FFS participation, the parameter is the effect of FFS onknowledge, xcaptures the role of other observed factors that influence knowledge, and combines allunobservables. Under certain conditions, it is possible to show that selection on unobservables is comparable inmagnitude to the selection on observables in terms of its influence on the outcome y, in the sense that the normalizeddifference between the average values of observables and of unobservables in the two groups are the same: 12E x w x w

xw w1 E 0 1 0varE Evar. (4)Under these conditions, by estimating equation (3), we can calculate how the index of observables in the knowledgeequation varies with FFS participation, and then ask how large the normalized shift due to unobservables wouldhave to be in order to explain away the entire FFS program effect. Applying this method we find that the bias due tounobservables on the parameter would be 2.7 points out of the average 7.6 points for the estimated averageimpact. This is likely to be an upper-bound on the bias since the condition in equation (4) pessimistically assumesthat the selected covariates in the impact regression are a random sample of the full set of covariates. In any event,the bias calculation suggests that selection due to unobservables is unlikely to wipe out the measured level of impactof the FFS program on knowledge.6.2. Estimations based on PPS matching methodsTable 9 reports estimates of FFS program impact based on the Propensity Score Matching methods.Theaverage difference in test scores between participants and their matches provides an estimate of the AverageTreatment Effect on the Treated ATE √

1PSM . For all three methods, there is a significant difference between the twogroups’ scores in every category of knowledge. The scores are more than twice as high among FFS participants forknowledge of resistant varieties, and knowledge of the Andean potato weevil and the potato tuber moth, and thesevalues are very similar across all three methods. Gain and knowledge attributable to the FFS are greatest for the12 The conditions for equality of selection on observables and unobservables are that the included regressors should be a randomsubset of all factors that determine the outcome, and none of the factors dominate the distribution of program participation or theoutcome.20more technical issues such as identification of resistant varieties and knowledge of the most important pests (lateblight and Andean potato weevil).The impact estimates are robust to the different estimation methods: for the overall score, the three methodsgive a remarkably similar estimate of 14 to 15 percentage points of program impact. This is also similar to the 13.8percentage point estimate obtained in the regression method.Difference =FFS farmers Control group Average Treatment Test of ATE1 = 0Test scores: percentage of maximum score scores scores Effect on the Treated p -valueMethod 1: Cut-off pointNumber of observations 45 80Knowledge on late blight 35 24 11 0.00Knowledge on Andean potato weevil 25 1 24 0.00Knowledge on potato tuber moth 15 1 14 0.00Pesticide knowledge 29 21 8 0.00Knowledge on resistant varieties 49 17 32 0.00Total test score 34 19 15 0.00

Method 2: Five nearest matchingNumber of observations 44Knowledge on late blight 35 25 10 0.00Knowledge on Andean potato weevil 25 9 17 0.00Knowledge on potato tuber moth 15 4 11 0.00Pesticide knowledge 49 16 33 0.00Knowledge on resistant varieties 29 21 8 0.00Total test score 34 19 15 0.00Method 3: Kernel-weights matchingNumber of observations 45Knowledge on late blight 35 24 11 0.00Knowledge on Andean potato weevil 25 11 13 0.00Knowledge on potato tuber moth 15 7 7 0.04Pesticide knowledge 29 21 8 0.00Knowledge on resistant varieties 49 17 32 0.00Total test score 34 20 14 0.00Table 9. FFS: Testing Knowledge Differentials Using PPS Matching MethodsAll control farmers with PPS > .60and under common supportControl farmers with five closest PPS(within .01 PPS) under common supportKernel-weigted average of all control farmersunder common supportKnowledge scores are similarly significantly higher for Andino program participants relative to theircontrol groups, with the three matching methods and for all categories of knowledge. We compare FFS and Andinoestimates in Table 10, where the Average Treatment Effects on the Treated are computed as the averages of theresults obtained with the three matching methods. Results show that the Average Treatment Effect on the Treated ishigher for FFS than for Andino. This is particularly the case for technical issues that matter most for farmers in the

region (Tables 2 and 3): knowledge of late blight, the Andean potato weevil, pesticides, and resistant varieties. Forthe total test score, the gain in knowledge due to treatment is 86% higher for FFS than for Andino participants.21Although there is no statistical test that can be applied to these comparisons, they confirm the suggestive results ofthe regression analysis.Table 10. Differentials in Knowledge Gains: FFS vs. Andino% difference in ATE1:FFS Andino FFS over AndinoKnowledge on late blight 10.7 6.8 56Knowledge on Andean potato weevil 18.0 6.2 192Knowledge on potato tuber moth 10.7 11.4 -6Pesticide knowledge 16.3 3.6 352Knowledge on resistant varieties 24.0 17.5 37Total test score 14.7 7.9 86Average Treatment Effect on TreatedVII. From knowledge to productivityWe can measure how score, an indicator of agricultural knowledge, is related to productivity by regressingproductivity (measured by the potato output/input ratio) on knowledge score and on plot and householdcharacteristics.As the FFS program was only in its first year of operation, we cannot expect yields of FFS participants toyet reflect acquired knowledge from the FFS. This is because the output/input ratio is computed for the plots thatwere harvested during the year in which the FFS was occurring. Planting, and much of the spraying, was carried outat the very inception of the program or perhaps even before participation started. On the other hand, there is alwaysa risk of selection bias in that farmers that choose to participate in FFS programs may be the most productive

farmers anyway. For these two reasons, we choose to establish the relationship between agricultural knowledge andproductivity on the 245 plots of farmers from the non-FFS communities.We control for clustering at the household level and use an instrumental variable technique to control forendogeneity of the “knowledge score” variable. Given the cross-sectional nature of the data, it is difficult to findhousehold variables that are correlated with knowledge and do not influence productivity. Consequently we useinstruments that are statistically valid, although admittedly ad’hoc. These instruments are the average knowledgescore on varieties of farmers in the same consumption category (total monthly consumption level), which is used torepresent the household’s welfare level, its square, and its interactions with the education of the household head andwith the arable land owned by the household. The first stage regression (not shown) indicates that the instrumentsare strong predictors of knowledge scores (F-statistic F(4,222) = 14.3, p–value =0.000). The overidentification testfails to reject the null hypothesis that the instruments are statistically valid (p–value = 0.33). The results of theinstrumental variable regression are presented in Table 11. The predicted knowledge score is significant andpositively affects productivity. We find that a ten percent increase in the knowledge score is reflected in a 2.9 points22increase in the output/input ratio. By comparison, the sample mean (among control communities) for theoutput/input ratio is 7.9 with a standard deviation of 4.8.Mean Coefficient p -valueKnowledge score (0–100) (instrumented1) 15.4 0.29 0.01Plot characteristicsArea of plot (hectare) 0.27 -4.96 0.00Steep slope 0.07 1.75 0.09Rocky soil 0.06 -1.60 0.07

Fallowed last season 0.62 0.44 0.61Irrigated 0.32 3.26 0.00Irrigated and fallowed last season 0.16 -2.45 0.06Household characteristicsEducation of household head 2.4 -0.24 0.68Age of household head 47.5 -0.04 0.27Number of workers in family 5.4 0.10 0.64Workers per hectare of arable land owned 1.21 -0.08 0.77Total land ownership (10 hect.) 0.11 -3.29 0.13Value of cattle assets (100 soles) 7.59 -0.02 0.42Number of inherited livestock 0.57 0.14 0.37Value of household assets (100 soles) 0.44 -0.07 0.40Value of farm assets (100 soles) 0.57 2.43 0.02% of losses from El Nino 0.15 -1.79 0.06Credit constrained 0.28 -1.06 0.15Distance from major metropolitan area (km) 244 0.01 0.24Constant 2.27 0.58Dependent variable: potato output/input ratio 7.9 (sd 4.8)Number of plots (150 households) 245Second stage F-statistic: F(19, 144) 2.80 0.000Joint significance of instruments in first stage: F(4,222) 14.3 0.000Test of overidentifying restrictions: Chi2(3) 3.42 0.33Table 11. Impact of Score on Productivity in non-CARE CommunitiesDependent variable: Plot level potato output/input ratio1 Instruments are average knowledge score on varieties among farmers of same consumption level, itssquare, and interactions with age of household head and owned arable land.Using the coefficients from the regression in Table 11 and the score differentials reported in Table 9, wecan calculate a rough estimate of the potential impact of FFS participation on productivity. Using the calculatedscore differential of 14 percentage points from FFS participation, this implies that farmer field school participation

would have resulted in an increase of 4.1 points in the output/input ratio. This corresponds to a 52% increase overthe average observed output/input ratio of 7.9, which corresponds to the value in a normal year. Note that non-seedinputs are not taken into consideration in the productivity measure. Therefore, although higher knowledge scoreshelp increase productivity, we do not know if they result in higher profits.23VIII. ConclusionsThe challenge of the FFS approach is whether training results in higher knowledge about complex technicalissues such as IPM and whether improved knowledge in turn translates into higher productivity. Using data on asmall-scale pilot FFS program targeted to Peruvian potato farmers, this paper finds that FFS participationsignificantly enhances knowledge on pests, fungicides, and resistant varieties – all instrumental in implementingIPM practices. The robustness of the positive results of FFS participation on knowledge is demonstrated by the factthat two separate approaches used for estimating the effect of FFS yield the same result: a fourteen-percentage pointincrease in knowledge score for FFS participants.While samples of participants are too small to detect statistically significant differences, we also findsuggestive evidence that the FFS approach is more effective that the traditional transfer-of-technology approach inimparting knowledge of technical issues related to IPM to farmers. Gains in knowledge are 86% higher with FFSthat with the traditional approach used in the Andino program. These results will need to be confirmed with largersamples of participants to extension programs.We show that farmers with higher levels of knowledge have significantly higher levels of productivity, and

estimate that, by increasing knowledge, FFS participation can raise the average potato seed output/input ratio by 4.1,or approximately 52% of the average value in a normal year. Finally, we end with a cautionary note that because theFFS pilot in Peru was started only recently, we did not examine the extent of knowledge diffusion from FFSparticipants to other farmers.ReferencesAltonji, Joseph , Todd Edler, and Christopher Taber. 2002. “Selection on Observed and Unobserved Variables:Assessing the Effectiveness of Catholic Schools.” Working Paper, Economics Department, NorthwesternUniversity.Andrews, Donald. 1989. “Power in Econometric Applications.” Econometrica, 57(5): 1059–1090Birkhaeuser, Dean, Evenson Robert, and Gershon Feder. 1991. "The Economic Impact of Agricultural Extension: aReview." Economic Development and Cultural Change, 39(3): 607–650.Byerlee, Derek. 1994. “Technology Transfer Systems for Improved Crop Management: Lessons for the Future”. InJ. Anderson, ed., Agricultural Technology: Policy Issues for the International Community. Wallingford,UK: Cab International.Feder, Gershon, and Roger Slade. 1986. A Comparative Analysis of Some Aspects of the Training and Visit Systemof Agricultural Extension in India. Journal of Development Studies, 22(3): 407–28.Feder, Gershon, Rinku Murgai, and Jaime Quizon. 2003. “Sending Farmers Back to School: An EconomicEvaluation of the Farmer Field School (FFS) Extension Approach.” Forthcoming in Review of AgriculturalEconomics.Feder, Gershon, Anthony Willett, and Willem Zijp. 2001. “Agricultural Extension: Generic Challenges and the

Ingredients for Solutions.” In S. Wolf and D. Zilberman (eds) Knowledge Generation and TechnicalChange: Institutional Innovation in Agriculture. Kluwer: Boston, pp. 313–56.24Foster, Andrew, and Mark Rosenzweig. 1995. “Learning by Doing and Learning from Others: Human Capital andTechnical Change in Agriculture.” Journal of Political Economy, 103(6): 1176-1209.Heckman, James, Hidehiko Ishimura, and Petra Todd. 1998. “Matching as an Econometric Evaluation Estimator.”Review of Economic Studies, 65: 261-294.Jalan, Jyotsna, and Martin Ravallion, 2003. “Estimating the Benefit Incidence of an Anti-Poverty Program byPropensity-Score Matching”, Journal of Business and Economic Statistics， 21(1): 19-30.Kenmore, Peter. 2002. “Integrated Pest Management”. International Journal of Occupational & EnvironmentalHealth 8(3):173-174.Nelson, R.J., R. Orrego, O. Ortiz, M. Mundt, M. Fredix, and N. V. Vien. 2001. “Working with Resource-poorFarmers to Mange Plant Diseases.” Plant Disease, 85(7): 684–695.Ortiz, Oscar, and A. Valdez. 1993. “Enfoque de Sistemas y Metodologia Participativa para Desarollar MediosEscritos de Comunicacion Agricola: El caso de la Papa en la Agricultura de Substitencia.” RevistaLatinoamericana de la Papa. Vol. 5/6: 103–121.Picciotto, Robert, and Jock Anderson. 1997. “Reconsidering Agricultural Extension.” World Bank ResearchObserver. 12(2): 249-259.Praneetvatakul, Suwanna, and Hermann Waibel. 2002. "A Socio-Economic Analysis of Farmer Field Schools (FFS)Implemented by the National Program on Integrated Pest Management of Thailand." Presented at the

CYMMIT International Conference on Impacts of Agricultural Research and Development, February 4-72002, San Jose, Costa Rica.Revenga, Ana, Michelle Riboud, and Hong Tan. "The Impact of Mexico's Retraining Program on Employment andWages." The World Bank Review, Vol. 9, No. 2, 1994.Rola, A., S. Jamias, and Jaime Quizon. 2002. “Do Farmer Field School Graduates Retain and Share What TheyLearn?: An Investigation in Iloilo, Philippines.” Journal of International Agricultural and ExtensionEducation, 9(1): 65–76.Rosenbaum, P.R., and Rubin, D.B. 1983. “The Central Role of the Propensity Score in Observational Studies forCausal Effects,” Biometrika, 70: 41-55.Smith, Jeffrey, and Petra Todd. 2000. “Does Matching Overcome Lalonde’s Critique of Non-experimentalEstimators?” Working Paper, Economics Department, University of Pennsylvania.Terrazas, F., V. Suarez, G. Gardener, G. Thiele, A. Devaux, and T. Walker. 1998. “Diagnosing Potato Productivityin Farmer's Fields in Bolivia,” International Potato Center, Social Science Department Working Paper, No.1998-5, Lima, Peru.Van de Fliert, E., N. Johnson, R. Asmunati, and Wiyanto. 1999. "Beyond Higher Yields: The Impact of Sweetpotato Integrated Crop Management and Farmer Field Schools in Indonesia." CIP Program Report 1999-2000, pp. 331-342, Lima, Peru.Vasquez-Caicedo, Gloria, Julio Portocarrero, Oscar Ortiz, and Cristina Fonseca. 2000. “Case Studies on Farmers’Perceptions about Farmer Field School (FFS) Implementation in San Miguel Peru: Contributing toEstablish the Baseline for Impact Evaluation of FFS.” Report to the DECRG from the World Bank, May.

AIAEE 2005 Proceedings of the 21st Annual Conference San Antonio, TX Farmer Field School as an Effective Methodology for

Disseminating Agricultural Technologies: Up-Scaling of Soil Management Technologies among Small-Scale Farmers in Trans-

Nzoia District, Kenya David K. Bunyatta1, Dr. Joseph G. Mureithi, Dr. Christopher A. Onyango2 and Dr. Faustine U. Ngesa F.U.2

1- Ministry of Agriculture, P.O. Box 249 Iten, Kenya 2 – Egerton University, Department of Education and Extension, P.O. Box 536 Njoro, Kenya Contact person Dr. Joseph G. Mureithi Kenya Agricultural Research Institute National Agricultural Research Laboratories P.O. Box 14733, 00800 Nairobi, Kenya Tel: 0254-20-4440935 Tel/Fax 0254-20-4449810 jmureithi@africaonline.co.ke Abstract

This study was conducted to determine the effectiveness of the Farmer Field School (FFS) approach in knowledge acquisition, adoption and dissemination of soil management technologies (SMTs) among small-scale farmers in Kenya. Eight technologies were scaled-out using the FFS approach and conventional extension methods. A survey methodology with the ex-post facto research design was employed with a sample frame consisted of 940 farmers. A sample of 60 FFS graduates and 60 non-FFS (NFFS) farmers was chosen for the study. There was a significant difference (P<0.05) in knowledge acquired in SMTs by FFS compared to NFFS farmers. About half of FFS farmers had acquired over 50% of the knowledge of all the eight technologies disseminated while the majority (>80%) of the NFFS farmers had acquired less than 50% of the same knowledge. About 44% of the FFS farmers had adopted 50% of the technology components while only 17% of NFFS farmers had adopted the same percentage of the technology components.

The FFS participants were significantly (P<0.05) better disseminators of SM technologies than the non-FFS farmers. While 54% of FFS farmers had moderate to high dissemination levels, 77% of non-FFS farmers had very low to low dissemination levels. It was recommended that all stakeholders in agricultural development in Kenya be sensitized on the potential effectiveness of FFS methodology in scaling-up agricultural technologies and also monitor how the application of knowledge acquired by FFS farmers is impacting on their livelihoods. Keywords: Extension methods, comparative analysis, knowledge acquistion, technology adoption and dissemination 515 AIAEE 2005 Proceedings of the 21st Annual Conference San Antonio, TX

INTRODUCTION The farmer field school (FFS) approach has gained prominence as

an extension methodology in Kenya following its success in training Asian farmers on integrated pest management (IPM) technologies (Abate & Duveskog, 2003). It was first introduced on a small scale in 1995 by the FAO’s Special Program for Food Security (SPFS) to promote maize (Zea mays) based IPM in western Kenya. Since then over 1500 FFS have been initiated in Kenya to promote technologies for IPM for maize, vegetable and poultry production, soil fertility management, water harvesting, dairy cattle production and management of HIV/AIDS (Abate & Duveskog, 2003). The FFS approach has now been embraced by Kenya’s Ministry of Agriculture as a promising participatory extension method and is being considered for incorporation into the National Agricultural and Livestock Extension Program (Sones, Duveskog & Minjauw, 2003). The adaptive research program of Kenya Agricultural Research Institute (KARI) has adopted the methodology as an up-scaling approach for its promising technologies (Mureithi, 2003). By the end of 2003, KARI had initiated over 60 FFS and trained over 800 farmers.

The FFS approach has many attributes that makes it a truly participatory extension methodology (Leeuwis, Roling & Bruin, 1998; Dilts, 2001; Khisa, 2003). Key among them include, a) its recognition that farmers are adult learners whose training is enhanced by using non-formal adult education methods, b) that the training covers the entire crop or livestock production cycle to enable farmers fully understand all components of the technology e.g. from planting to harvesting in case of crops and a whole production cycle in case of livestock, c) its focus on group training of about 25 to 30 people to bring individual experience and strengths into the FFS and to provide individuals with group support in trying new things, d) enabling participants to focus more on basic processes (basic sciences) through field observations, analysis, discussions and presentations, and e) testing and validation of technologies during the season long training.

All FFS need technically competent facilitators, trained on season-long facilitation skills where they learn how to grow crops with their

own hands and develop management skills of local program activities that foster group dynamics (Gallagher, 2003). The FFS training follows a curriculum that is composed of weekly lessons covering the entire natural cycle of its subject. An important aspect of the weekly training is the “special topics” which are invited by farmer participants as they touch on issues affecting their farming or welfare in general. After FFS training graduates are not only equipped with knowledge on the technologies disseminated but through the approach of discovery learning used in FFS, they are empowered with skills to experiment and to solve their daily problems as individuals or as a community (Dilts, 2001).

A main question that lingers in the mind of many development workers with potential to incorporate FFS methodology into their programs is how effective the FFS methodology is in up-scaling agricultural technologies (Leeuwis, Roling & Bruin, 1998; Quizon, Feder & Murgai, 2001; Rola, Quizon & Jamias, 2002; Feder, Murgai & Quizon, 2003 and 2004). This study was therefore conducted to assess the effectiveness of FFS in knowledge acquisition, adoption and dissemination of soil management technologies (SMTs) among small-scale farmers in Yuya Location of Trans-Nzoia District, Kenya. These technologies which were developed by the Soil Management Project (SMP) of KARI (Asiabaka, Mureithi & Owens, 2003) were, 516 AIAEE 2005 Proceedings of the 21st Annual Conference San Antonio, TX

Forage production based on Napier grass established through “Tumbukiza method” and intercropped with Desmodium intortum (green leaf desmodium)

Use of high quality organic fertilizers (compost and farmyard manure) in combination with half recommended rate of inorganic fertilizers for production of maize, vegetables and fodder crops (Napier grass and desmodium).

• • • • • • • • • • Introduction of alternative legumes to common beans (Phaselous

vulgaris), e.g. groundnuts (Arachis hypogaea) , soybeans (Glycine max), Lablab (Lablab purpureus) and pigeon peas (Cajanus cajan) into the farming system

Evaluation of suitable maize varieties Quality seed production of a local vegetable known as “Sucha”

(Solanum nigrum) Low cost soil conservation methods like use of grass strips, contour

farming and terracing Use of low cost plant extracts and other local methods for control of

pests for kales, local vegetables and maize.

From 2001 these technologies were scaled-out using the FFS methodology and conventional extension methodologies (e.g., demonstrations, farm visits, farmer trainings, meetings, farmer leaflets and bulletins etc). Farmers graduated in December 2001 after going through a season long training on each of the technologies.

The specific objectives of the study were; To compare level of knowledge acquisition of the soil management

technologies between FFS participants and non-FFS farmers. To compare level of adoption of soil management technologies between

FFS graduates and non-FFS farmers. To compare level of dissemination of knowledge acquired in SM

technologies between FFS and non-FFS participants.

MATERIALS AND METHODS

Study Area The study area was Yuya Location of Kaplamai Division, Trans-

Nzoia District, North Rift Valley Province, Kenya (1.01’N, 35.01’ E). Its altitude is 1800 m above sea level and receives an annual rainfall ranging from 900-1200 mm per annum. The rainfall pattern is uni-modal, with one long agro-humid period extending from the end of March to the middle of November (Jaetzold & Schimdt, 1983). The dominant soils are humic Ferralsols (FAO, 1990) which are slightly acidic (pH-H20 5.49), low in nitrogen (0.11%), moderate in organic matter (1.64%) and low in total P (12.26 mg/kg). The farm sizes are small averaging 0.8 ha per household. Important food crops grown by farmers include, maize, beans, sweet potatoes (Ipomea batatas) and local vegetables (e.g. Sucha).

Table 1 shows eight soil management technologies that had been developed by SMP, the respective FFS implementing them, membership of each school and the number of farmers who graduated from each. The schools were facilitated by a team of researchers, extensionistists and farmers who had gone through training of trainers’ course in FFS methodology. 517 AIAEE 2005 Proceedings of the 21st Annual Conference San Antonio, TX Table 1. FFS enrolment and technologies disseminated-Yuya site, Kitale Soil management technologies

School name Members FFS graduates

Male Female Total

Forage production and utilization

Khuyetana 13 18 31 30

Use of organic/inorganic fertilizers for maize

Bikholwa 5 16 21 18

Use of organic/inorganic fertilizer for vegetable production

Bulala 18 10 28 21

Introduction of legumes other than beans

Busime 9 13 22 17

Introduction of suitable maize varieties

Twende Mbele

7 11 18 11

Quality seed production

Upendo 6 24 30 16

Mteremko 11 9 20 16

Low cost soil conservation methods

Indigenous technical knowledge for pest control

Mutua 8 14 22 16

Totals 77 115 192 140 •

A Global Survey and Review of Farmer Field School Experiences by

Arnoud Braun1, Janice Jiggins, Niels Röling, Henk van den Berg and Paul Snijders

Report prepared for the International Livestock Research Institute (ILRI) Final Report, 12 June 2006

Endelea Rietveldlaan 3

6708 SN Wageningen The Netherlands

1 Corresponding author: arnoud.braun@farmerfieldschool.net; for authors’ profiles and contact addresses, see Appendix III A Global

Survey and Review of Farmer Field School Experiences. A. Braun, J. Jiggins, N. Röling, H. van den Berg and P.Snijders

Table of contents

TABLE OF CONTENTS..................................................................................................I

LIST OF ABBREVIATIONS AND ACRONYMS...........................................................III

ACKNOWLEDGEMENTS.............................................................................................VI

EXECUTIVE SUMMARY.............................................................................................VII

1. INTRODUCTION.......................................................................................................1

2. THE ORIGINS AND EVOLUTION OF FARMER FIELD SCHOOLS.........................2

3. CURRENT GLOBAL STATUS OF FARMER FIELD SCHOOLS.............................7 Asia...........................................................................................................................................8 Evolution of FFSs in Asian FAO Programmes and Community IPM...................................8 NGOs in Asia.........................................................................................................................8 Recent adaptations and developments....................................................................................9

Sub-Saharan Africa (SSA).........................................................................................................9 South America and the Caribbean............................................................................................11 Responding to public sector collapse through collaboration...............................................11 Strengthening research and community-based agricultural development through FFS......11 Near East and North Africa......................................................................................................13 Central and Eastern Europe......................................................................................................14 Farmer Livestock School experiences......................................................................................14

4. THE BROADER PICTURE.....................................................................................15 Introduction............................................................................................................................15 Approaches based on extension and training...........................................................................15 Learning-based approaches......................................................................................................17 Intermediate forms of innovation systems...........................................................................18 Comparative studies.............................................................................................................19 What can we expect the FFS to achieve?.................................................................................19

5. IMPACT OF FARMER FIELD SCHOOLS..............................................................23 Complexity of impact evaluation.............................................................................................25 Natural and economic impact...................................................................................................26 Human and social impact.........................................................................................................27 Dissemination of impact...........................................................................................................28 Institutional impacts.................................................................................................................29 Conclusion..............................................................................................................................29

6. ADDRESSING COGNITIVE NEEDS OF LIVESTOCK FARMERS.........................31 Integrating the body of experience with extension, information and education through using the model of the livestock farmer as a cognitive agent............................................................31 i A Global Survey and Review of Farmer Field School Experiences. A. Braun, J. Jiggins, N. Röling, H. van den Berg and P.Snijders

The model of the cognitive agent explained............................................................................31 The Cognitive Agent as a “coat hanger” for understanding attempts to inform, train, educate, organise and otherwise change livestock farmers....................................................................32 A brief overview of attempts to address the cognitive needs of livestock farmers..................34 Public extension services.....................................................................................................35 Farmers organizations, producer associations and other common interest groups..............36 Private extension..................................................................................................................36 Non Governmental Organizations........................................................................................37 Public-private partnerships...................................................................................................37 Public markets, mass media, networks, expertise centers....................................................37

7. HOW EFFECTIVE IS THE FARMER FIELD SCHOOL FOR STIMULATING FARMER INNOVATION?............................................................................................38

8. HOW DOES/CAN AN FFS FIT INTO AN INNOVATION SYSTEM APPROACH? …………………………………………………………………………………………..40

9. HOW CAN RESEARCH ORGANISATIONS, INCLUDING ILRI, INTERACT WITH FFS TO INCREASE THE EFFICIENCY OF THEIR INNOVATION SYSTEMS?42

10. WHAT RESEARCHABLE QUESTIONS REMAIN TO BE ANSWERED IN RELATION TO LIVESTOCK FFS?..............................................................................44

11. REFERENCES......................................................................................................46

APPENDIX I. SHORT DESCRIPTION OF THE FFS APPROACH..........................62

APPENDIX II. GLOBAL STATUS OF FARMER FIELD SCHOOLS..........................64 Asia.........................................................................................................................................64 Sub-Saharan Africa..................................................................................................................70 South and Central America, and the Caribbean.......................................................................76 North America........................................................................................................................79 Near East and North Africa......................................................................................................79 Eastern Europe.........................................................................................................................81

APPENDIX III. AUTHORS’ PROFILES......................................................................91

ii A Global Survey and Review of Farmer Field School Experiences. A. Braun, J. Jiggins, N. Röling, H. van den Berg and P.Snijders

List of abbreviations and acronyms AAA Armenian Agricultural Academy AAS Academy of Agricultural Sciences AECI Agencia Espanola de Cooperacion Internacional AID Association for Integrated Development ARC Agricultural Research Corporation

AREX Agricultural Research and Extension Department (Govt of Zimbabwe) AsDB Asian Development Bank ASPS Agricultural Sector Programme Support ATC Advisory Training Centre CDB Cotton Development Board CENTA Centro Nacional de Tecnolgia Agropecuaria CFC Common Fund for Commodities CODA Cotton Development Authority CORPOICA Corporación Colombiana de Investigación Agropecuaria COSUDE Agenzia Suiza para el Desarrollo y la Cooperacion DAALI Department of Agronomy and Agricultural Land Improvement DAE Department of Agricultural Extension DANIDA Danish International Development Assistance DPPQS Directorate of Plant Protection Quarantine and StorageDAALI Department of Agronomy and Agricultural Land Improvement DAE Department of Agricultural Extension DED German Development Service DLGs District Local Governments DoAE Department of Agriculture Extension DoA Department of Agriculture DoI Department of Irrigation DGPCQPA Direction Générale de la Protection et du Contrôle de la

Qualité des Produits Agricoles DR Democratic Republic DRC Danish Refugee Council DSFL Dry Season Feeding of Livestock ETL Economic Threshold Level FAO Food and Agriculture Organization of the United Nations

FEDEPAPA Federación Colombiana de Productores De Papa FINNIDA Finnish Development Assistance FLS Farmer Life Schools FlivS Farmer Livestock Schools FFS Farmer Field School FFSs Farmer Field Schools FU Fertilizer Unit GoC Government of China GoE Government of Egypt GoI Government of Indonesia GoP Government of the Philippines GoPa Government of Pakistan GoT Government of Thailand

GO-INTERFISH Greater Opportunities for Integrated Rice-Fish Production Systems GRDB Guyana Rice Development Board GRPA Guyana Rice Producers Association GSMoA Gezira State Ministry of Agriculture HMG/N His Majesty’s Government of Nepal IARD Institute of Agricultural Research for Development IARS Ismailia Agricultural Research Station iii A Global Survey and Review of Farmer Field School Experiences. A. Braun, J. Jiggins, N. Röling, H. van den Berg and P.Snijders

IBAFFS Institute for Biological Agriculture and Farmer Field Schools ICB International Consulting Bureau ICM Integrated Crop Management ICP Inter-Country Programme IER Institut d’Economie Rurale IM Integrated Management INRA National Institution for Agricultural Research INRAA Institut National de la Recherche Agronomique d’Algérie INRAT National Institute for Agricultural Research of Tunisia IPM Integrated Pest Management IPPM Integrated Production and Pest Management ISWNM Integrated Soil Water and Nutrient Management ITGC Institut Technique des Grandes Cultures LIFE Local Initiatives for Farmer Extension LIFT Local Initiatives for farmer’s Training LVV Ministerie van Landbouw, Veeteelt en Visserij MAFF Ministry of Agriculture, Forestry and Fisheries MAFFS Ministry of Agriculture, Forestry and Food Security MAC Ministry of Agriculture and Cooperatives MAESA Ministry of Agriculture, Education and Social Action MAG Ministerio de Agricultura y Ganaderia MAGFOR Ministerio Agropecuario Forestal MALMR Ministry of Agriculture, Land and and Marine Resources MAPA Ministério da Agricultura, Pecuária e Abastecimento MARD Ministry of Agriculture and Rural Development

MARNDR Ministry of Agriculture, Natural Resources and Rural Development MASL Mahaweli Authority of Sri Lanka MAWMF Ministry of Agriculture, Water MAWRD Ministry of Agriculture, Water and Rural Development MAWR Ministry of Agriculture and Water Resources MBESC Ministry of Basic Education, Sports and Culture MDS Ministério do Desenvolvimento Social e Combate à Fome MHSS Ministry of Health and Social Services MoA Ministry of Agriculture MoAC Ministry of Agriculture and Co-operatives

MoE Ministry of Education MTT Finnish Institute of Plant Protection MWACW Ministry of Women Affair’s and Child Welfar NARC National Agricultural Research Centre NARC-Nepal National Agricultural Research Council (Nepal) NATESC National Agriculture Technical Extension and Service Centre NBC National Biodiversity Center ncda no consistent data available nda no data available NDRE National Directorate for Rural Extension NGO Non-Government Organization NOPEST New Options for Pest Management NPDP National Potato Development Programme NRCS Namibia Red Cross Society NRM Natural Resource Management OCHA Office for the Coordination of Humanitarian Affairs (UN) OHVN Opération Haute Vallée du Niger ORC Ohangwena Regional Council PDA Provincial Department of Agriculture PDAFF Provincial Department of Agriculture, Forestry and Fisheries PPD Plant Protection Department iv A Global Survey and Review of Farmer Field School Experiences. A. Braun, J. Jiggins, N. Röling, H. van den Berg and P.Snijders

PPI Plant Protection Institute PPPS Provincial Plant Protection Stations PPRS Plant Protection Research Institute PPS Plant Protection Station PPSD Provincial Plant Protection Sub-Department PROMIPAC Programa de Manejo Integrado de Plagas en Centroamérica PTD Participatory Technology Development RADA Rural Agricultural Development Authority RAS Rural Advisory Service RMA Risk Management AgencyRRN Rural Reconstruction Nepal SDC Swiss Development Coorporation SEARICE South East Asia Regional Institute for Community Education SFFP Integrated Soil Fertility and Fertilizer Management Project

SHABGE Strengthening Household Access to Bari (homestead) Gardening Extension SPI Soil Productivity Improvement SPPS Strengthening Plant Protection Services Project STSS Soil Testing and Service Section TITAN Trainer’s Association of Nepal ToF Training of Facilitators ToT Training of Trainers UNDP United Nations Development Programme USAID United States Agency for International Development USDA United States Department of Agriculture VCC Vietnam Cotton Company WB World Bank WN World Neighbours WNG World Neighbours Guatemala WR World Relief WUR Wageningen University and Research Centre v A Global Survey and Review of Farmer Field School Experiences. A. Braun, J. Jiggins, N. Röling, H. van den Berg and P.Snijders

Acknowledgements The authors wish to thank the International Livestock Research Institute (ILRI) for granting this consultancy to the team of authors. Keith Sones, Bruno Minjauw and Kim Groeneweg are specifically thanked for their comments and inputs to the drafts of this report.

Section 3 and Appenix II would not have been possible without the inputs from a larger group of Farmer Field School practitioners from around the world. Particular thanks go to Kevin Gallagher for providing contacts addresses of FFS practitioners. We appreciate the inputs from all FFS practionioners that have responded to the request for inputs that has been sent out: Clarissa Adami, Iftikhar Ahmad, Souhila Aouila, Randy Arnst, Fantahun Assefa, Joost Bakkeren, Sajeda Begum, Hein Bijlmakers, Anna Blok, Mohamed Bouhache, Margriet Bredewold, Robert W. Caudwell, Ngin Chhay, Jacqueline Chenier, Philip Chung, Naomi Commodore, Loy Van Crowder, Jens Peter Tang Dalsgaard, Soniia David, Russ Dilts, Deborah Duveskog, Mohamed Elansary, Hans Feijen, Elske van de Fliert, Marjon Fredrix, Esbern Friis-Hansen, Edson Gandarillas, Lydda Gaviria, Brice Gbaguidi, Moahamad Gomaa, Femke Griffioen, Kim Groeneweg, Paco Guevara, Daniel Gustafson, Lars Hein, Ole Hendriksen, Alfredo Impiglia, Jayasundara, Ricardo Labrada, Alida Laurense, Vyju Lopez, Jørgen Karlsen, Ganesh Kumar, Eugenio Macamo, Francesca Mancini, Dave Masendeke, Michael McGuire, Bruno Minjauw, Kharrat Mohamed, Hasimi Mzoba, Jacob Ngeve, James Okoth, Peter Ooi, Oscar Ortiz, Palaniswamy Pachagounder, Larry Paul, Neiburt Phiri, Francis Porras, Yang Puyun, Jan Rijpma, Rodnez Pierre, Alfredo Rueda, Joseph Rusike, Nune Sarukhanian, Adrian Shuhbeck, Bill Settle, Stephen Sherwood, Manzoor Soomro, Ad Spijkers, Julianus Thomas, Jan Venema, Janny Vos and her CABI team, Edith van Walsum, Handoko Widagdo, Esther Wiegers, Siebe van Wijk, Midori Yajima, Piao Yongfan, all participants of the May 2005 Kenya FFS Networking and Coordination workshop and others who have contributed but have not been mentioned.

Arnoud Braun, Janice Jiggins, Niels Röling, Henk van den Berg and Paul Snijders

vi A Global Survey and Review of Farmer Field School Experiences. A. Braun, J. Jiggins, N. Röling, H. van den Berg and P.Snijders

Executive Summary 1. Farmer Field Schools evolved initially to address the challenge of ecological heterogeneity and local specificity in pest management, by supporting ecologically-informed decision-making by farmers that would allow them to reduce pesticide use, improve crop management and secure better profit margins.

2. Classic FFSs rely for their effects on the development of learner-centred curricula for experiential learning that takes place in the field, allowing producers to observe, measure, analyse, assess and interpret key agro-ecosystem relationships as the basis for making informed management decisions. The adult education concepts and principles that underlie the design of curricula and of the learning cycle process have proven robust in all areas where FFSs have been developed.

3. FFSs have spread rapidly to all continents since their first introduction in 1989 in Indonesia, where Integrated Pest Management FFSs were developed to help farmers deal with the pesticide-induced problem of rice brown planthoppers in irrigated rice. As the concept has spread, it has been adapted for a wide range of crops (including tree crops such as bananas, various high value crops such as vegetables and fruits, industrial crops such as cotton, cocoa). FFSs curricula and learning processes also have been developed for the livestock sector (dairying, veterinary care, poultry and integrated rice-duck systems, goat husbandry, aquaculture and fishing), for land productivity issues (land and water management, soil fertility, land degradation), for a range of social and health issues, such as food security, HIV/AIDS and vector-born diseases, and environmental issues, such as water quality. These innovations have brought new types of participants within its ambit, including school children.

4. In the course of the spread, adaptations have been made not only to suit the content and specific purpose but also in the methodology. Innovations here include community-based selection of participants, “commercial plots” that enable participants to recover (some of) the costs of running a school, farmer facilitators, spatially clustered FFFs,

and a range of community-based institutional developments that capitalize on the self-confidence and leadership capacities created through the FFSs.

5. FFSs are not a universal panacea for development, nor are they a substitute for more familiar technology-centred or profit-driven approaches to rural development, such as extension, credit cooperatives, core-estates with outgrowers, farmer training centres, or the use of mass media. They share some of the features of other participatory approaches, such as Participatory Technology Development, that seek to catalyse farmer-driven development.

6. On the present evidence they seem best suited for (i) problems and opportunities requiring a location-dependent decision or management, (ii) issues that entail articulation and implementation of changes in behavior within the farm enterprise, household, and community or among institutions at varying scales of interaction, and (iii) situations that can be improved only through development and application of location-dependent knowledge.

7. Their comparative advantage relies on skilful incorporation of the following principles: (i) learner-centred, field based, experiential learning; (ii) observation, analysis, assessment, and experimentation over a time period sufficient to understand the dynamics of key (agro-ecological, socio-ecological) relationships; (iii) peer-reviewed individual and joint decision-making based on learning outcomes; (iv) individual and group capacity building.

8. They are vulnerable to loss of quality (and thus impact) particularly in terms of: (i) poor or inappropriate curriculum design; (ii) inadequate attention to the quality of the learning process; (iii) poor or inappropriate facilitation.

9. They are not meant for technology transfer or the delivery of simple messages – as such they do not have a comparative advantage and are also not cost effective for those purposes. FFS were designed to be time-bound with a built-in exit strategy: graduation. Originally the FFS itself is not meant to be sustained. However, the impact of FFS in terms of

economic, social, environmental and political assets are hoped to be sustained. Therefore a livelihood analysis is perhaps more appropriate for sustainability assessments. FFS can be a “stepping stone” to self-sustained groups in some situations. The FFS format builds sustainable human and social capital needed for next step actions among farmers such as

vii A Global Survey and Review of Farmer Field School Experiences. A. Braun, J. Jiggins, N. Röling, H. van den Berg and P.Snijders

collective marketing of produce and lobbying through farmer networks, savings groups and other associations that are sustained as independent groups, no longer registered by projects as “outputs”.

10. There is a need for experimention on how the effects of FFSs might be augmented in purposeful combination with mass media, folk media, extension activities and training.

11. The impacts of FFSs have been variously measured. No agreement as yet exists as to what to measure, how to measure, or how to assess the results of the measurement of impacts. The lack of consensus arises in part because of disputes over whether to classify FFS as an educational investment or as an extension activity and whether the important impacts are those relating to change in practice, knowledge, or technology used, productivity, and profitability, or whether changes in human and social capacity, and impacts on human health and the environment, are as important. There is also no agreement as to the weight to be given to participants’ own appreciation of the difference a FFS might have made to their lives, compared to objective measurements.

12. A particular concern regarding impact relates to the diffusion effect of FFSs. If the FFS is regarded as an educational investment, this could be considered the “wrong” question – what a student learns at school is not expected to diffuse widely to those who do not attend. Preliminary data suggest that information, and simple practices that can be observed by non-participating farmers, do diffuse from FFS participants, to some extent, but not the self-confident knowledge and skills in problem-solving required for the kinds of purposes for which FFSs seem best suited (see point 6, above).

13. Another concern is the sustainability of FFSs impacts. There is insufficient long time series data to assess this definitively but the weight of the evidence so far suggests a potential for significant longer-term impact.

14. This appears to be achieved principally through the institutional innovations FFS alumni are able to set in place, or bring about together

with other actors, at local levels. The chances of such innovations occurring appear to be strengthened if care is given in the implementation phase to the longer term prospects (e.g. in the processes and criteria used for participant selection and site selection), follow up support is given to farmer facilitators and FFS alumni, and farmer-driven network development is encouraged.

15. There has been relatively little experience in adapting the FFS concept to the needs of livestock farmers. However, there is evidence both from practice and theory that livestock farmers in Africa, too, are facing the kinds of conditions and challenges noted in point 6 above. They thus could benefit substantially from further testing of the contribution FFSs might make to meeting producers’ needs for knowledge, enterprise organisation, and the discovery of location-dependent options for development.

16. FFSs hitherto have tended to focus on bringing a limited set of actors into effective relationships and social spaces for shared learning. However, to achieve impacts over the longer term in the livestock or other sectors, as noted in point 13 above, may require changes in larger sets of relationships and institutional arrangements. Evidence does not support the assumption that “markets” will organise themselves to set in place the institutional arrangements that would support the achievement of the Millennium Goals. Overall, the institutional aspects of innovation systems have not been well appreciated in FFS programmes, nor the effects studied from this perspective. There is scope here too for further exploration of the role of FFSs from an institutional perspective, i.e. their contribution to innovation systems that meet the multiple goals desired.

17. On the other hand, it has been emphasised that the sustainable, local-level, institutionalised gains noted under point 14 above, can be negated or diminished if the framework conditions are hostile or unsupportive (e.g. policies and regulations that allow or promote the use of toxic chemicals, or that suppress citizens’ self-organising capacities and initiatives, or that hold farm gate prices down). Action at other scales

and hierarchical levels would be necessary to bring any required adjustment in the framework conditions.

18. A research organization such as ILRI could make a strong contribution to the further development and testing of the contribution of FFSs by: (i) supporting the design of science-based curricula and learning processes suitable for livestock farmers in specific places; (ii) contributing to the methodological development of impact assessment tools and procedures, as well as carrying out impact assessment

viii A Global Survey and Review of Farmer Field School Experiences. A. Braun, J. Jiggins, N. Röling, H. van den Berg and P.Snijders

studies in the livestock sector; (iii) testing the (limits of the) comparative advantages of FFSs in relation to the sub-points noted in point 6 above; (iv) exploring how to amplify and augment the impacts of FFSs by skilful and purposive combination of FFSs with other investments; (v) testing how to support FFSs alumni so that local level institutional innovations arise and can be sustained; (vi) investigating the role of FFSs from the perspective of developing location-dependent innovation systems.

ix A Global Survey and Review of Farmer Field School Experiences. A. Braun, J. Jiggins, N. Röling, H. van den Berg and P.Snijders

2 The authors of this document are Arnoud Braun, Janice Jiggins, Niels Roling, Henk van den Berg and Paul Snijders. Short FFS-relevant biodata of each of the authors is provided in Appendix III. 3 A formalised network of FFS contacts does not exist up to this point. However, at the global level the demand for such a network does exist. Based on this demand Endelea and partners have developed a proposal for funding a Global FFS Network and Resource Center. A list of contacts will become available through http://farmerfieldschool.net/. As a result of the survey carried out for this review a preliminary contact list of potential FFS national nodes has been compiled (Appendix 2, Table II.1 - contacts).

1. Introduction The Farmer Field School (FFS) has become an innovative, participatory and interactive model approach for farmer education in Asia, many parts of Africa, Latin America and more recently also introduced in the Middle East, North Africa and Eastern/Central Europe. The approach has been used with a wide range of crops and has subsequently expanded to topics such as livestock, community forestry, HIV/AIDS, water conservation, soil fertility management, food security and nutrition. The aim of an FFS is to build farmers’ capacity to analyse their production systems, identify problems, test possible solutions and eventually adapt the practices most suitable to their farming system. The knowledge acquired during the learning process enables farmers to adapt their existing technologies to be more productive, profitable, and responsive to changing conditions, or to test and adopt new technologies. A short description of the elements of the FFS approach is presented in Appendix I.

FFSs are spreading and adapting at an enormous speed over the globe in terms of geographical distribution and entry points/topics. However, concerns have been expressed by various implementing organisations about the relative cost of the FFS approach compared to other extension approaches, the time consuming character of the approach as well as the impact the FFS approach achieves. The management of the International

Livestock Research Institute (ILRI) would like to know whether the concerns expressed by others are valid. For this reason ILRI is developing a “Livestock Farmer Field School position paper” for ILRI management and board, and other interested parties that will address the fundamental question “How and with what intent should ILRI be working on FFS?”

This review document will serve as a key background document for the above-mentioned ILRI position paper. This comprehensive review is based on formal and grey literature, and experiences of the authors2 and a network of FFS contacts3. It will address the following key elements: • Origins and evolution of FFS • Current status of FFSs globally (in terms of geographic expansion and

in terms of topics), including global experiences of livestock FFS • FFSs in the broader education and extension picture • Impact or lack of impact of FFSs • Effectiveness of the FFS approach for stimulating farmer innovation • Cognitive needs of livestock farmers • How can research organizations, including ILRI, interact with FFSs to

increase the efficiency of their innovations systems? • What researchable questions remain to be answered in relation to

livestock FFSs?

The references in this report have been numbered (see list of references in section 11). In the text each reference is referred as follows: (224) – this is reference no. 224 in the list of references (section 11). 1 A Global Survey and Review of Farmer Field School Experiences. A. Braun, J. Jiggins, N. Röling, H. van den Berg and P.Snijders

2. The origins and evolution of Farmer Field Schools

This section will briefly cover the origins and evolution of Farmer Field Schools

The FFS approach emerged out of a concrete, immediate problem. Farmers in Indonesia were putting their crops, their health and their environment at severe risk through massive abuse of highly toxic pesticides promoted aggressively by private industry and government. Pest species were becoming resistant and in some cases resurgent. What was called for was a large-scale decentralised programme of education for farmers wherein they become “experts” in managing the ecology of their fields – bringing better yields, fewer problems, increased profits and less risk to their health and environment (68). The Integrated Pest Management Farmer Field School (IPM-FFS) and a corresponding large-scale Indonesian programme were developed in response to these conditions. The genesis of integrated pest management (IPM) was a response to the emergence of problems associated with the reliance on chemical controls for insect pests by governments, extension systems and farmers. The search for solutions to these problems led to the development of a more holistic view of what constituted an agro-ecosystem and how human interventions could either enhance or disrupt one. More on IPM development in the context of the FFS approach can be found in Chapter 6 of the book “From farmer field school to community IPM” (224). FFS alumni are able to not only apply IPM principles in their fields, but also to master a process enabling them to help others learn and apply IPM principles, and organise collaborative activities in their communities to institutionalise IPM principles. A good field school process ensures these outcomes. The educational concepts underpinning the FFS approach are drawn from adult non-formal education. These concepts have been found to be relevant across the many countries and cultures in which the FFS approach has been used, and have proven to be empowering for farmers. More on these concepts that underlie the learning activities found in a field school can be found

in Chapter 5 of the book “From farmer field school to community IPM” (224).

One of the biggest problems with many of the developments in IPM over the years has been the tendency to generalise and make recommendations for farmers across large and highly heterogeneous areas. This has been true for all manner of input recommendations including fertilisers, pesticides and rice varieties. This problem, ecological heterogeneity, has also severely limited the effectiveness of government monitoring and forecasting systems. All of these practical issues vary on a small spatial scale. This local specificity requires that farmers become (IPM) experts. The main crop protection approaches since the late 1960s, from the perspective of donor support, are presented in Table 1. The recommendations or decision criteria of each approach reveal a steady progression in the accommodation of ecological heterogeneity and farmer control of agro-ecosystem management.

Governments across Asia have enacted policy in support of one or more of the four approaches presented above. Some countries have supported each of the approaches over the last four decades, often using more than one approach at the same time. Countries have often adopted new approaches without abandoning old approaches, despite glaring contradictions. Presented in roughly chronological order of emergence from left to right, these four approaches place an increasingly larger burden on the user in terms of ecological knowledge, observation and analysis. Each successive approach requires more data for decision-making and the decisions made cover increasingly smaller units of area and time. This increased precision in decision-making, not surprisingly, has led to better control of insect pests and reduced use of pesticides. The FFS approach was designed to address the problem of ecological heterogeneity and local specificity by placing the control of small-scale agro-ecosystems in the hands of the people who manage them (224).

2 A Global Survey and Review of Farmer Field School Experiences. A. Braun, J. Jiggins, N. Röling, H. van den Berg and P.Snijders

4 In Agroecosystem Analysis (AESA) in the classical FFS, crop growth stages, presence and abundance of pests and beneficial insects, weather, soil and overall crop conditions in contrasting plots in a FFS, are recorded by farmers each week on a poster - a large piece of paper – using skethches and symbols. The purpose of the drawing is to stimulate close observation of ecological and climate features that stimulate the crop.

Table 1. Pest control approaches in tropical irrigated rice (224) Calendar-based applications

Surveillance systems

ETL-based decisions by farmers

Farmers as IPM experts

Farmers, in this approach, apply insecticides based on number of days post-sowing or transplanting.

Goal: prophylactic control of pest populations. Relies on broad recommendations and assumes homogeneity among planting conditions.

Developed in 1960s.

Usually an activity of agriculuture departments. Based on ETLs developed at national level to be applied in widely differing conditions.

Goal: insure national yield targets achieved by usiung professional pest control agents.

Emerged in 1970s as

The count-and-spray approach relies on use of criteria that assumes homogeneity across all local agro-ecosystems.

Goal: employ control tactics at predetermined pest population levels to avoid population levels to avoid economic loss.

ETLs appeared with advent of surveillance

Farmers as decision makers; decision based on analysis of agro-ecosystem4.

Goal: farmers as IPM experts taking action based on analysis of their agro-ecosystem; pesticide-free rice production.

FFSs introduced in 1990, has led to a rapid growth in number of

pesponse to massive pest outbreaks.

systems, promoted to farmers in 1980s.

farmer IPM experts.

Farmer Field Schools: emerging issues & challenges 279Methodology development forparticipatory monitoring andevaluation of farmer field schoolapproach for scaling up the adoptionof agricultural technologiesJoseph G. Mureithi1, Festus M. Murithi1, Chigozie C. Asiabaka2,Jane W. Wamuongo1, Lawrence Mose1 and Benjamin Mweri3The farmer field school (FFS) approach was adopted as one of the methodologies to scale up promisingagricultural technologies developed by two Kenya Agricultural Research Institute (KARI) projects: theSoil Management Project and the Legume Research Network Project. The Food and AgricultureOrganization (FAO) had earlier promoted the FFS approach in the coastal and western parts of Kenyato scale up agricultural technologies with promising results. Consequently, researchers in the twoKARI projects began using this approach during the long rainy season in early 2001. Unfortunatelythe frameworks to assess the impact of this approach on farmers’ adoption behaviors were lacking. Asix-day workshop was held in March 2002 with the following objectives: (a) to expose participants tothe basics of participatory monitoring and evaluation (b) to jointly design and develop participatory

tools for internal monitoring and evaluation of the effectiveness of FFS as an approach for upscalingadoption of technologies, and (c) to develop participants’ skills in analysis and reporting forparticipatory monitoring and evaluation (PM&E). A total of 35 participants attended the workshop.The workshop began with an introduction to the basic concepts and principles of participation,monitoring, and evaluation. Participants were then divided into groups for brainstorming sessionsaimed at identifying the PM&E measurements/outcomes and indicators. After days of brainstormingand participatory activities, measurements and indicators were identified by each group and synthesizedin a plenary session. Techniques and tools for PM&E of FFS using the harmonized measurements andindicators were then developed. The methodology is now being used in the field. This paper discussesthe mechanics followed in addressing the workshop objectives and also the relevant measurements/outcomes, indicators, and tools for PM&E of the different stages of the farmer field school process.The Kenya Agricultural Research Institute (KARI) is a national agriculturalresearch organization that contributes to the national goals of ensuring foodsecurity, poverty alleviation and environmental protection (KARI 2000). Itundertakes this by raising agricultural productivity and incomes on a sustained basisthrough technology generation and dissemination in close cooperation with farmers,extension staff, and other stakeholders. In particular, KARI emphasizes generating1 Kenya Agricultural Research Institute.

2 Federal University of Technology, Owerri, Nigeria3 Coastal Development Authority, Kenya.280 FFS monitoring & evaluationtechnologies, which are appropriate to smallholders, gender sensitive, and take intoaccount existing local knowledge. Due to declining agricultural production and risinglevels of poverty and food insecurity, KARI is keen to demonstrate the relevance andpotential impact of its technologies on the livelihoods of its beneficiaries, the farmersof Kenya.Disseminating technologies is basically the responsibility of the publicextension service and other extension service providers, including nongovernmentalorganizations and the private sector (Muchena and Gicheru 2001). Given the needfor increased adoption of technologies by rural farming communities, KARI has beenadopting various approaches to strengthen its working relationships with otherdevelopment agencies to enhance the dissemination of agricultural technologies andinformation. The farmer field school (FFS) is one such approach that is currentlybeing used by KARI. Others include: farmer participatory research (FPR),participatory rural appraisal (PRA), participatory learning and action research (PLAR)and agricultural technology and information response initiative (ATIRI).The FFS was chosen since it has been used successfully in some Asiancountries, e.g., the Philippines and Indonesia (Pontius et al 2000) to promote integratedpest management technologies for rice production. The FFS is a participatory

approach that uses nonformal adult education methods based on experimentallearning techniques and participatory training methods (Miagostovich et al 1999).The FFS approach shifts from targeting farmers with preset extension messagestowards building on and improving farmers’ capacity to analyze their farming systemsand practices, and to develop and test possible solutions that address their prioritizedneeds, combining local and scientific knowledge. The FFS approach emphasizeslearning by doing. Learning takes place in the field and is normally designed to lasta full growing/cropping cycle. This enables farmers to fully participate inimplementing all components of the technology from planting to harvesting. Thelearning process provides farmers an opportunity to observe and reflect on theadvantages and disadvantages of the technologies and thereby make informeddecisions on whether to adopt them or not.Farmer field schools are not new in Kenya; the first ones were established in1994-95 following the original model promoted by FAO in Indonesia. Similar to thosein Southeast Asia, most FFS centered on integrated pest management (IPM) on variouscrops, with many focusing on vegetable and poultry production. In 1996 the FAO’sSpecial Program for Food Security initiated FFS in the western province of Kenya inKakamega, Bungoma, and Busia Districts and later in the Kenyan coast (Khisa 2000).

The schools in western Kenya have been reported to increase crop yield by up tothree times and reduced chick mortality from 80% to 20% (Abate 2000). In Kenya FFShave been led mainly by extensionists and have been used to train farmers on onlyone technology (Augusta Abate, personal communication).KARI’s farmer field school pilot projectThe FFS pilot project commenced in March 2001 and aimed at incorporating the FFSapproach in the Soil Management Project (SMP) and Legume Research NetworkProject (LRNP) of KARI. The SMP and the LRNP were initiated in 1994 to combatsoil fertility decline in smallholder farms in Kenya. The SMP was implemented throughFarmer Field Schools: emerging issues & challenges 281two KARI Centers: the National Agricultural Research Center at Kitale and theRegional Research Center at Kisii. The SMP adopted the farmer participatory research(FPR) approach to implement research activities so that farmers and otherstakeholders could actively participate in technology development and transfer. Inaddition to decline in soil fertility, farmers identified lack of suitable crop varietiesand livestock feed as important constraints limiting smallholder agriculturalproduction that the project needed to address.The LRNP was began as a legume screening network to primarily screensuitable green manure legumes in 11 sites across the country from 15 m to 1900 masl. The Network expanded its activities to include coordinated studies in legume

residue management, evaluation of legume green manure as a component ofintegrated soil management, and livestock feeding studies based on selected legumes.The first phase of these projects ended in 2000 after being on the ground forsix years. At the end of the phase about 10 technologies were identified as beingready for scaling up (i.e. wide-scale dissemination in neighboring villages and regionswith similar agroecological characteristics as the study sites). These technologiesinclude:• Improved preparation, management, and use of organic manures to improvesoil fertility.• Different combinations of organic and inorganic fertilizers for maize, fingermillets, forages, and vegetables (kales and cabbages).• Soil-improving green manure legumes.• Low-cost soil conservation structures.• Bean varieties tolerant of beanfly infestation and root rot.• Food legumes other than beans for intercropping with maize.• Suitable forages for water-logged soils.• High-yielding forage species for milk production.• Suitable crop varieties for different agroecological zones.• Plant extracts for controlling crop pests.The FFS was one of the scaling up approaches adopted by the two projects indisseminating the technologies. Others included the conventional group extensionapproach and farmer research committees (FRC) as dissemination agents. The FFSwas adopted on pilot basis for three years beginning March 2001 by five KARI Centers

- Kitale, Kakamega, Kisii, Embu, and Mtwapa (Figure 1).The FFS pilot project has six major activities:1. FFS sensitization workshop.2. Training of trainers course (ToT) on the FFS approach.3. Development of farmer training curricula on the technologies to be scaledup.4. Development of participatory monitoring and evaluation tools for theFFS approach.5. Support for four MSc students.6. Running of about 45 FFS in five KARI centers.282 FFS monitoring & evaluationThese activities are briefly described below.FFS sensitization workshop. This workshop was held on 6-8 March 2001 in westernKenya. Its primary objective was to sensitize senior managers of KARI and the Ministryof Agriculture and Rural Development (MoARD), researchers and extensionistsimplementing SMP and LRNP, and farmers on the FFS approach for informationtransfer and scaling up of agricultural technologies. About 90 participants attendedthe workshop. The workshop covered the genesis of FFS approach and its principlesand concepts; FFS ToT course and running an FFS in the field; development of FFStraining curricula; monitoring and evaluation of FFS; and FFS for integrated soilfertility and nutrient management and conservation. Country experiences on theFFS approach from the Philippines, Indonesia and Kenya were shared during theworkshop.

Training of trainers (TOT) course on FFS approach (Mweri and Khisa 2001). The aim ofthis course was to equip the SMP and LRNP staff with methods, skills, attitudes, andknowledge to design, facilitate, and implement FFS in their project mandate areas.Participants came from KARI centers at Kitale, Kisii, Kakamega, Embu, and Mtwapa.The course had two parts: the first part covered FFS theory and the second part wasa season-long training in the field. FAO Kenya provided two facilitators to conductthe training. The first part was held at Egerton University from 12-17 March 2001.Figure 1. KARI Centers running farmer field schoolsKitaleKakamegaKisiiFFS SITESRainfallOver 1000 mm500 - 1000 mm0 - 500 mmFarmer Field Schools: emerging issues & challenges 283Topics covered introduction to FFS methodology, steps in conducting FFS, organizingand managing FFS, and nonformal education methods. It also included field exercises,group discussions, and plenary sessions. During the training participants developedtentative workplans for schools they plan to initiate in the field. They also developedtentative training curricula on technologies to be scaled up.The second part of the ToT was a season-long field-based training on how to

run a successful FFS. The workplans developed during the first part of the trainingwere used to initiate and run the schools. KARI Centers in Kitale and Mtwapa startedtheir schools in April 2001 because the long rainy season had just begun in theirsites. Schools in Kisii were initiated in May/June, while in Kakamega they were startedin late June. Embu was the last to start its school in late August 2001. Table 1 givesdetails on the FFS that were formed and when they were terminated. Figure 2 showsFFS participants inspecting and collecting data from a vegetable plot in Kitale.The FAO trainers provided technical backstopping and visited Kitale everyfirst Monday of the month and Kisii every third Thursday of the month.Development of farmer training curricula on technologies to be scaled up. During part oneof the ToT course participants developed draft training curricula for the FFS in theirrespective project areas. These draft curricula formed the basis for preparing weeklylessons of the FFS. The ToT participants met once a week to prepare the lessons forthe following week and also to improve on the previous week’s lesson using feedbackfrom farmers. At the end of the ToT, the weekly lessons were compiled into a farmertraining curricula for each of the technologies to be scaled up. Participants wereencouraged to document technologies being demonstrated at different stages, whichwere to be used to enhance the quality of the curricula.

Figure 2. FFS participants inspecting and collecting data from a vegetable plot in Kitale284 FFS monitoring & evaluationTable 1. Summary report of farmer field schools initiated during the season-long training of trainers course.KARICenterName of farmer field school(FFS)Technology being scaled up No. of schoolmembersMale FemaleDate initiated Date terminated1. Bikholwa (Action) FFS Combinations of organic and inorganicfertilizers for maize production18 4 10 April 20012. Bulala (Unity) FFS Food legumes other than beans 15 10 20 April 20013. Busime (Love) FFS Management of organic and inorganicfertilizers for vegetable production5 12 20 April 20014. Twende Mbele (Moveforward) FFSSuitable maize varieties for Kitalemandate region4 8 30 April 20015. Upendo (Love) FFS Quality seed production in smallholderfarms7 23 10 April 20016. Khuyetena (Helping oneanother) FFSForage crops establishment,management, and utilization12 11 20 April 2001

7. Mteremko (Steep slope) FFS Low-cost soil conservation measures 5 9 14 May 2001Kitale8. Mutua (Last born) FFS Use of plant extracts to control crop pests 9 16 21 May 2001December 20021. Riboba (cultivated plot) FFS Combinations of organic and inorganicfertilizers10 18 4 May 2001 April 20022. Mlango (Door) FFS Improved soil conservation measures 29 23 4 May 2001 August 20023. Etono (small ediblemushrooms) FFSIntegrated pest management on beanproduction8 19 27 June 2001 April 20024. Keroka FFS Improved fodder production 25 20 10 June 2001 August 20025. Riomwando (Inheritance) FFS Finger millet varieties tolerant to blastdisease5 27 10 July 2001 April 2002Kisii6. Umoja (Togetherness) FFS Use of legumes that improve soil fertility 11 25 13 June 2001 August 2002Kakamega Malanga FFS Green manure technologies for soil fertilityimprovement38 25 June 2001 September 2002Embu Karurina FFS Upscaling green manure technology 31 August 2001 October 2002Mtwapa Jembe (Hoe) FFS Combination of green manure legumewith FYM and inorganic fertilizers7 8 28 March 2001 September 2002Farmer Field Schools: emerging issues & challenges 285Development of participatory monitoring and evaluation (PM&E) tools for the FFS. This

was to be done during the methodology development workshop and by four MScstudents who were expected to undertake research to refine the FFS process and testtools developed during the workshop.a) PM&E methodology development workshop. The aim of the workshop was tojointly develop tools/frameworks for PM&E on the effectiveness of FFS as an approachto upscaling soil management technologies and information. This workshop is thegist of this paper and is discussed in greater detail in the later sections.b) Support for four MSc students. The MSc training was included in the project sothat the students could undertake research that would contribute to developing andrefining M&E tools for the FFS process. They were also expected to evaluate the rateof technology spread and its impact on smallholder farming. Table 2 shows thestudents that are on MSc training.New schools initiated in March/April 2002. So far a total of 30 new FFS havebeen initiated in three KARI centers (Table 3). Twenty-nine of them were farmer-ledand one was extension-led. The farmer-led ones are near the old sites and aretechnically backstopped by researchers and extensionists.Participatory monitoring and evaluation of the FFS approachKARI embraces the need for an elaborate and systematic planning, monitoring, andevaluation (PM&E) system to generate information that will show the impact of itsactivities at different levels (KARI 1998). In most instances, planning accounts for

majority of the time spent on PM&E but with very little internal evaluation takingplace. KARI is currently emphasizing the need for participatory planning, monitoring,and evaluation so that there is ownership of the process among the researchmanagers, scientists, development partners, extensionists, other agricultural serviceproviders, and the ultimate beneficiaries - the farmers. This calls for mechanismsinvolving key players to identify and agree on various performance indicators to beused in monitoring and evaluation. The need to monitor and evaluate the effectivenessof the FFS approach in scaling up adoption of agricultural technologies cannot beover-emphasized. Unfortunately, tools/frameworks for doing so either lacking orMScstudentKARICenterUniversity Course/Degree Tentative title of research workGideonMwagiKisii Egerton M. Sc. Extension Factors influencing group effectiveness in FFSapproach for up-scaling agriculturaltechnologies: a case study of Kisii DistrictDavid K.BunyattaKitale Egerton M. Sc. Extension Effectiveness of FFS in validation anddissemination of soil managementtechnologies among small scale farmers inTrans-Nzoia District, Kenya

SallyRonoKitale Moi M.Phl. AgriculturalDevelopment and PolicyNot yet decidedMicahPowonKitaleEgertonM. Sc. Horticulture Evaluation of the effects of farm yard manure,phosphorus and potassium on the growth andtuber yields of Irish potato using the FFSapproachTable 2. MSc students undergoing training through the support of the FFS pilot project.286 FFS monitoring & evaluationlimited in scope. A methodology development workshop on PM&E of FFS wasorganized to develop such tools. The major objective of the workshop was to designand develop participatory tools/frameworks jointly for internal monitoring andevaluation of the effectiveness of FFS as an approach for upscaling technologyadoption.PM&E methodology workshop (Asiabaka et al 2002)The workshop, which was held on 17-24 March 2002 drew participants from KARI(scientists) and the Ministry of Agriculture and Rural Development (extensionists),the FAO office in Kenya, and the Coast Development Authority. The workshop wasfacilitated by Prof. C.C. Asiabaka, a professor of Economics and Extension at the

Federal University of Technology, Owerri, Nigeria. The workshop covered topicssuch as introduction of the basic concepts and principles of participation, activitiesthat encourage participation, meaning of participatory monitoring and evaluation,differences between conventional monitoring and evaluation and participatorymonitoring and evaluation. The concept of measurements and indicators,methodologies/techniques/tools for PME data collection, analysis, reporting skills,and PME data use. The concepts were discussed in plenary sessions andmisconceptions/misunderstandings were cleared during the question and answersessions. The participants were then divided into several groups for brainstormingsessions aimed at identifying the PME measurements/outcomes and indicators. Themeasurements and indicators were then synthesized in a plenary session. In the nextstage, methodologies, techniques, and tools for participatory monitoring andevaluation of FFS were developed using the harmonized measurements andindicators.Definition of PM&EParticipation was defined as the process by which people become involved in theirown development. It can be described as the voluntary involvement of people inself-determined change. Participation includes joint planning, management andimplementation, sharing benefits, and monitoring and evaluation. PM&E requires

the involvement of people in deciding what areas to monitor, selecting the indicatorsfor monitoring and evaluation, designing data collection systems, collating andtabulating data, analyzing the results, and using PM&E information/data for theirown use. Therefore PM&E improves people’s efficiency and effectiveness, andincreases awareness and understanding of factors which affect their situation, therebyincreasing control over the development processKARI center Farmer field schoolsResearcher-led Farmer-led Extension-ledKitale 13 4 1Kisii 6 4Mtwapa 1 1Total 20 9 1Table 3. New FFS initiated in 2002.Farmer Field Schools: emerging issues & challenges 287The following section presents the harmonized measurements/outcomes,indicators, and tools/frameworks for PM&E. An attempt was made to match theharmonized outcomes, indicators , and tools to the different stages of the FFS process.The tools are presented in Appendices 1-12.Collection of baseline information. Baseline information gives the currentsituation of farming and farming systems, and is important for future assessment ofthe impact of the approaches/technologies. Participants brainstormed during theworkshop and identified the following key areas to be covered in a baseline study.Conventional methodologies can be used to collect information on identified areas.

Village immersion. In this activity, facilitators of the planned FFS enter into acommunity. They hold a series of meetings with the local opinion leaders and localadministrators in which they explain the objectives and goals of the anticipatedactivities. They explain the roles of the facilitators and discuss what is expected ofthe community. This is all done to solicit support in forming the FFS. The mainmeasurement/outcome of this activity is that the opinion leaders are sensitized onthe goals and objectives of forming the FFS, hence supporting the formation of theschools. Indicators that this outcome has been achieved include the following:• Number of schools formed• Number of times opinion leaders participated in the FFS activities• Number of times opinion leaders have invited FFS members to their meetings,e.g., chief’s Baraza• Number of times opinion leaders have scheduled their activities on FFS days• Number of times opinion leaders have been called upon to resolve conflicts inFFSAppendix 1 shows the tools for collecting information on these indicators.Groundworking. With the assistance of opinion leaders, facilitators convenean open meeting with community members. In the meeting, facilitators - with theassistance of opinion leaders - explain the objectives and goals of the anticipated

activities, clarify the roles of facilitators, and discuss expectations of the communityand facilitators (leveling of expectations). The site(s) for the school(s) is/are chosenand farmers willing to enroll in the school(s) are enlisted. Table 4 gives some outcomesTable 4. Outcomes and indicators of success of groundworking.Measurements (outcomes) IndicatorsFarmers sensitized onobjectives of forming FFSNumber of farmers that expressed willingness to enrol in FFSNumber of farmers that later on joined FFSNumber of farmer dropouts from FFSNumber of farmers whose expectations were met by FFSFarmers enrolled in FFSNumber of farmers enrolled in FFSFFS site selectedNumber of FFS schools formedNumber and names of selected sites288 FFS monitoring & evaluationand indicators of success expected in this stage. Appendix 2 gives the tools forcollecting information on these indicators.Day 1 of FFS. In day 1 of the school, the school leadership is chosen as well asthe norms and rules governing the school. The FFS concepts and objectives/goals arespelled out. The types of records kept by the school are also explained. Table 5 presentsoutcomes and indicators of results for day 1 of the FFS. Appendix 3 lists tools forcollecting information on the indicators.Setting up participatory technology demonstrations (PTDs). In this stage plots

were laid out and planted with options of the technology to be scaled up. A farmerpractice plot is included for comparison. Participation of farmers in planning, layingout, and planting the technological options including their participation in managingthe plots enhanced their ability to experiment and fostered farmer-to-farmercommunication by collecting data and interpreting the PTD results. The outcomeand indicators for this stage are technology-specific. Table 6 gives an example.Appendix 4 gives the tools for collecting information on indicators at this stage.Running the FFS: Monitoring PTDs using the agroecosystem analysis (AESA)approach. In setting up the AESA, participants look at the interface between a cropand its physical environment. Farmers interpret the performance of the crop inrelation to the physical environment. They collect data, process them and presentthem to the “class’’. Based on the results, they decide on their next course of action.Table 7 lists some of the expected outcomes and indicators of success of the AESA.Appendix 5 gives the tools that can be used to collect information on the indicators.Area IndicatorsEconomicProduction levels, income levels, ownership of assets, povertylevel, economic improvement, household food security,mechanizationSocioculturalGroup cohesion, gender participation, standard of living,

wealth, learningTechnologicalAdoption, facilitation skills, communication skills,sustainability, post harvest handling, condition of the produceInstitutionalCapacity building, networking (linkages), access to credit,marketingEnvironmentalConservation of resources, afforestation, pesticide usePoliticalLeadershipAccountabilityBank accounts, records kept, planning forumsFarmer Field Schools: emerging issues & challenges 289Table 5. Outcomes and indicators of success of day 1 in the FFS school.Measurements (outcomes) IndicatorsSchool register developed andusedDaily roll callOther uses for register laterPercentage attendance (% of those enrolled)Number of farmers fined for latenessNumber of farmers expelled for latenessNumber of farmers approved for graduationFFS concept, objectives andprocess understood by farmersNumber of farmers aware of objectives of FFSNumber of farmers who can explain FFS conceptsNumber of farmers who can explain the FFS processSchool leadership put in placeList of names of elected officialsDate of electionTenure in office of elected officialsHost teams (with name andslogan) formed

List of names and slogans of host teamsNumber of host teams formedFFS meeting day identifiedName of meeting day of FFSTime of meeting of FFSProcedure for sharing benefitsagreed uponFarmer knowledge of mode/method of sharing the benefits from FFSNorms and rules of schoolestablishedAvailability of list of norms and rulesTable 6. Example of outcome and indicators of the PTD.Measurements (outcomes) IndicatorsDemonstrations established Plot sizeDate(s) of input(s) acquisitionDate of plantingSeed and fertilizer application rate by plotType of feeds and amount usedNumber of livestock houses availableType of livestock houses availableNumber of records kept by typeMeasurements (outcomes) IndicatorsAESA chart prepared Availability of AESA chartsFarmers can collect data from thedemonstrationsNumber of farmers who can identify insect pests/ diseases, etc.Number of farmers who can assess extent of damage causedby pests/diseasesMeasurements made and recorded on AESA chart e.g., plantheight, weight, insect damaged leaves, etc.Farmers can process data from thedemonstrationsNumber of farmers who can process dataResults of processed data presented inplenary

Number of farmers who can present results and frequency ofplenary presentationsBased on results, comparisons ofdemonstration made by farmersNumber of farmers who can make comparisons among thedemonstrationsBased on results,decisions/recommendations made byfarmers on future activitiesNumber of times consistent decisions /recommendations aremade based on results and curriculumTable 7. Expected outcomes and indicators of success of an AESA exercise.290 FFS monitoring & evaluationRunning and facilitating the FFS. Running an FFS involves a weekly routinestarting with prayers, roll call, taking of the AESA and presentations, and finallydeciding on the next course of action by the host team. The facilitator presents thelesson of the day and/or the special topic. Table 8 gives some outcomes and indicatorsfor the facilitation of the FFS. Appendix 6 lists the tools for collecting information onFFS facilitation.Special topics covered in the FFS. Households have many objectives thatneed to be met. They could be productive, e.g., food production; or social e.g., diseasecontrol; or physical, e.g., water provision. These objectives, if not met, may adverselyaffect the performance of an FFS. On certain occasions, the FFS members may demandspecial topics to address the objectives. In most cases, this special topic is unrelated

to the lesson of the day for a particular FFS, but is nonetheless important. Table 9gives some outcomes and indicators for special topics, while Appendix 7 providestools for collecting of information on special topics.Field day hosted by the FFS. This is an open day for exchanging messages/information about technologies shown to the wider community to increase diffusionand possibly enhance adoption. Table 10 gives some outcomes and indicators forfield days hosted by the FFS. Appendix 8 gives tools for collecting of information onsuccess of field days.FFS exchange visits. Exchange visits are made to other FFS in similar ordifferent AEZs and socioeconomic settings, and other places of particular agriculturalinterest. The exchange visit is intended to broaden the visitors’ perspective on howother farmers manage their resources, given their circumstances to meet their farmingaspirations. During such visits other unintended benefits may occur through personalTable 8. Outcomes and indicators of the success of the facilitation of the FFS.Table 9. Outcomes and indicators for special topics.Measurements (outcomes) IndicatorsKnowledge of the lesson of theday enhancedContent of the lesson of the dayMethod of presentationLength of presentationUnderstanding of subject taughtenhancedNumber of farmers practicing the skills learned

Quality of facilitation enhanced Type of topic facilitatedMethod of presentationTimeliness of topic (appropriate for the time presented)Length of presentationFeedback mechanism (Testing knowledge of presentation by farmers)Measurements (outcomes) IndicatorsKnowledge of the lesson of theday enhancedContent of the lesson of the dayMethod of presentationLength of presentationUnderstanding of subjecttaught enhancedNumber of farmers practicing the skills learnedQuality of facilitation enhanced Type of topic facilitatedMethod of presentationTimeliness of topic (appropriate for the time presented)Length of presentationFeedback mechanism (Testing knowledge of presentation by farmers)Farmer Field Schools: emerging issues & challenges 291interactions and observations, such as conflict resolution among FFS members. Table11 gives some outcomes and indicators for exchange visits, while Appendix 9 liststools for collecting information on the success of exchange visits.Group cohesion and group dynamics. Group cohesion is critical to thesuccessful completion of any FFS. This is fostered by good leadership, facilitation,and social activities that bond the group together. Table 12 gives some outcomes andindicators for group cohesion and dynamics. Appendix 9 provides tools for collectinginformation on the same.Graduation of FFS. At graduation, farmers who have successfully gone

through the season-long FFS training and have met the group norms and conditionsfor graduation are given certificates. Some are able to facilitate new FFS with thesame PTDs. Table 13 gives some outcomes and indicators for graduation, whileAppendix 10 lists tools for collecting information.Table 12. Outcomes and indicators of group cohesion in FFS.Measurement (outcomes) IndicatorsGroup cohesion/dynamicsstrengthenedTypes of conflicts encounteredMethods of conflict resolutionFrequency of conflictsNumber of farmers dropping out from schoolNumber of poems, drama, songs, etc ., composedNumber of FFS-related messages in the folk media, etc.Number of income-generating activitiesTable 11. Outcomes and indicators for exchange visits.Measurements (outcomes) IndicatorsLinkages between schoolsestablishedNumber of visits madeNumber of FFS farmers who made visitsNumber of visitors received in FFSNature of FFS linkagesNumber of linkages establishedFFS farmers exposed to othertechnologies, skills, and farmingsystemsType of messages and information exchangedMethod of funding visits (whether group or farmer sponsored)Skills practiced as a result of exchange visitsFarmers’ exchange knowledge onleadership

Number of new approaches in resolving conflictsTable 10. Outcomes and indicators of field days.Measurements (outcomes) IndicatorsFFS technologies demonstrated Number of exhibitions presentedNumber of invited guestsNumber of participants in attendanceNumber of institutions participatingNumber of prizes awardedFFS farmers share knowledgelearned to the communityType of exhibitions presentedNumber and type of messages sharedRecord of speechesDocumentation done e.g. Photographs, video taped messages, etc.FFS members get feedback fromthe communityRecord of questions and answers292 FFS monitoring & evaluationPost-FFS evaluation: assessing FFS graduates one year after. Assessment aimsat establishing the value of FFS in diffusing knowledge/technologies, how acquiredknowledge contributes to the welfare of farmers, and how FFS enhances farmers’experimentation skills.ConclusionThe PM&E methodology tools that were developed are being used in the field byworkshop participants to test their relevance, efficiency, and usefulness. The workshopwas an initial process to develop PM&E tools, which will not be complete until thetools are tested in the field and fine-tuned using field experiences. A workshop is

planned to review experiences and make modifications. However, a few conclusionscan be derived from the process so far:Measurements (outcomes) IndicatorsRecap of what was learned duringthe season-long schoolNumber of poems, songs, and dances with FFS messagesChart displaying promising technologies and their performanceCertificates and prizes inrecognition of successfulparticipation in school awardedNumber of farmers that participated (in attendance)Number of farmers that graduatedNumber of certificates awardedNumber of prizes awardedAction plan for way forwardpresentedRecord of action plan for way forwardTable 13. Outcomes and indicators of the FFS graduation.Measurement IndicatorsFFS technologiesdiffusedNumber of non-FFS farmers practising the technologyNumber of farmer-led FFS formedNumber of other groups (e.g., CBOs) formedKnowledge learnedretained (technology andspecial topic specific)Number of farmers who remember the basics of lessons on technologiestaughtNumber of farmers who remember the basics of lessons on special topicstaughtFFS technologiesadoptedType of technology adopted

Number of FFS members practicing FFS technologiesNumber of FFS members practicing special topicsNumber of non-FFS members practicing FFS technologiesChanges in levels ofproductionProduction before FFS (kg, L, etc.)Production after FFSChanges in levels ofincomeIncome level before FFSIncome level after FFSChanges in food securitystatusMonths of food deficit before FFSMonths of food deficit after FFSStandard of living of thegraduates improvedNumber of graduates with access to good drinking waterNumber of graduates with access to better quality foodNumber of graduates with access to good healthNumber of graduates with access to good housingNumber of graduates with access to better clothingNumber of graduates with access to basic educationGraduates’ ability toexperiment enhancedNumber of farmers comparing different practices/interventions in their farmsTypes of practices/interventions in those farmsTable 14. Outcomes and indicators of success of FFS graduates.Farmer Field Schools: emerging issues & challenges 2931) The participants understood and appreciated the difference between PM&E of aprocess as opposed to monitoring and evaluating impacts of a project or atechnology.

2) The workshop helped bring out the key steps in the FFS approach and made itpossible to identify those that could be combined in PM&E exercises.3) The multidisciplinary team of scientists appreciated their role in PM&E; beforethe workshop, many thought that PM&E tools were used by socioeconomistsonly.AcknowledgmentsWe acknowledge the financial support from the Rockefeller Foundation. We are indeedgrateful to Dr. Ruben Puentes of RF New York and Mexico, and Dr. John Lynam of RFNairobi for the technical support they have given the pilot project from its inception.ReferencesAbate, A.N. 2000. Farmer field schools as a participatory research/extension methodology.Paper presented in the 2nd Scientific conference of the Soil Management andLegume Research Network Projects. 26-30th June 2000, Mombasa, Kenya.Asiabaka, C.C., J.G. Mureithi, F.M. Murithi, J.W. Wamuongo. 2002. Report of participatorymonitoring and evaluation methodology workshop of the farmer field schoolapproach for scaling up the adoption of INM technologies and information. KenyaAgricultural Research Institute. p. 66.Kenya Agricultural Research Institute (KARI). 2000. Improved livelihood throughappropriate agricultural research and technology. Kenya Agricultural ResearchInstitute Strategic Plan 2000-2010. p. 28.

KARI. 1998. Working paper on institutionalization of a harmonized planning, monitoringand evaluation system in KARI. KARI Working Paper Series. Working Paper No. 1.p. 11.Khisa G.S. 2000. Output of the intensive training of trainers course on farmer field schools.Mabanga Farmers Training Center, Bungoma District, February 13-23, 2000.Mweri B.M. and G.S. Khisa. 2001. Report of the training of trainers course on farmer fieldschool methodology for KARI’s soil management and legume research networkproject held at Utafiti Hall, Egerton University, Kenya, March 12-17, 2001. KenyaAgricultural Research Institute. p. 71.Miagostovich M., J. Anderson and S. Sukwong. 1999. Farmer field school in integrated cropmanagement. Rural learning networks. Regional Community Forestry TrainingCenter (RECOFTC). p. 10.Muchena F.N. and T.G. Gicheru. 2001. Institutional and policy frameworks on soil fertilityand productivity. Paper presented during the Consultative Workshop on SoilFertility and Land Productivity Initiative for Kenya. 30-31st July 2001.Pontius J., R. Dilts and A. Bartlett, editors. 2000. From farmer field schools to communityIPM. Ten years of IPM in Asia. The FAO Program for Community IPM in Asia, P.O.Box 1380, Jarkarta 12013, Indonesia. p. 141.294 FFS monitoring & evaluationAPPENDICES: PARTICIPATORY MONITORING AND EVALUATIONTOOLS FOR FARMER FIELD SCHOOLS PROCESS

Appendix 1. Village immersionChecklist1. What are the objectives/goals of the FFS set by the facilitators?2. What are your expectations concerning the FFS after the meeting(s) with thefacilitators?3. What roles will opinion leaders play in the FFS?4. What roles may opinion leaders not play in FFS?5. What roles will farmers play in the FFS?6. What roles may farmers not play in FFS?Questionnaire(Fill in the blanks appropriately) – later in the life of the school1. How many times in the life of the school have opinion leaders participated inthe FFS activities?Name/title of FFS activity participated in Frequency ofopinion leader participation............................................. .......................................... ............................................................... .......................................... ..................2. How many times have FFS members been invited to meetings organized bylocal opinion leaders (e.g., chief’s baraza, local community/locational/divisionaldevelopment meetings, etc.)?Title or name of member(s) Type of meeting attended Frequency ordate(s)attended............................................. .......................................... ............................................................... .......................................... ..................3. Frequency of scheduling opinion leader meetings on FFS daysTitle/name of Type of activity scheduled Date(s) attendedopinion leader on FFS day........................................ ........................................... .............................................................. ........................................... ......................

4. Frequency of opinion leaders having been called upon to resolve conflictsamong FFS membersTitle/name of Nature/type of conflict How resolved Date(s) conflictopinion leader resolved............................ ...................................... ........................ ................................................ ...................................... ........................ ....................Farmer Field Schools: emerging issues & challenges 295Appendix 2. Ground workingChecklist1. Why was your FFS formed?2. How was the name of your school and its site chosen?3. What roles will farmers play in the FFS?4. What roles may farmers not play in FFS?5. What were your expectations concerning the FFS after the meeting(s) withthe facilitators/opinion leaders?Questionnaire1. How many schools were formed as a result of the ground-working meeting(s)?.......................2. How many farmers expressed willingness to enrol as members in therespective FFS (as enlisted in the ground working meeting)? ............................Name of school Number enrolled.................................................................................... ...................................................................................................... ....................................................................................................... ..................3. How many farmers (not in the ground-working meeting) later enrolled in theFFS through the influence of others?.................4. How many of the farmers initially enrolled in FF have dropped out? .................5. What are the main reasons for dropping out?

.....................................................................................................................

..............(a) Were your expectations of FFS met? Yes or No (Circle as appropriate)(b) If No, which ones were not met?................................................................................................................................296 FFS monitoring & evaluationAppendix 3. Day 1 in schoolChecklist1. School register opened2. What are the main concepts and objectives of FFS?3. Meaning of FFS as a process4. Roles of FFS leaders by title5. Date of election6. Tenure in office of elected officials7. What is a host team?8. What is (are) the role(s) of a host team?9. Day and time of FFS meetings10. Norms and rules of the school11. Procedure of sharing benefits/losses of FFSQuestionnaire (Fill in the blanks or answer questions appropriately)1. How many of the enrolled farmers attended the first day of school based onthe school register?............2. How many farmers were aware of the objectives of FFS?..........3. Which FFS concepts were you exposed to?......................................................................................................................4. What does the FFS process involve?.........................................................................................................................................................................................................................................................5. Procedure of sharing of benefits/losses of FFS activities

…………………………………………….....................................................................6. How is the FFS run?7. What is the gender composition of your FFS group?Male………... Female …………… Youth .……..……8. Leadership position by genderLeadership position Number by genderMale Female Youth............................................. ................... ................. ............................................................... ................... ................. ..................ChairpersonSecretaryTreasurerOther (specify)List of names and slogans of the host teams…………………………………………………………….....................................................Farmer Field Schools: emerging issues & challenges 297Appendix 4. Participatory technology demonstrations (PTD)Checklist1. Plot size of participatory technology demonstrations2. Method(s) of acquisition of input(s) for the PTD3. Type of seed planted4. Type of feed used5. Method of planting used6. Method of weeding used7. Type of livestock feeding systemQuestionnaire (Fill in the blanks or answer questions appropriately)1. When were the inputs for the PTDs acquired?………………………......................2. When was the PTD planted?………………………………........................................3. What seed rate was used?……………………………................................................4. State type and number of livestock houses available

…………………..........................................................................................................Type of livestock house Number................................................................................................. ................................................................................................................... ................................................................................................................... ..................

Journal of Agricultural Extension Vol. 14 (1), June 2010 53 Farmer Field School (FFS) and Junior Farmer Field and Life School (JFFLS) as challenges to agricultural extension development and practice in Nigeria E. N Ajani* and E.A. Onwubuya** Department of Agricultural Extension, Faculty of Agriculture, E-mails: vnglajani@yahoo.com* and lizzybuya@yahoo.com** Mobile: 07037898918* and 08050338606** Abstract This paper discusses Farmer Field School (FFS) and Junior Farmer Field and Life School (JFFLS) as challenges to agricultural extension development and practice in Nigeria. FFS and JFFLS are participatory extension approaches which emphasize participation of local people and their communities working in groups and building upon the traditional or indigenous knowledge that they have acquired. Discovery learning is emphasized on FFS and JFFLS approaches whereby participants learn by doing as well as discovering new ideas by themselves. The paper suggests the need for promotion of these approaches by national extension policy and donor agencies to ensure sustainability. It notes that these approaches which encourages qualitative rather than often used quantitative researches will reduce unrealistic and crooked formal research data and also challenge other methods of extension delivery for better discovery learning. It concludes that developing an appropriate framework for analysis and evaluation of these approaches will help to

more accurately measure their effectiveness and impact on the lives of the participants and the society at large. Key words: Farmer Field School, Junior Farmer Field and Life School, agricultural extension, participatory approaches and discovery learning. INTRODUCTION Agricultural extension can be defined as a conscious provision of information and communication support to rural users of renewable natural resources. It involves offering advice, helping farmers to analyze problems and identify opportunities, sharing information, supporting group formation and facilitating collective action. Extension services are delivered not only by extension agencies but also by farmers, scientists, commercial companies, mass media organizations, among others (Garforth and Lawrence, 1997). In the last twenty years, many efforts have been made in trying to change research and development in agriculture to better involve farmers, to the extent that it has been widely accepted (Low External Input and Sustainable Agriculture (LEISA, 2006). However, most formal researches related to agriculture in developing countries are still carried out at large research institutions, and the extent to which farmers are involved in setting the agenda, taking part in experiments, monitoring, evaluating or using the results varies a lot, but is generally very limited. LEISA (2006) further stated that the vast range of participatory approaches promoted in the last twenty years have aimed in general at building technical knowledge in order to improve livelihoods ( examples, FFS and JFFLS). The participatory process involves narrowing the gap between research organizations and farmers‘ realities by ensuring direct farmer involvement at different stages of the research process. Journal of Agricultural Extension Vol. 14 (1), June 2010 54

According to Hellin, Bellon and Badstue (2006), the most effective way for participatory research processes to benefit a greater proportion of farmers is by close coordination and collaboration with organizations that are better placed to link farmers and researchers due to their relatively long-term contact with farmers. These organizations include: extension services, farmer organizations and non-governmental organizations (NGOs). As these organizations focus on development, they are better placed to ensure that research results reach greater number of farmers and that in the process more farmers are empowered. A number of agricultural extension approaches have been used in Nigeria. The major differences in their characteristics are based on how the extension services systems are structured and organized, the relationship and linkage mechanisms amongst the extension service actors, particularly farmers, extension agents and researchers, the range of agricultural services contained in the technical package, the types of extension methods that are used and the way the extension services are financed (Ministry of Agriculture, 2008). This paper discusses the concept of Farmer Field School (FFS) and Junior Farmer Field and Life School (JFFLS) and their challenges to agricultural extension development and practice in Nigeria. Farmer Field School (FFS) Approach Farmer Field Schools (FFS) are schools without walls where groups of farmers meet periodically with facilitators during the crop or animal cycle (Davis and Place, 2003). According to FAO (2008), FFS is described as a platform and schools without walls for improving decision-making capacity of farming communities and stimulating local innovation for sustainable agriculture. It is a school without walls that teaches basic agro-ecology and management skills that make farmers experts in their own farms. It is a participatory method of technology development and dissemination whereby farmers are given the opportunity to make a choice in the methods of production through discovery based approach based on adult learning principles and experiential learning (FAO, 2001). It reflects the four elements of experiential learning cycle, namely: concrete experience, observation and reflection, generalization and abstract conceptualization, and active

experimentation. These emphasize the importance of learning in practical field settings instead of through didactic modes in classroom settings (Farrington, 2002). FAO (2008) reported that the specific objectives of FFSs are to: empower farmers with knowledge and skills to make them experts in their own fields; sharpen the farmers‘ ability to make critical and informed decisions that render their farming profitable and sustainable; sensitize farmers in new ways of thinking and solving problems; and help farmers learn how to organize themselves and their communities.

The approach requires a group of 20 – 30 farmers to meet regularly on a given farm where they make field observations, relate their observations to the ecosystem and apply their previous experience and any new information to make a crop or livestock management decision with the guidance of a facilitator. The observations are carried out throughout the enterprise cycle (Farrington, 2002). Key non-formal education methods in the Farmer Field School learning include: sharing, case study, role play (dramatized sessions), problem solving exercises, panel Journal of Agricultural Extension Vol. 14 (1), June 2010 55

discussions, group dynamics, small group and large group discussion, brainstorming and simulation game. These key non- formal education methods encourage and contribute to the qualitative nature of this approach thus challenging the usual and often used quantitative methods involved in most formal researches. It also challenges these formal methods by reducing unrealistic crooked data in formal methods as experiential learning is involved through adult learning principles thereby bringing about effectiveness and efficiency in practices. This is achieved as the farmers are empowered with better and more knowledge and skills through their experiences which make them experts in their own fields. The farmers‘ abilities are also sharpened enabling them to make critical, informed decisions that make their farm production efficient by being profitable and sustainable. The farmers are also sensitised in new ways of thinking and solving problems. The approach challenges farmers to learn how to organize themselves and their communities. Hein and Muhammad (2007) reported that the Farmer Field School (FFS) approach was developed in the late 1980s in Indonesia. The first FFS networks emerged in Western Kenya in the year 2000 as a result of exchange visits and communication between farmers, facilitators and trainers of different Farmer Field Schools. Similar networks have subsequently emerged elsewhere in Kenya, Uganda and Tanzania. These FFS networks were formed by farmers who had graduated from a FFS. The main reason for their formation was that the graduates wanted to continue the dynamics generated by the FFS process: to build local institutions to ensure the continuation of farmer-led FFS, and benefit from becoming a larger voice in expressing their demands (Arnoud, James, Habakkuk and Godrick, 2007). They further reported that the FFS approach was first introduced in East Africa in 1995 through a project of the Food and Agriculture Organization (FAO) in Western Kenya. Since then, several projects have been successfully implemented in the region using various different entry points, including issues such as integrated production and pest management, land and water management, self sustainability for refugee communities, integrated crop

management of sweet potato, promotion of farmer innovations, livestock and control of banana bacterial wilt. To date, the FFS networks in East Africa support about 2000 FFSs with close to 50,000 direct beneficiaries. The main reason for the success of FFS in the region has been the involvement of farmers in identifying their problems, in selecting, testing and evaluating possible solutions. This paper is advocating that this approach should challenge (be used as a challenge) in the Nigerian extension service delivery and system to bring about such networks to generate dynamics and processes to build up local institutions and benefits (or that will benefit farmers) sufficiently. The approach is currently one of the fore-front extension-related activities sponsored by FAO, and the principles and methodology of the approach are being replicated by other technical services such as irrigation and water use and forestry. Irrigation and Water Use technical unit has already successfully piloted a FFS project in Zambia (FAO, 2008). FAO‘s Forestry Policy and Institutions branch have also adopted the FFS approach, but have changed the name to suit its community forestry development purposes: Farmers‘ Forest Management Schools (FFMS). The Farmer Field School approach is relatively new to West Africa, and there are few examples of its application to tree crops and perennial crops. Sustainable Tree Crop Programme (STCP) has pioneered FFS on cocoa integrated crop and pest management in Cote d‘Ivoire, Ghana, Nigeria, and Cameroun since 2003. Although it is based on the experience built with cocoa FFSs, many of the principles and Journal of Agricultural Extension Vol. 14 (1), June 2010 56

recommendations can be applied to FFSs on other tree crops (Soniia, 2006). FAO (2008) also reported that other African countries implementing this approach are Zimbabwe, Malawi, Ethiopia, Gambia, Egypt, Lesotho, Swaziland and Mozambique. Hence the approach is being advocated for Nigeria as a challenge to our usual extension service delivery methods. According to Agro Care (2009), feedback from farmers and operators of the Farmer Field School (FFS) from Edo state, Nigeria have shown that this agricultural extension approach is capable of improving farm yields tremendously, particularly in the cocoa sub-sector where it is presently being put into use and in which many more farmers and states are adopting it. The programme, jointly funded by the federal government, cocoa producing states and the International Institute for Tropical Agriculture (IITA)'s Sustainable Tree Crop Programme (STCP), is a school without border and is held fortnightly in the field in cocoa producing communities where FFS is located. FFS was adopted by the Sustainable Cocoa Development Committee (SCDC) in 2005 as an improved methodology for training cocoa farmers in Nigeria. The approach can be tried and used to challenge other areas of agriculture such as yam, rice and cassava producing areas as in the case of these cocoa producing areas. The overall objective of the project was to strengthen the capacity of the extension services of participating states to use the FFS extension approach to develop, implement and manage cocoa integrated crops and pests management. Following the adoption, the Sustainable Tree Crop Programme (STCP) of the IITA was commissioned to develop and implement the FFS capacity building project for the cocoa producing states. A total of 14 master trainers, 27 supervisors and 156 facilitators have been trained. Of these numbers, 12 master trainers, 24 supervisors and 136 facilitators from eight states have had at least a year experience in running FFS in their states. Besides, efforts are being made to constitute the Edo State Cocoa Development Committee, which would immediately be followed by the inauguration of the Local Governments Cocoa Development Committees, all aimed at enhancing the nation's cocoa production capacity and repositioning the country in the league of cocoa producing

nations (Agro Care, 2009). Other states of the federation should attempt to take up this challenge and replicate it for agricultural production and practices that suits their region or introduce other. Olukayode (2009) reported that Edo state presently has 22 Farmer Field Schools, second to Osun state which has 30. The first cycle of the state's Farmer Field School programme commenced in September 2007 and ended in October 2008, with the graduation of 500 cocoa farmers. The second cycle was officially flagged-off by Edo state deputy governor on Monday, 18th May, 2009 at Aihuobabekun/Obarenren Farmer Field School in Ovia North-East local government area of the state, with over 500 cocoa-farmer participants attending. FFS as an informal institution is based on the assumption that farming communities have a vast body of knowledge, skills and experience on which they can build their future. The local farmer‘s knowledge and insights are based on their vast experience, rooted in their own local context (Raklin and Ajay, 2007). In this case, existing knowledge, values, cultures and practices are the key knowledge resources. According to LEISA (2001), in field schools, farmers learn to conduct experiments independently, create learning materials on their own, and manage field laboratory and plan for special sessions such as Integrated Pest Management (IPM) field days or IPM popular theatre. Farmers do not master a specific set of contents Journal of Agricultural Extension Vol. 14 (1), June 2010 57

or messages, rather they master a process of learning that can be applied continuously to a dynamic situation. Field school intentionally included processes and methods that would provide such interaction. Participants work together in small groups to collect data from the field, generate analysis through discussion, present results, conduct experiments and make group decisions for field management. For many farmers unaccustomed to even speak in front of groups, this confidence building and process mastery is the most important outcome of their field school experience (Russ, 2007). This approach will challenge the collection of fake data common in quantitative research as small groups are involved in qualitative field data collection for analysis, discussions and effective group decisions. The operation of the extension delivery approach is that developmental organizations partner with extension personnel to identify or form farmer groups based on particular topics. For instance, there are groups based on passion fruit, poultry, beekeeping and vegetable production. Farmer Field Schools hold field days for other FFS groups and neighboring farmers. This is a chance for each participant to teach others what they have learnt. At the end of the FFS cycle, certain farmers are chosen by the group to be farmer facilitators. They can then lead their own Farmer Field School the next season (Davis and Place, 2003). Madukwe (2006) noted that the FFS have transformed farmers from recipients of information to generators and manipulators of local data. One important issue in FFS is that of sustainability without outside funding. It is a participatory approach, which facilitates farmer‘s demand for knowledge and offers opportunity for the end users to choose, test and adapt technologies according to their needs. Through participation in FFS, farmers develop skills that allow them to continually analyse their own situation and adapt to changing circumstances (Madukwe, 2006). Junior Farmer Field and Life School (JFFLS) Approach HIV and AIDS have a tremendous impact on rural African societies: families and social networks of solidarity are disrupted, children are orphaned, the rural livelihoods and the mechanisms of knowledge transmission are grievously affected (Djeddah, 2005). She further

reported that the growing number of orphans is of direct concern to all sectors. Rural children orphaned by AIDS are more likely than other orphans to be at risk from malnutrition, disease, abuse and sexual exploitation. Often, orphaned children are growing up without the necessary knowledge and skills for their future livelihoods. From the farm-household perspective, food security is affected: both the quantity and quality of the food diminishes and orphans can often go hungry or are malnourished. From an agricultural perspective, these young boys and girls need to have the necessary agricultural and livelihood skills, the education and the food required to grow into healthy adults and become agents of their own change. The JFFLS objective is to improve their livelihoods and provide them opportunities for long-term food security, while minimising the vulnerability to destitution and extreme coping strategies (LEISA, 2007). Junior Farmer Field and Life Schools (JFFLSs) were developed by FAO, together with the World Food Programme (WFP), other UN agencies, national governments, NGOs and local institutions, as a way to counter the impact of HIV and AIDS on orphans and vulnerable children, to reduce their vulnerability and to improve their livelihoods and long-term food security. FAO has established JFFLSs in several African countries since 2004, with the objective of mitigating the impact of Journal of Agricultural Extension Vol. 14 (1), June 2010 58

AIDS epidemics on the rural populations and specifically empowering orphans, vulnerable children and youths by improving their livelihoods and their agricultural and life skills (FAO, 2007). Djeddah, Mavanga and Hendrickx (2005), reported that the JFFLSs are an adaptation of two successful participatory learning methodologies to the needs of rural youths: During an agricultural season, a group of 30 children/youths (boys and girls between 12 and 17 years) follow the life cycle of crops and make links and inferences regarding their own lives and problems. They meet once, twice or thrice a week in the field, and learn by doing and exploring. An inter-disciplinary team of facilitators accompanies the children to the field: a school teacher, an agriculturist / extension worker and a social animator, proficient in drama, dance and creative activities. Community volunteers always work in close collaboration with the facilitators. The curriculum of the JFFLS is built on four main pillars, namely: school site and the field activities where children learn by doing; special agricultural topics; life skills and cultural activities (theatre, dance, singing etc).

The learning activities in the school site follow the local agricultural cycle, depending on the choices of the children and people of the community who own the project. The activities range from laying out the site, preparing the land, seeding or planting, weeding, thinning, constructing suitable storage units, storing harvests, making compost, managing livestock, establishing a nursery and irrigating vegetables. The JFFLS curriculum integrates and links the agricultural learning with life skills according to monthly themes, with a holistic perspective, which is its trademark and peculiarity. Art, theatre, song and traditional dance play a central role in encouraging self-expression and integration with peers; they also help to build trust, explore risks, solve problems and develop more gender-equal attitudes (Dimitra Newsletter, 2007). The JFFLSs were developed as a pilot initiative in Mozambique in 2003. Since then, they are refined, scaled up and enthusiastically adopted by

different stakeholders in nine African countries, namely: Kenya, Malawi, Namibia, Sudan, Swaziland, Tanzania, Uganda, Zambia and Zimbabwe. The JFFLSs are now embedded in the formal education system in most cases, providing new inputs to this sector in terms of participatory learning and good agricultural and life practices. When possible, the JFFLSs are also co-coordinated with the adult FFS network (Djeddah, 2005).This paper advocates that Nigeria joins these African countries in this regard using it as a challenge to stimulate our own version that could be called youth for Agriculture(YFA) Programme which can be embedded in our school programme for youths in school to improve agricultural production and practices in Nigeria. This will also enable the youths to be self reliant and improve their livelihood thus reducing their vulnerability. This approach according to Djeddah ( 2005) has been expanded to the Kakuma refugee camp in Kenya since 2006, with a particular focus on orphans and vulnerable children resulting from civil violence and displacement, with support provided by the United Nations System-wide Work Programme on scaling-up HIV/AIDS services for populations of humanitarian concern. Spore (2008) also reported that in Mozambique, the education and training on Junior Farmer Field and Life Schools (JFFLS) programme has trained 7,000 AIDS orphans in an effort to stop them from leaving their communities. These young people have not just acquired Journal of Agricultural Extension Vol. 14 (1), June 2010 59

farming skills and knowledge; they have also developed the capacity to understand their problems and ensure that their rights are respected. Food and Agricultural Organization of the United Nations (FAO) identified the Junior Farmer Field and Life School (JFFLS) concept as a useful way to assist rural youth in HIV/AIDS programmes. The JFFLS programme provided technical, business and life skills, while at the same time providing some constructive activities to get junior farmers started in income generating enterprises to help support their families and themselves into the future (LEISA, 2007). This can be replicated in Nigeria for our myriads/ vast youths especially unemployed school leavers so as to contribute to national development. Example, the Nigerian government through extension system can consolidate this approach (JFFLS) by empowering the youths through acquisition of agricultural skills that will make them experts in their own fields. Viable strategies of sustainability can be devised by developing alliances with government, Non- Governmental Organizations and extension agencies to scale up the JFFLS. Such strategies should/ may include developing appropriate framework for evaluating the approach. There should be proper/ efficient maintenance of its technical qualities and core non- negotiable elements such as unique synergy between agricultural skills, life skills and the participatory field experience by the extension service. JFFLS have been labelled as one of the FAO‘s ―Best practices‖. The key challenges are: consolidation of the approach; devising viable strategies of sustainability by developing alliances with governments, NGOs and United Nations partners to scale-up the JFFLS and maintaining its technical quality and core non-negotiable elements, namely, unique synergy between agricultural skills, life-skills and the participatory field experience (FAO, 2005).

Conclusion and Recommendations The approaches challenges agricultural extension development and practice in Nigeria by encouraging qualitative extension delivery, practice and research through encouraging realistic methods in them.

This paper advocates that the approaches be used to challenge our extension delivery system to bring about networks to generate dynamics and processes which could be used to spring up local institutions and benefits for our teeming unemployed Nigerians, young and old. Effective participation of farmers in Farmer Field Schools (FFS) will enhance development of appropriate skills in farming thus necessitating formation of groups that facilitate effective dissemination of agricultural information within a social system. Vulnerable children and orphans who participate in Junior Farmer Field and Life Schools acquire agricultural skills that empower them and also improve their livelihoods. In order to support sustainable agriculture, extension approaches should use extension resources to support the development of independent client organizations, work increasingly to influence and facilitate planning decisions and action at group and community levels; and incorporate bottom-up and interactive approaches for extension planning and technology development. The national extension policy and donor agencies should promote changes in extension approaches, which will enhance sustainability rather than merely increase efficiency of contact with clients and the relevance of top-down technology development and information delivery. Journal of Agricultural Extension Vol. 14 (1), June 2010 60

References Agro Care (2009). Farmers' Field School: An Agricultural Extension Model. Agro Care Newsletter, 1. Arnoud, R. B, James, R.O, Habakkuk, K and Godrick S.K (2007). Building Farmer Field Schools networks in East Africa. LEISA Magazine, vol.23 (1): 18. Davis, K and Place, N (2003).Current Concepts and Approaches in Agricultural Extension in Kenya. Proceedings of the 19th Annual Conference of AIAEE. Raleigh, North Carolina, USA,745-756. Dimitra Newsletter (2007). Junior Farmer Field and Life Schools: A response to counter the impact of HIV and AIDS on orphans and vulnerable children in Southern and Eastern Africa. No. 13 (15). Djeddah, C (2005). Junior Farmer Field and Life School, empowering orphans and vulnerable children living in a world with HIV/ AIDS: Concept paper. FAO/WFP Djeddah, C, Mavanga, R and Hendrickx, L (2005).Junior Farmer Field and Life Schools: Experience from Mozambique. In Gillespie, S (eds). AIDS, poverty and hunger: Challenges and responses, IFPRI. Farrington, J (2002). Recent and Future Challenges in Agricultural Extension, Overseas Development Institute (ODI), London, LEISA Magazine, vol. 4 (2): 8. Food and Agriculture Organization (2001). Farmer innovation and new technology options for food production, income generation and combating desertification (99/2000). Progress report- 2001. Nairobi, Kenya. Food and Agriculture Organization of the United Nations. Food and Agriculture Organization (2005). Harvesting for life, movie, director: Boudicca Downes. Food and Agricultural Organization (2007). Getting started! Running a Junior Farmer Field and Life School, FAO/WFP. www.fao.org. Food and Agriculture Organization (2008). FAO‘s current programmes for Agricultural and Rural Extension Worldwide. FAO corporate document Repository, 1.

Garforth, C and Lawrence, A (1997). Supporting sustainable agriculture through extension in Asia. Natural Resource Perspectives, No 21. London: Overseas Development Institute (ODI), London Hein, B and Muhammad, A.I (2007). Changing the strategies of Farmer Field Schools in Bangladesh. LEISA Magazine, vol. 23 (4): 21. Hellin, J, Bellon, M and Badstue, L (2006). Bridging the gaps between researchers‘ and Farmers‘ realities. Impact, Targeting and Assessment Unit, International Maize and Wheat Improvement Center (CIMMYT), China. LEISA Magazine, vol. 22 (3): 6. Low External Input and Sustainable Agriculture (2001). Lessons in scaling up. LEISA Magazine, vol. 1(3): 18. Low External Input and Sustainable Agriculture (2006). Building knowledge, vol. 22 (3): 4 – 8 Low External Input and Sustainable Agriculture (2007). Junior Farmer Field Schools in Zimbabwe. LEISA Magazine,vol.23 (3): 9. Journal of Agricultural Extension Vol. 14 (1), June 2010 61

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M.C. MadukweE.C. OkoliS.O. EzeATPS Working Paper Series No. 35Analysis and Comparison of the AgriculturalDevelopment Programme and UniversityAgricultural Technology Transfer Systems inNigeriaChapter One:Introduction 1Chapter Two:Literature review 4Chapter Three:Methodology 8Chapter Four:

Results and discussion 13Chapter Five:Conclusion and policy issues 36References 40Table of ContentsList of TablesTable 1 Differences in technology generation practices between the ADP and university 25Table 2 Differences in technology transfer practices between the ADP and university 28Table 3 Socio-economic indices of agro-technology staff in the ADP and university system 31Table 4 Socio-economic indices of farmers under the agro-technology transfer systems ofADP and university 32Table 5 Farmers’ level of use of agricultural technology packages 33Table 6 Farmers’ perception of contact methods used by the ADP and university 34List of FiguresFigure 1 Conceptual framework for a comparative analysis of ADP and university technologytransfer system 9Figure 2 Organogram of Isoya Rural Development Project of Obafemi Awolowo University 16Figure 3 Administrative structure of agricultural media resources and extension centre of theUniversity of Agriculture, Abeokuta 18Figure 4 Administrative structure of the cooperative extension center of the University ofAgriculture, Makurdi 20Figure 5 Organogram of ADP agro-technology transfer system 22Figure 6 A proposed linkage structure for university and ADP in agro-technology transfer inNigeria 37

Figure 7 Proposed merge structure for university and ADP in agro-technology transfer inNigeria 39List of Tables and FiguresNigerian agricultural technology transfer policy since political independence emphasized transfer oftechnical information to farmers using various agro-technology transfer systems. Currently, theAgricultural Development Programme (ADP) and University are the prominent government fundedagro-technology transfer systems in Nigeria. This study comparatively analysed technology generation,transfer and utilization sub-systems of the ADP and university in Nigeria. The study covered three outof five agro-ecological zones in Nigeria, namely: Southwest, Central and Northwest. Four states, namely:Benue, Kaduna, Ogun and Osun, were selected on the basis of geographical spread and the presenceof universities with agro-technology transfer programmes. The staff of the ADPs and universities in theselected states and farmers served by the two agencies, constituted the research population. On thewhole, 524 randomly selected respondents comprising from the ADPs and 160 from the universitiesmade up the sample size for the study. One structured questionnaire for management staff and anotherfor field extension workers; and an interview schedule for farmers, were utilized for data collection.Percentages, mean scores and t-test were the statistical tools adopted in analysing the data.The findings showed that the ADP had larger staff and wider technology transfer coverage, comparedwith the university. The organizational structure of the university had at most two supervisory steps,

compared with the ADP, which had four supervisory steps. The extension staff of the ADP had bettertenets of field agro-technology transfer services compared to the field extension staff of the universitywith limited field exposure and orientation. The technology transfer staff of the University had betterconditions of service and were more committed towards the farmers compared with the ADP, whichlacked appropriate staff motivation. ADP had high rate of staff turnover compared with the University,which currently has high selectivity in staff recruitment. University organized agro-technology generationthrough research efforts in their faculties of agriculture compared with ADP which carried out limitedtechnology generation activities, mostly through on-farm research (OFR) and on-farm adaptive research(OFAR) trials. ADP organized constant and decentralized staff training for field extension workers withpoor training facilities, and provided inadequate training incentives to staff, compared to the universities,which provided competitive training incentives to extension workers. The ADP provided information onmore agro-technologies and had higher socio-economic impacts on participating farmers, comparedwith the university. The study recommends restructuring of the ADP and university agro-technologytransfer systems, taking into consideration their areas of comparative strengths and weakness. Thelocation of agro-technology services within the university system is strongly recommended of thegovernment contributing funds at different levels.AbstractPublished by the African Technology Policy Studies Network, P.O. Box 10081, 00100 General PostOffice, Nairobi, Kenya

© 2002 African Technology Policy Studies Network (ATPS)ISBN: 9966-916-42-3rinted by Newtec ConceptsP.O. Box 00800, Westlands14180 Nairobi, KenyaTel: 4449849, Fax: 4450399newtec@bidii.comABU Ahmadu Bello UniversityADP Agricultural Development ProgrammeADPEC Agricultural Development Project Executive CouncilAMREC Agricultural Media Resources and Extension CentreAMRECMAC Agricultural Media Resources and Extension Centre Management CommitteeAPMEU Agricultural Project Monitoring and Evaluation UnitARMTI Agricultural and Rural Management Training InstituteBESs Block Extension SupervisorsBRM Block Review MeetingCEC Cooperative Extension CentreCRN Cocoa Research Institute of NigeriaEA Extension AgentFACU Federal Agricultural Coordinating UnitFRI Forestry Research InstituteFVS Fixed Visit ScheduleHOUs Heads of UnitsIAR Institute of Agricultural ResearchIAR&T Institute of Agricultural Research and TrainingIITA International Institute for Tropical AgricultureIKS Indigenous Knowledge SystemLCRI Lake Chad Research InstituteLGC Local Government CouncilsLRI Leather Research InstituteMOA Ministry of AgricultureNAERLS National Agricultural Extension Research Liaison ServicesNAPRI National Animal Production Research InstituteNARSs National Agricultural Research Institutes

NATSP National Agricultural Technology Support ProjectNCRI National Cereals Research InstituteNFDP National Fadama Development ProjectNIFOR National Institute for Oil Palm ResearchNIHORT Nigerian Institute for Horticultural ResearchNRCRI National Root Crops Research InstituteNSPRI Nigeria Stored Products Research InstituteAbbreviations and AcronymsOAU Obafemi Awolowo UniversityOFAR On-Farm Adaptive ResearchOFR On-Farm ResearchPCU Project Coordinating UnitPFT Project Facilitating TrainingPMU Project Management UnitREB Research - Extension BoardRH Regional HeadsRRI Rubber Research InstituteSMS Subject Matter SpecialistsSPATs Small Plot Adoption TechniquesTOT Transfer of TechnologyTRM Technology Review MeetingsT&V Training and VisitsVRI Veterinary Research InstituteZEO Zonal Extension OfficerZM Zonal ManagerZSs Zonal SupervisorsATPS Working Paper SeriesNo.Title Publication Authors1 The Effect of Economic Reform on Technological Capability T. AdeboyeM. S. D. BafachwaO. A. Bamiro2 Methodological Issues in Science and Technology Policy Research T. AdeboyeN. Clark

4 Rehabiliation in the Manufacturing Sector in Tanzania S. M. Wangwe5 Agricultural Policy and Technology in Sierra Leone C. Squire6 Effectiveness of Agricultural Research Extension in Sierra Leone A. K. Lakoh8 Generation and Utilization of Industrial Innovation in Nigeria O. OyeyinkaG. O. A. LaditanA. O. Esubiyi9 Irrigation in the Tuli Block, Botswana Water Conservation Techniqesor Optimal Strategies I. N. Masonde10 Endogenous Technology Capacity and Capability Under Conditionsof Economic Policies of Stabilization and Structural Adjustment S. E. Chambua11 Technology and Female-Owned Business in the Urban InformalSector of South-West Nigeria R. O. Soetan12 Technology Innovations Used to Overcome the Problem of ResourceScarcity in Small Scale Enterprises C. W. Ngahu13 Financing of Science and Technology Institutions in Kenya DuringPeriods of Structural Adjustment M. Mwamadzingo14 Impact of Economic Liberization on Technologies in EnterprisesProcessing Agricultural Produce P. Madaya15 Technology and Institutions for Private Small and Medium Firms B. Oyeyinka16 Institutiona Reform, Price Deregulation and Technological Changein Smallholder Agriculture E. C. Eboh17 Adoption of Agricultural Technologies by Rural Women under theWomen-in-Agriculture Program in Nigeria D. S. Ugwu18 Electrical Power Utilities and Technological Capacity Building inSub-Saharan Africa Brew-Hammond19 Investigation into Factors that Influence the Diffusion and Adoptionof Intentions and Innovations from Research Institutes and Bwisa, H. M. andUniversities in Kenya Gachui20 The effects of Economic Reforms on the Quality on the Quality ofTechnological Manpower Development in Nigeria H. E. Nnebe

21 Issues in Yam Minisett Technology Tranfer to Farmer in Southern Michael C. MadukweNigeria Damain AyichiErnest C. Okoli22 Technological Respone to Telecommunication Development: AStudy of Firms and Instituions in Nigeria Adeyinka F. Modupe23 Gender Differences in Small Scale Rice Farmers’ Access toTechnological Inputs in Enugu State of Nigeria David Nwoye Ezeh24 Adoption of Sustainable Palm Oil Mini-Processing Technology inNigeria Nkechi Mbanefoh25 Domestic Energy Situation in Nigeria: Technological Implications Olabisi I. Ainaand Policy Alternatives26 Technological Capability in the Nigerian Leather Industry: A Uka Enenwe,Firm-Level Case Study Enwere dike,Anthony Ihuoma,Mike Duru.27 Agricultural Research and Delivery in the South-Eastern Highlandsof Ethiopia: A Case Study of the SG-2000 Approach in HitosaDistrict G. Yiemene28 Impact of Computer Technology Adoption on Banking Operationsin Nigeria A. I. Odebiyi29 Agricultural Technology Adoption on Small-Holder Farmers: PolicyPolicy Options for Nigeria J. O. Olusi30 Donor Funding and Sustainability of Rural Water Supply and Aja Okorie,Sanitation Technologies in Swaziland M. Mabuza,U. Aja-Okorie.31 Promotion of Production and Utilization of Ceramic RoofingMaterials in the Informal Housing Industry in Sierra Leone Tamba Jamiru32 Technology Transfer and Acquisition in the Oil Sector andGovernment Policy in Nigeria R.I. ChimaE.A. Owioduoki

R.I. Ogoh33 Acquisition of Technological Capability in Africa: A Case Studyof Indigenous Building Materials Firms in Nigeria Yomi OruwariMargaret JevOpuene Owei34. Analysis of Indigenous Knowledge in Swaziland: Implicationsfor Sustainable Agricultural Development Musa A. DubePatricia J. MusiDr. M.C. Madukwe and Dr. E.C. Okoli are both Lecturers at the Department of Agricultural Extension,University of Nigeria, Nsukka, Nigeria. Dr. S.O. Eze is a lecturer with the Ebonyi State AgriculturalDevelopment Programme Abakaliki, Ebonyi State, Nigeria.For more information on this series and ATPS, contact:The Executive DirectorThe African Technology Policy Studies Network3rd, Floor, The Chancery,Valley RoadP.O. Box 1008100100 General Post OfficeNairobi, KenyaTel: 254-2-2714168/092/498Fax: 254-2714028Email: info@atpsnet.orgWebsite: http://www.atpsnet.org1This report examined the concept of agro-technology transfer and presents success indices. Featuresof each of the agro-technology sub-systems (generation, transfer and utilization) are discussed. Theagro-technology generation sub-system, ecological distributions of agro-research institutes anduniversities are presented. The agro-technology transfer sub-system, the historical involvement and

organizational structure of different universities, and the Agricultural Development Programme (ADP)are examined. Similarly, the characteristics of the agro-technology utilization sub-system are presented.Two theoretical approaches commonly used in the analysis of agricultural technology transfer systemswere examined and eight basic issues for comparative analysis of agro-technology transfer systemswere identified using the systems approach.This is followed by the comparison of the agro-technology generation practices of the ADP and universityagro-technology transfer systems based on: the organization of staff, and farmer characteristics; use ofagricultural technology packages; and contact methods.Recommendations and policy options for restructuring agro-technology transfer practices in Nigeriaare presented.The problemNearly two decades after independence, in 1960, the Nigerian agricultural technology transfer policyemphasized transfer of technical information on specific cash crops using regional Ministries of Agriculture(MOA) in the north, west and east. The period saw the establishment of agro-research institutes, namely:Institute of Agricultural Research (IAR) in the north; Moore Plantation in the west; and National RootCrops Research Institute (NRCRI), Umudike in the east, to link research and extension services.With state creation in 1968, the main focus of agro-technology transfer policy was food productionthrough the Federal and states’ MOA. It was slow in achieving the desired objectives of agro-technologytransfer, because of the bureaucracy. However, it was the sole agency responsible for agro-technology

transfer until the 1976 local government reform, which gave some specific agricultural technology transferfunctions to Local Government Councils (LGC; Mijindadi, 1983). Some defects of the LGC technologytransfer policy include poor job description of staff, lack of mobility and absence of staff training andcontacts with farmers (Madukwe, 1996). Further reforms of the Nigerian agricultural technology transferChapter OneIntroduction2 ATPSWORKING PAPER SERIES NO. 35policy gave rise, in the seventies, to the involvement of universities and Agricultural DevelopmentProjects (ADPs) to transfer agro-technology to farmers.Initially, five conventional universities namely: Ahmadu Bello University, Zaria; University of Ibadan,Ibadan; University of Ilorin, Ilorin; University of Nigeria, Nsukka; and Obafemi Awolowo University, Ile-Ife, were involved. Later, the university of agriculture policy was initiated in 1988 to amplify the efforts ofconventional universities in agro-technology transfer services to farmers. This led to the establishmentof the University of Agriculture at Abeokuta, Makurdi and Umudike. In addition, the successes of enclaveADPs at Ayangba, Lafia, Ekiti-Akoko, Gusau, Katsina and Gombe, gave rise to state-wide ADPs in the1980s. Currently, the ADP and university are the prominent government funded agro-technology transfersystems in Nigeria. This pluralistic approach to government participation and funding in the transfer,has the potential for duplication of effort and waste. Beyon (1998) noted that African countries spendbetween 10 and 20 times on agro-technology transfer compared to developed countries.

An agricultural technology transfer system has identifiable organizational structure linked toinstitutionalized source of new agro-technologies and independent staff with appropriate channel fordisseminating research information to end users (Madukwe, 1995). A viable agricultural technologysystem has technology generation, transfer and utilization sub-systems with notable indices of success.The success indices of a viable transfer system include: constant creation of technical knowledge,extension staff training and contacts, harmonious existence with other agencies, orienting technologiestowards utilization and provision of information on necessary farm inputs (Mijindadi, 1994;Swanson,1997). The study considered the university and ADP as agro-technology transfer systemsand comparatively analysed the two systems using a systems approach. The systems approachrecognizes three sub-systems necessary in implementing a viable agricultural technology transfersystem, namely: technology generation, transfer and utilization.The question that arises is as to what extent ADP and university have developed these indices to justifytheir operation. The ADP used the training and visits (T & V) strategy which focuses on improving theknowledge and skills of small holder farmers, using technology testing and transfer techniques onstate-wide coverage. On the part of the university, emphasis has been on generating relevant agriculturaltechnologies within the faculties of agriculture and using available resources to transfer these technologiesto the farmers at selected farming communities. What comparative advantages exist between theuniversity and ADP in agro-technology transfer practices to the farmers? What were the practices

adopted by the university and ADP in sourcing research information, implementing staff training andcontacts? What social and economic changes among the farmers could be attributable to each of thesesystems and what differences exist between farmers served by the two systems? What methods wereemployed by the ADP and university in persuading farmers to use improved technical packages? Whatpolicy lessons could be learned from the approaches of the university and ADP systems to enhanceagricultural technology transfer process in Nigeria?ANALYSIS AND COMPARISON OF THE AGRICULTURAL DEVELOPMENT PROGRAMME AND UNIVERSITYAGRICULTURAL ... NIGERIA 3Purpose of the studyThe overall purpose of this study was to comparatively analyse the agro-technology transfer systemsof the ADP and university in Nigeria. Specifically, the objectives were to:(1) compare the agro-technology generation and transfer practices of university and ADP,(2) compare the socio-economic impacts of the agro-technology transfer systems of universityand ADP, and(3) identify necessary policy issues to ensure the effectiveness of the agro-technology transferprocess in Nigeria.4Literature is organized under agricultural technology generation, transfer and utilization sub-systems.Agricultural technology generation sub-systemAgricultural technology has remained a viable tool for improving the productivity of the agriculturalsector in Nigeria. Thus, a major step in the improvement of food production in Nigeria has been the

increase in the number of the national and international agro-research institutes from 3 in 1963 to thecurrent 18. Agro-technology generation in Nigeria is carried out by National Agricultural ResearchInstitutes (NARIs) with mandate in arable crops, forestry and tree crops; livestock; fisheries; extensionand training; and processing and storage.According to Okon (1998), the aim of agro-technology generation is to address better techniques ofland development, crop and animal management and achieve higher yields. Thus, agricultural technologygeneration system is aimed at providing modern technology and facilities to communities (Bolade,1990; Eziator, 1990 and Njoku, 1991). According to Ayichi (1995), agricultural technology involves theapplication of mechanical, chemical and biological inputs such as tractors, fertilizers, agro- chemicals,livestock breeds, high yielding crops, storage and processing facilities, to improve food production.Technology generation is influenced by determination of need,and research and management oftechnology generating institutions (World Bank, 1994). Previous research reports blamed ineffectivenessin technology generation on conventional research activities operated in Nigeria. Which have poorconsideration of farmers’ problems, skill and scale of operation and financial status and orienting ofresearch to journal publication (Zaria et al., 1994). In developing countries such as Nigeria, the acutelack of collaboration between the social and biological scientists on farming system research (FSR),has limited research efforts in generating relevant technologies (Van den Ban and Hawkins, 1992). Thenet effect of FSR adopted as a policy in the activities of the agricultural technology generation subsystem

is the evolvement of technologies best suited to existing farming system and accepted byfarmers (Asiabaka, 1998).According to Blum (1991), most research efforts in technology generation in developing countries arewasted due to their inadequate orientation to farmers’ needs and utilization. Farinde (1996), added thatthe bureaucracy domiciled in the Ministry of Agriculture and Natural Resources, under which researchChapter TwoLiterature ReviewANALYSIS AND COMPARISON OF THE AGRICULTURAL DEVELOPMENT PROGRAMME AND UNIVERSITYAGRICULTURAL ... NIGERIA 5institutes operate in Nigeria, contributes to the inability of research into meeting technology needs offarmers. In the 1990s, emphasis on agricultural technology generation has shifted from euphoria ofspectacular results to appropriateness of these technologies to the existing farming system. An agriculturaltechnology is considered appropriate, if it provides a cost-effective level of productivity and has minimaleffects on the environment (McNamara, 1990; Okigbo, 1991). According to Platt (1989), a critical issueto the appropriateness of technologies is in developing them at local levels using skills and perceptionof the people who live in the rural communities. Presently, technology generation sub-system in Nigeriaexperiences poor and uncertain funding, frequent government administrative changes and lack of policyinitiative in research.According to Vengara and McDicken (1990), technologies which are capable of improving foodproductivity at farm level should evolve from well funded autonomous research sub-system, so as to

provide timely solution to priority problems of farmers. Farmer-driven research effort must be based onpolicy setting, utilization of research personnel, continuous flow of information and evaluation of itsactivities (ISNAR, 1984). The technology generation efforts should be oriented towards social desirability,economic feasibility and existing practices of the farmers as a priority (Monu and Omole, 1983; Farinde,1996).Technology generation in Nigeria results from the national agricultural research system, namely; universityfaculties of agriculture and veterinary medicine including universities of agriculture, and internationaland national agricultural research institutes, which operate in Nigeria. The objectives of the researchinstitutes are impressive, but the issues of establishing a workable relationship between institutionaltechnology design and indigenous knowledge system (IKS), constitutes a critical issue in technologygeneration in Nigeria. A workable relationship between institutional technology generation and indigenousknowledge system is largely desired to enhance orientation of technologies towards utilization andoverall participation of farmers in extension systems (Rajasekaran et al., 1993). This is necessary toachieve compatibility of technologies to farmers’ practices and overall suitability to field needs. Severalstudies such as those of Igodan and Adekunle (1993), Rolings and Pretty (1997), and Anyanwu (1997a),have highlighted the need for indigenous knowledge in generating appropriate technologies and overallsustainability in food production.Agricultural technology transfer sub-systemThere is a problem of choice of the right type of agricultural technologies and methods with which to

communicate relevant technologies to small scale farmers. To enhance adequate food production inNigeria, demands that farmers should be reached with appropriate technologies that are economicallyviable and culturally acceptable (Sokoya, 1998). Utilizing appropriate methods in reaching small scalefarmers with relevant agricultural technologies in order to improve their knowledge, skill and overallattitude towards agricultural productivity, is agricultural technology transfer. According to Farinde (1996),technology transfer involves complex processes consisting of diverse structures, and relationship ofinter-dependent factors and related variables, aimed at enhancing adoption of innovations.6 ATPSWORKING PAPER SERIES NO. 35Agricultural technology transfer constitutes a crucial sub-system in implementing any agro-technologyprocess. Effective technology transfer involves organizing of personnel in a hierarchy, staff training andcontacts, and adopting of appropriate communication process. According to Ogolo et al., (1994), effectivecommunication is a pre-condition for feedforward and feedback mechanisms, necessary for sustainableagricultural technology transfer. Agricultural technology transfer as a communication technique requiresa two-way directional information movement, which involves six elements, the source, message, channel,receiver, effects and feedback (Chinaka, 1993). Thus, effectiveness in technology transfer involveswell articulated communication elements in the transfer process (Obinne and Anyanwu, 1991). In otherwords, effective integration of communication elements, enhances sustainability in communication ofideas and consequent transfer of agricultural technology to farmers.

Asiabaka (1998), added that formal arrangement of staff in the transfer of agricultural technology,enhances participatory approach in which farmers’ views are represented and practical orientation inwhich efforts are focussed on immediate problems of farmers. Chuta (1992), blamed inadequateorganization and overall ineffectiveness of Nigerian agro-technology transfer systems on low andunsuitable qualifications of personnel operating in the system. According to Madukwe (1995b), mostadministrative staff in Nigerian agro-technology transfer organizations, have little training in basic issuesof administering agro-technology transfer process.Organization of activities in any agricultural technology transfer system demands a chain of administrativecommands, which largely depend on legal basis of operation (Adebayo, 1995). A legal base is requiredin order to define a number of programmes, determine qualification of personnel, manner of entry andexit, discipline, training and conditions of service (Madukwe, 1996). Legal basis indicates a policydocument establishing the technology transfer system. Such policy document spells out the structure,budget, level of autonomy and clients.Effective technology transfer system places emphasis on simplicity in the structure of transfer organizationin terms of the relationship existing among staff of the organization. Basically, we have vertical andhorizontal relationships between staff of a technology transfer organization. Whereas vertical relationshipindicates top down and bottom up relationship among staff of the organization, horizontal relationshipdepicts relationship between staff at the same level in an organization. Effective vertical relationship

requires well-articulated horizontal staff relationship. Thus, inadequate horizontal relationship of extensionstaff would largely limit meaningful vertical structure and overall efficiency in implementing technologytransfer.Previous studies by Uwakah (1985) and Ijere (1992), have blamed delay in transfer of agriculturaltechnologies and overall lack of adoption of recommended agro-technologies on inadequate budgetaryallocation and absence of autonomy. Autonomy indicates degree of independence necessary inestablishing efficiency and sustainability in implementing agricultural technology transfer.ANALYSIS AND COMPARISON OF THE AGRICULTURAL DEVELOPMENT PROGRAMME AND UNIVERSITYAGRICULTURAL ... NIGERIA 7Agricultural technology utilization sub-systemAgro-technology transfer programmes are directed towards farmers with diverse social, educational,political and economic needs (Obibuaku, 1986). Studies by Titilola (1994) and Igbokwe (1995), identifiedsocio-cultural and economic characteristics of farmers, as factors influencing farmer participation andadoption of agricultural technologies in Nigeria.Socio-cultural characteristics of farmers include, family size, farm size, social organizations, valueorientation, belief system, prevailing norms, educational background and attitudes of farmers towardschange and material well being (Jibowo, 1992; Sene, 1994). According to Ijere (1992) and Nweze(1995), economic characteristics of farmers include: income status, labour availability, internal resourcemobilization, investment rate, saving potentials and marketing pattern. Husain et al. (1993) blamed

inadequate adoption and ineffectiveness of most agro-technology transfer programmes on lack ofconsideration of the socio-cultural practices and technology incompatibility with the economic status offarmers. Ayichi (1995), added that the impact of any agricultural technology transfer system could bemeasured on the basis of extent of changes in the socio-cultural and economic characteristics of thefarmers.Impacts are enduring changes in the social and economic conditions of farmers, which have resultedfrom project effects (Obiechina and Otti, 1985; Ladele, 1991). Some related studies like those ofOgunbameru (1986) and Agwunobi (1993), reported that farmer participation in planning and projectimplementation, enhanced greater socio-economic impacts. They concluded that training of farmersfacilitated adoption of recommended practices.The impacts of any extension system relate to improvement in the socio-cultural and economiccharacteristics of the farmers, such as increases in farmers’ income and improvement in overall standardof living. Earlier impact studies identified increases in the levels of participation in programme planning,hectare of land cultivated by farmers, positive changes towards agriculture and greater access to socialservices, as success indicators (Aihonsu, 1992).8Conceptual frameworkTwo theoretical approaches commonly employed in the analysis of agricultural technology transfersystems are: transfer of technology (TOT) and systems approaches. The TOT model posits a linearrelationship between knowledge creation, exchange and user sub-systems. Traditionally, the TOT model

involves a vertical one way directional communication, featuring technology generation, exchange andutilization sub-systems. The model is biased towards knowledge creation rather than knowledge users.Thus, knowledge creation commonly deals with those problems that are considered relevant toresearchers’ interests, rather than orienting research efforts towards utilization. In other words, newtechnologies are constantly generated by knowledge creation sub-system and given to knowledgeexchange sub-system, for transfer to knowledge user sub-system.The TOT model puts little emphasis on co-ordination between the technology generation and transfersub-system (Asiabaka, 1998). The situation permits only feedback from knowledge user to knowledgecreation sub-systems through knowledge exchange sub-system. This is a major defect of the thismodel. It neglects the role of both general and agricultural education as synergistic factors, enhancingthe potential value of newly acquired agricultural knowledge. The approach also neglects the centralimpact, which policy making or the disastrous effects of its lack, has on the agricultural knowledgesystem.The systems approach seems to correct the imbalance inherent in the TOT model. It was introduced forthe analysis of agro-technology transfer system by Nagel (1980). The approach was further amplifiedby Swanson and Claar (1983), Lionberger (1986), Rolings (1988a, b) and Blum (1989).The utilization of the systems approach for the analysis of agricultural technology transfer systems isbased on the assumption that interactions exist between technology generation, transfer and utilization

sub-systems. The situation permits direct linkages and feedback across sub-systems interface. Inother words, there are linkages between technology generation, transfer and utilization sub-systems,as well as direct linkages and feedback between technology generation and utilization sub-systems.This is schematically represented in Figure 1.Chapter ThreeMethodologyANALYSIS AND COMPARISON OF THE AGRICULTURAL DEVELOPMENT PROGRAMME AND UNIVERSITYAGRICULTURAL ... NIGERIA 9Figure 1: Conceptual framework for a comparative analysis of ADP and university technologytransfer system.TECHNOLOGYGENERATIONSUB-SYSTEM:. Evolution ofnewtechnologies. Involvementof Extensionworkers intechnology. Distance totechnologytransfer subsystem.. Participationand control byuser subsystemTECHNOLOGYTRANSFER SUBSYSTEM. Degree ofautonomy

. Legal statues

. Cost ofeffectiveness Stafftraining. Extensionteaching methods. Organizationalstructure. Number, type andrank of personnel. Level ofinteraction withother exchangesub-system.. Degree ofinfluence by usersub-systemTECHNOLOGYUTILIZATION SUBSYSTEM. Social compatibility andeconomic feasibility oftechnologies. Categorization of user intechnology transferpractices. Level of participation ofusers in technologytransfer. Degree of farm inputsavailability. Acceptance of newtechnologies. Improved statuses oftechnology usersTypes of

linkagesin theADPSanduniversitiesextensionsystemINTERACTION BETWEENTECHNOLOGY GENERATIONAND TRANSFER SUB-SYSTEMIN ADP AND UNIVERSITYINTERACTION BETWEENTECHNOLOGY TRANSFER ANDUTILIZATION SUB-SYSTEMS INUNIVERSITY AND ADPTypes oflinkages inthe ADPSanduniversitiesextensionsystemsDIRECT LINKAGES AND FEEDBACK BETWEEN TECHNOLOGY GENERATION ANDUTILIZATION SUB-SYSTEM IN ADP AND UNIVERSITY10 ATPSWORKING PAPER SERIES NO. 35The schema suggests mutual interactions and linkages between the major sub-systems as a preconditionfor successful implementation of agricultural technology transfer systems. In other words, theschema posits users’ influence in technology generation and participation in technology transfer practices,as well as involvement of technology transfer personnel in technology generation. Earlier research

reports indicated that in a successful agricultural technology transfer system, technology users formpart of a research team and participate in technology transfer activities (Ajala and Madukwe, 1992).The schema posits eight basic issues for consideration in the comparative analysis of agro-technologytransfer systems of the ADP and university in Nigeria, namely:(1) sources of new technologies,(2) degree of linkages between technology generation, transfer and utilization sub-systems,(3) extent of users’ influence on technology generation and participation in technology transferpractices,(4) level of technology transfer workers’ involvement in technology generation and managementof field trials,(5) degree of autonomy in the technology generation, transfer and utilization sub-system,(6) number, type, ranks and distribution of extension personnel,(7) degree of staff training and contacts with clients system, and(8) level of social compatibility and economic feasibility in technology generation and transferprogrammes.The schema suggests that a successful technology generation involves variables such as field driventechnology evolution, technology transfer workers’ and farmers’ participation in technology generationand a social distance span between technology transfer sub-systems. In addition, a successful technologytransfer sub-system depends on issues such as legal status, organizational structure, budgets, autonomyof service and qualifications of staff. Also in significance is the staff training, teaching methods, level ofinteractions with other exchange sub-systems and degree of user influence over transfer activities.

Similarly, a successful technology utilization sub-system involves issues relating to social compatibilityand economic feasibility of technologies, categorization of users in technology transfer, level ofparticipation of users in technology transfer and degree of input availability. Levels of acceptability ofnew technologies and socio-economic characteristics among technology users in terms of improvedproductivity, income levels, and desired changes in knowledge, skills and attitudes towards extensionprogrammes are also important. We argue that agro-technology transfer is an interactive process involvingresearcher, farmer and other key operators in agricultural development. The acid test of the success ofagro technology transfer systems of the ADP and university is the extent to which their operationsapproximate the indices of a successful agricultural technology transfer system.ANALYSIS AND COMPARISON OF THE AGRICULTURAL DEVELOPMENT PROGRAMME AND UNIVERSITYAGRICULTURAL ... NIGERIA 11Study populationNigeria is politically administered under a 36 state structures and a federal capital territory, Abuja.There are 37 ADPs, one in each of the 36 states and the federal capital territory, Abuja. In addition,there are seven federal universities with agricultural technology transfer programmes. The seven federaluniversities include Ahmadu Bellow University, Zaria; University of Agriculture, Abeokuta; University ofIbadan, Ibadan; University of Ilorin, Ilorin; University of Agriculture Makurdi; Obafemi Awolowo University,Ile-Ife; and University of Agriculture, Umudike. All the ADPs and universities staff, and farmers in theiroperational areas, constituted the target population.

Sample sizeThe study selected four states, namely Benue, Kaduna, Ogun and Osun. Their selection was based onthe existence of universities with agro-technology transfer outreach programmes and geographicalspread. Both the universities and ADPs in the selected states were comparatively investigated. Fromeach university, the director of the agro-technology transfer unit and three departmental staff; one fromresearch and two from agro-technology transfer (extension services), were selected. At field level, 12agro-technology transfer workers and 24 farmers from each of the universities, were randomly selected.Thus, a total of 64 university agro-technology transfer workers and 96 farmers served by the universities,were randomly selected.At the headquarters level of each of the state ADP, the directors of three core sub-programmes, extension,technical and rural institution development, and one support sub-programme, administration, wereinvolved. At the zonal level, three zones were selected per state, the Zonal Manager (ZM) and ZonalExtension Officer (ZEO) of each zone were selected. Three Subject Matter Specialists (SMSs) perzone (Agronomy, Women in Agriculture, and Livestock) were selected.At the block level, six Block Extension Supervisors (BESs) and six Extension Agents (EAs) (made up ofone EA per block), were selected per zone. At the farmers’ level, 36 farmers per state (made up of 12farmers per zone, that is, two farmers per selected EA), were randomly selected. Thus, 55 extensionstaff and 36 farmers per state ADP were involved in the study. A total of 220 extension workers and 144farmers served by the ADP were involved in the study.

Thus, a total of 524 respondents made up of 284 extension workers and 240 farmers, constituted thesample size for the study.Data collectionData were obtained from both primary and secondary sources. The primary sources include interviewwith ADPs and universities staff as well as farmers served by the two agencies. Two sets of questionnaires,one for management staff and the other for field workers, were used to collect data from workers of both12 ATPSWORKING PAPER SERIES NO. 35agencies. Secondary data were derived from assessment of documented materials on agriculturaltechnology transfer practices of the agencies.The management staff questionnaire measured organizational structure of the ADP and university,specific extension programmes, how programmes were initiated, frequency of implementation, inputoutputrelationships, and funding, monitoring and evaluation. Section A of both extension staffquestionnaire and the farmer interview guide, measured issues comparing technology generation inADP and university, and involvement of extension workers in technology generation, and the influenceof users in technology generation. Section B measured autonomy, legal status and structure of extensionservices, staff training contacts, and qualification, and farmers’ participation in technology transferpractices of the ADP and university. Section C investigated variables relating to type and number oftechnologies transferred to the farmers, input provision, method of communication adopted in transferprocess and socio-economic characteristics of farmers. Assessment was also made under section C to

determine farmers’ evidence of expansion in farm holdings and use of agro-technology packages.Data analysisThe information collected was analysed using percentages (based on the proportion of total respondentsindicating an opinion to a question), mean scores,(average of the scores of individual responses toparticular question on a 1-5 continuous scale), standard deviation and group t-test. The biodata ofrespondents and overall organizational structure of the ADP and university, were analysed usingpercentages. Sections A and B, which compared the means for agro-technology generation and transfers,respectively, were analysed using group t-test at 5% probability for significance. Finally, section Cwhich compared the extension systems of the ADP and university on socio-economic indices of theagencies and participating farmers, was analysed using percentages.13The findings are presented as follows:(1) features of the agro-technology transfer systems,(2) comparison of agricultural technology generation, and sub-systems transfer, and(3) comparison of socio-economic characteristics of ADP and university.Features of the agro-technology transfer systemsIn this section, information is provided on:(1) ecological distribution of agro-research institute in Nigeria,(2) involvement of university in agro-technology transfer, and(3) features of the ADP agro-technology transfer system.Ecological distribution of agro-research institute in NigeriaThe Federal Government of Nigeria divides the country into five agro-ecological zones. The agroecologicalzones of Nigeria are southeast, southwest, central, northwest and northeast.

Southeast zone: The zone consists of nine states, Abia, Akwa Ibom, Anambra, Bayelsa, Cross River,Ebonyi, Enugu, Imo and Rivers. Two research institutes are located in the southeast zone, NationalRoot Crops Research Institute (NRCRI), Umudike; and Nigeria Stored Products Research Institute(NSPRI), Port Harcourt. Also, five federal universities with faculties of agriculture are located in thesoutheast zone. These universities which are involved in agro-research activities include: University ofNigeria, Nsukka, University of Uyo, Uyo; University of Calabar, Calarbar; Federal University of Technology,Owerri, and Federal University of Agriculture, Umudike.Southwest zone: The zone consists of eight states, Lagos, Ogun, Osun, Oyo, Ondo, Ekiti, Edo andDelta. The agro-research institutes located in the southwest ecology include: Institute of AgriculturalResearch and Training (IAR&T) Ibadan; National Institute for Oil Palm Research (NIFOR), Benin; andCocoaResearch Institute of Nigeria (CRIN), Ibadan. Others include: International Institute for Tropical Agriculture(IITA) Ibadan, Nigerian Institute for Horticultural Research (NIHORT) Ibadan; Forestry Research InstituteChapter FourResults and Discussion14 ATPSWORKING PAPER SERIES NO. 35agro research activities in the southwest zone. The universities include University of Ibadan,Ibadan;Obafemi Awolowo University, Ile-Ife; Federal University of Technology, Akure; and University ofAgriculture, Abeokuta.The central agro-ecology zone: The central agro-ecology zone consists of the Federal Capital Territory,

Abuja; Plateau, Niger, Nassarawa, Kogi, Kwara, Benue and Taraba states. The central zone has researchinstitutes, National Cereals Research Institute (NCRI), Badeggi; Veterinary Research Institute (VRI),Vom; and Agricultural and Rural Management Training Institute (ARMTI), Ilorin. Also, federal universitieswith faculties of agriculture in the central agro-ecology zone include University of Ilorin; and Universityof Agriculture, Makurdi.Northwest zone: States within the northwest zone include Sokoto, Kebbi, Zamfara Katsina, Kaduna,and Kano. Research institutes located within the northwest are National Animal Production ResearchInstitute (NAPRI), Shika-Zaria; Leather Research Institute (LRI), Kano; National Agricultural Extensionand Research Liaison Services (NAERLS), Zaria; and IAR, Zaria. The federal universities located withinthe ecology, which engage in agricultural research activities are Ahmadu Bello University (ABU), Zaria;and Usman Dan Fodio University, Sokoto.Northeast zone: This zone consists of Borno, Yobe, Jigawa, Bauchi, Gombe and Adamawa states.The Lake Chad Research Institute (LCRI), Maiduguri has the responsibility of linking research andextension services in the northeast zone. Three federal universities, University of Maiduguri; AbubarkarTafawa Balewa University, Bauchi; University of Technology, Yola, are involved in the agro-researchactivities in the northeast zone.Involvement of university in agricultural technology transferThe idea of involving universities in agricultural technology transfer services could be traced to theattempt by British universities establishing educational programmes outside the campus to assist farmers

benefit from research efforts of the university (Obibuaku, 1983). However, the practical step to involveuniversities in organized agro-technology transfer services was by Cambridge University in 1876 andOxford University in 1878. The approach under British system was to give organized lectures underuniversities’ supervision to associations of men and women on the results of universities researchefforts (Ogunfiditimi and Ewuola, 1995). In the United States of America, involvement of universities inagro-technology transfer services commenced with passing of three legislative acts between 1862 -1914, to link research, educational institutions and informal educational orientation. The issue of agrotechnologytransfer in the American universities system was aimed at incorporating adult education,agricultural extension, nutrition, home economics and mass communication in the educationalprogrammes of the universities. To implement this, the cooperative extension services were formed ineach state in association with the Land Grant Colleges, and farmers were granted land by the NigeriaFederal Government, to operate under the advisory services of the major universities (Obibuaku, 1983).ANALYSIS AND COMPARISON OF THE AGRICULTURAL DEVELOPMENT PROGRAMME AND UNIVERSITYAGRICULTURAL ... NIGERIA 15In Nigeria, universities’ involvement in agricultural technology transfer came into existence in the earlyseventies. The universities technology transfer system in Nigeria was modelled along the cooperativeextension system of the United States (Ogunfiditimi and Ewuola, 1995). The approach involves thefaculties of agriculture of universities utilizing research reports of their academic departments and their

independent staff, in implementing agro-technology transfer to selected farming communities. In thepast, five conventional universities, Ahmadu Bello University, Zaria; University of Ibadan, Ibadan;University of Nigeria, Nsukka; University of Ilorin,Ilorin; and Obafemi Awolowo University, Ile-Ife; wereinvolved.Currently, the Isoya Rural Development Project of the Obafemi Awolowo University, Ile-Ife; BadekuRural Change Project of University of Ibadan, Ibadan; and the Agricultural Research and ExtensionComplex of the Ahmadu Bello University, Zaria, have persisted in agro-technology transfer services tofarmers in Nigeria. In addition to the functional conventional universities, the universities of agriculturelocated at Abeokuta, Markurdi, and Umudike assist in agro-technology transfer services to farmers inNigeria. The universities’ approaches to agro-technology transfer differed among the universities,including the universities of agriculture.In Obafemi Awolowo University (OAU), the Isoya Rural Development Project is a unit responsible forimplementing agro-technology transfer services to the farmers. The Isoya Rural Development Projectis in the Department of Agricultural Extension and Rural Sociology, but headed by separate staff belowthe rank of a Director. The head of the Isoya Rural Development Unit reports directly to the Head,Department of Agricultural Extension and Rural Sociology (Figure 2).16 ATPSWORKING PAPER SERIES NO. 35Figure 2: Organogram of Isoya Rural Development Project of Obafemi Awolowo University.Source: Department of Agricultural Extension and Rural Sociology, Obafemi Awolowo University, Ile-Ife, Nigeria.VICE CHANCELLOR

HEAD DEPT. OFFOOD SCIENCE &TECHNOLOGYHEAD DEPT. OFANIMALPRODUCTIONHEAD DEPT. OFAGRIC. EXTENSION &RURAL SOCIOLOGYHEAD DEPT. OFSOIL SCIENCEHEAD DEPT. OFAGRONOMYHEAD OF UNIT: ISOYA RURALDEVELOPMENT PROJECTFIELD AGRIC. EXTENSION ADVISORSCONTACT FARMER/GROUPSDEAN, FACULTY OF AGRICULTUREANALYSIS AND COMPARISON OF THE AGRICULTURAL DEVELOPMENT PROGRAMME AND UNIVERSITYAGRICULTURAL ... NIGERIA 17The programme of the universities of Agriculture is designed to promote a more democratic and liberalisedtransfer of agro-technology to farmers. At the University of Agriculture, Abeokuta, the agro-technologytransfer programme is implemented by the Agricultural Media Resources and Extension Centre (AMREC),while the Cooperative Extension Centre (CEC) implements similar programmes at the University ofAgriculture, Makurdi.Administratively, AMREC of the University of Agriculture, Abeokuta, consists of a board chaired by theuniversity vice chancellor. Highly placed members of the society outside the university community are

also members. Other members of the board are deans of the academic colleges and the Director. Nextto the board is the AMREC management committee (AMRECMAC). The Director chairs the AMRECMACand other members include deans of colleges and the Director of Research and Development Centre ofthe University. Below the committee are seven relevant programme areas of agricultural technology,crops/forestry, livestock/wildlife/fisheries, post-harvest technology, women in development, training/demonstration, and development communication and environmental protection, headed by programmeleaders.Sectoral heads, further down the administrative hierarchy, are in charge of crops, forestry, livestock,wildlife, fisheries, processing, storage, utilization, cooperative groups, and adult functional/politicaleducation. Also included are groups in extension and farmer training, agricultural shows, education forcoping with changes, health and nutrition education, information publicity, audio-visual aids, radio,printing, waterology, and toxicology. The agro-technology transfer services of AMREC are implementedby specialists in crops, forestry, livestock, wildlife and fisheries, and there are also processing, storage,utilization and support services sectors. The administrative structure of AMREC under University ofAgriculture, Abeokuta is shown in Figure 3.18 ATPSWORKING PAPER SERIES NO. 35Figure 3: Administrative structure of agricultural media resources and extension centre of theUniversity of Agriculture, Abeokuta.Source: University of Agriculture, Abeokuta.

ANALYSIS AND COMPARISON OF THE AGRICULTURAL DEVELOPMENT PROGRAMME AND UNIVERSITYAGRICULTURAL ... NIGERIA 19At the University of Agriculture, Makurdi, the administrative structure of the Cooperative ExtensionCentre (CEC) includes the Vice Chancellor, who is the Chairman of the Research-Extension Board(REB). Other members of the REB include the Director CEC and deans of relevant colleges. Thisboard is the policy body that supervises the centres activities. The board coordinates the research andextension activities of the centre.The approved activities of the CEC are grouped into three major programmes, extension services,women in development and development communication. A senior extension officer heads eachprogramme. Furthermore, the agro-technology transfer programmes are implemented through thegrassroots and training programmes, which participate in adaptive research and demonstration, extensiondelivery, workshop and technology, review meetings (TRM).The women in development sub-programme operates the women in agriculture programme, whichimplements home economics and workshops programme, and the development communication unitimplements audio-visual and publication programmes. The audio-visual programme operates radio,TV, graphic and photography activities; the publication programme is in charge of editorial and printingservices. The administrative structure of the CEC is shown in Figure 4.20 ATPSWORKING PAPER SERIES NO. 35Vice-ChancellorDirector of Co-operativeExtenstionWomen in

DevelopmentExtension ServiceDevelopmentCommunicationEconomics Workshop Extension WorkshopDeliveryRadio/TVGraphics Photography Editorial PrinteryMonthlyTechnologyReview MeetingAdaptive ResearchandDemonstrationWomen inAgricultureProgrammeGrassrootProgrammeTrainingProgrammeAudio-VisualProgrammePublicityProgrammeContact Farmers/Contact GroupVillageExtensionAdvisorFigure 4: Administrative structure of the cooperative extension centre of the University of Agriculture, Makurdi.Source: University of Agriculture, Makurdi, Nigeria.ANALYSIS AND COMPARISON OF THE AGRICULTURAL DEVELOPMENT PROGRAMME AND UNIVERSITYAGRICULTURAL ... NIGERIA 21

The agro-technology transfer services of the CEC are made available to farmers by officers of thegrassroots extension programme; and the other programmes support activities of the grassrootsprogramme. However, the focus of the grassroots agro-technology transfer programme of the CEC isto provide prompt solutions to the farmers’ practical problems using research findings of the Universityof Agriculture, Makurdi.Features of ADP agro-technology transfer systemThe ADP is modelled as a reform of the regulatory, highly bureaucratized office, based on MOA agrotechnologytransfer system. The operation of ADP is preceded by the enactment of an edict giving it alegal status. An edict is a legal document, which gives formal approval for the establishment andoperation of the ADP, as an agro-technology transfer agency in a state. Under the edict establishingeach ADP, administrative, staffing, funding, supervisory, monitoring, evaluation and co-ordinatingprocedures are spelled out as basis for operation.The system posits that only integrated agricultural and rural development approaches appliedsimultaneously could reduce the problems of low productivity among the farmers. Its primary focus isthe small holder farmer. However, operational technique of the ADP is to raise farmers’ productivity,increase total farm output, and improve income levels and standard of living of the small scale farmers.To achieve these primary objectives, the system adopted the features in Figure 5 as follows.22 ATPSWORKING PAPER SERIES NO. 35Figure 5: Organogram of ADP agro-technology transfer system.Source: Project Coordinating Unit (PCU) Federal Ministry of Agriculture, Abuja, Nigeria.

ADPECPMUDIRECTORENGINEERINGDIRECTORRIDDIRECTORTECHNICALSERVICEDIRECTOREXTENSIONSERVICESDIRECTORADMINISTRATIONDIRECTORFINANCEDIRECTORPMEDIRECTORIIRDDEPUTYDES.ZEOBES.BEAEACONTACTFARMERSWGSKEYS:DES: Director Extension ServicesZN: Zonal ManagerZEO: Zonal Extension OfficerSMS: Subject Matter SpecialistBES: Block Extension Agent

EA: Extension AgentWG: Women's GroupANALYSIS AND COMPARISON OF THE AGRICULTURAL DEVELOPMENT PROGRAMME AND UNIVERSITYAGRICULTURAL ... NIGERIA 23Vertical structure: The ADP in each state is organized for ease of operation, into four levels,headquarters, zone, block and circle supervisory. The headquarters level is responsible for policyarticulation, budgeting, staffing, discipline, administrative control, supervision and coordination ofextension activities. The ADP is organized into two broad sub-programmes, core and support. The coresub-programmes are extension, technical, engineering services and rural institution development. Thesupport sub-programmes are finance, human resources development, administration and management,and planning, monitoring and evaluation. Administratively, the agricultural development project executivecouncil (ADPEC) oversees activities of the ADP, including workplan, budget approval, senior staffappointment and discipline. The Programme Manager (PM) serves as an administrative head in theADP and in conjunction with other members of the project management unit (PMU) make workplan andbudget proposals, appoint junior staff and promote and discipline the staff. At the headquarters, the PMis the administrative head. Below the headquarters is the zone, which is in charge of six to eight blocksand headed by a ZM. Assisting the ZM in the implementations of the programmes are the ZEOs and ateam of SMSs. Next to the zonal level is the block level, which represents an area with similar cropping/farming pattern. Occasionally, a block corresponds to a political area known as local government council.

However, a Block Extension Supervisor (BES) who is in charge of six to eight circles heads the block.The circle is headed by an extension worker called Extension Agent (EA). The job of extension contactwith farmers is executed at the circle level by the EA.The programme management unit (PMU): One basic step towards achieving effective administrativecontrol and technical command in the ADP is the involvement of a virile PMU in implementation ofprogrammes. The PMU is virtually autonomous in decision-making and project implementation and isconstituted by the heads of six to eight sub-programmes and zonal managers, with the programmemanager as chairman.Instituitionalized on-farm testing and adoptive trials: ADP has as linkage mechanisms, on-farmresearch (OFR); on-farm adaptive research (OFAR) and small plot adoption techniques (SPATs). TheOFR is a researcher managed farm testing technique, aimed at testing the result of his laboratoryresearch. It is set up to test the viability of the research results under farm situation. On the other hand,OFAR is a joint management technique between the researcher and farmer. It is implemented to testthe adaptability of OFR results under various farm locations/environments. The OFAR also serves as ameans of developing and validating new agro-technologies before transfer to the farmers. It enhancesfarmer participation in technology generation, design and supply services.Similarly, SPAT is a contact technique. It is a teaching laboratory aimed at enhancing communicationon proven agricultural technologies. The SPATS is a demonstration, which is organized by field extension

workers at farm level in order to enhance increased knowledge and skill acquisition of the relevantagricultural technologies among the farmers. Necessary farm inputs for implementing SPAT are providedby the farmers, except in situations where such technologies are entirely new in the farming communities.Tripartite funding arrangement: Funding arrangement in the ADP system involves the World Bank,and Federal and State Governments. From the inception of the ADP system, the funding ratio has24 ATPSWORKING PAPER SERIES NO. 35been: World Bank (66%), Federal Government (20%) and State Government (14%). Currently, withthe partial withdrawal of the World Bank sponsorship as a lending agency, the ADP has sought toinvolve local government councils and non-governmental organization (NGOs) in the fundingarrangement.Regular staff training and contact with farmers on fixed scheduled basis: Training is organized asa matter of policy in the ADP, either as external and sponsored by the ADP or in-house. Externaltraining is organized in form of workshops, conferences and seminars, either within or outside thecountry, mainly for management staff and subject matter specialists to update their knowledge andskills. Similarly, in-house training is organized for headquarters, zonal and block levels staff. Headquarterstraining is organized in form of project facilitating training (PFT) for members of the PMU, workshop andspecialized training in selected areas of ADP operations and technology review meetings (TRM).At zonal level, training is organized for zonal management staff, such as the ZM, ZEO, Zonal Supervisors

(ZSs) and a team of SMSs at TRMs, and monthly or fortnightly training for extension workers. At blocklevel, training is organized in form of block review meeting (BRM) for field extension workers, aimed atfine-tuning relevant production recommendations acquired at FNTs and reviewing of field situationactivities.In addition, the ADP system has scheduled contact with farmers under fixed visit schedule (FVS). TheFVS is adopted to enhance agro-technology transfer process and technical backstopping, necessary inachieving efficiency of feedback mechanism between farmers and extension workers.Provision/maintenance of rural infrastructure: In the past, ADP was engaged in the provision ofrural feeder roads, boreholes and storage projects, to enhance contacts with farmers. Currently, it hasadopted the National Fadama Development Project (NFDP), National Agricultural Technology SupportProject (NATSP) and maintenance of existing feeder roads. Under these projects, ADP is required toconstruct access and fadama roads, wash bores and tube wells, and organize the farmers into groupsand associations, aimed at enhancing teamwork among the farmers. This assists the farmers inembracing irrigation agriculture and maintaining basic rural infrastructure located in farming communities.Institutionalised monitoring, supervision, and coordinating activities: The operations of theextension system of ADP is supported by monitoring, supervizing, and coordinating agencies, such asthe agricultural project monitoring and evaluation unit (APMEU), and the federal agricultural coordinatingunit (FACU), recently renamed PCU. The APMEU is organized into headquarters and regional offices

for ease of operations.The headquarters offices are headed by Heads of Units (HOUs) and regional offices by Regional Heads(RHs). The APMEU collates and analyses quarterly and annual reports on workplan and budgets, cropyield, and performance evaluation activities on ADP staff. On the part of FACU, emphasis is on monitoring,supervision and coordination of the ADP projects. FACU activities are organized in line with the fiveANALYSIS AND COMPARISON OF THE AGRICULTURAL DEVELOPMENT PROGRAMME AND UNIVERSITYAGRICULTURAL ... NIGERIA 25agro-ecological zones in Nigeria with HOU at the national headquarters level and RH at the regionaloffices.Comparison of agro-technology generation practices of the ADP and universityThe results showed a significant difference (t = 2.03;p<0.05) in the levels of autonomy enjoyed by theADP and university in generating agricultural technologies. The university (0 = 4.26) had greater freedomin generating agricultural technologies than the ADP (0 = 3.54).Table 1: Differences in technology generation practices between the ADP and universityTechnology generation Means indicatingpractices level of existence (max.=5)ADP University t-cal.Autonomy in technologygeneration 3.54 (1.47)+ 4.26 (1.19)+ 2.03*Technology generationbased on field problem 4.05(0.93) 4.43(1.22) 1.80*Farmers participate infield research trials 4.00(0.10) 3.52(0.96) 1.78*Technology generationactivities keep pace with

current field practices 3.76(1.11) 3.32(1.0) 1.67*Adaptive research trials arelocated in farmers’ field 3.17(1.11) 2.84(1.17) 1.18Extension agents participatein field research trials 4.20(1.07) 3.89(1.49) 1.09Adequate research facilitiesand incentives to workers 2.84(1.11) 3.15(1.17) 1.18Distance betweentechnology generation andtechnology transfercomponent 2.89(1.26) 2.21(1.36) 2.17*Farmers co-financeadaptive research trial 1.82(1.17) 1.63(1.14) 0.67*P < 0.05.+ Data in parenthesis are standard deviationsAutonomy in technology generation had been identified as a major index of success in agriculturaldevelopment (Blum, 1991; Madukwe, 1996). Autonomy in agro-technology generation meansindependence, non-interference in problem identification and uninterrupted technology design and supplyservices.26 ATPSWORKING PAPER SERIES NO. 35The ADP and university differed on the extent to which their technology generation activities wereoriented to farmers’ field problems (t = 1.80). Orientation of technology generation towards field problems,means directing research activities towards addressing the immediate and pressing field problems offarmers. Such technology generation effort should be cost-effective with minimum adverse effect onfarmers’ environment (McNamara, 1990). The analysis indicates that ADP’s (0 = 4.05) technologygeneration activities had poorer orientation towards the farmers’ field problem, compared to the university

(0 = 4.43). One reason for this could be because university research efforts were based or targeted atspecial problems of known farmers in a geographical location, while the research results implementedby ADP were conducted by research institutes. They provide answers to problems affecting farmers indiverse geographical location, thus making such solutions less targeted to the specific needs of farmers.Orientation of technology generation efforts towards farmers’ fields would ensure that new technologiesevolve from farmers’ field problems. Evolution of technologies from farmers’ field problems had beenidentified as an index of a successful agro-technology generation sub-system (Blum, 1991).Other areas of differences in technology generation between the agro-technology transfer systems ofADP and university, include levels of farmer participation in field research trials (t = 1.78), and theextent to which the technologies generated kept pace with current field practices (t = 1.67). Farmers’participation in field research trials contributes largely to orienting agro-technologies towards sustainingfarmers’ interests. This practice ensures that technologies evolve from current field practices andproblems. The indication was that farmers participated less in field trials under the university system (0= 3.52), compared with the ADP (0 = 4.0). It was observed that though farmers participate less in termsof frequency of participation in university field research trials, they were more involved, mostly at theearly stages of planning. In the ADP system farmers were called in later in the research process,usually after the technology was developed in the entire process of field testing.

Also, the university differed with the ADP in the physical distance between their agro-technologygeneration and transfer sub-systems, (t=2.17). The close physical distance between the technologygenerating and transfer sub-systems could explain why in the university system the technology generatedkept pace with field practices. Distance between technology generation and transfer sub-systems hadbeen identified as a major factor influencing the quality and time of providing technologies to participatingfarmers (Blum, 1991; Madukwe, 1996). The ADPs were located farther from their technology generatingresearch institutes, compared with the universities. It depended on distant research institutes as sourcesof agro-technology, compared with the universities, which basically sourced relevant technologies fromtheir academic departments.The physical distance between the locations of the agency for technology generation and technologytransfer of any agricultural technology transfer system, could increase the cost and time of providingtechnical information to the participating farmers. The analysis showed that university technologieswould be more available to the participating farmers compared to the ADP, which would involve longerperiod and higher financial cost sourcing technologies from distant research institutes.ANALYSIS AND COMPARISON OF THE AGRICULTURAL DEVELOPMENT PROGRAMME AND UNIVERSITYAGRICULTURAL ... NIGERIA 27Data showed that the ADP and university did not differ on practices such as locating research in farmers’field (t=1.18); and involving field agents in the management of field trials (t=1.09). Other areas of similarity

include: provision of adequate research facilities and incentives (t=1.18); and farmers’ participation infinancing adaptive research (t = 0.67). Locating adaptive research in farmers’ field, demands fieldagents involvement in research management in order to establish the desired targets. In addition,provision of necessary research facilities and incentives would contribute largely to meaningfulinvolvement of the field agents and overall participation of farmers in financing adaptive research activities.Thus, the analysis indicates that the ADP and university in Nigeria had agricultural technology generationindices identifiable in a successful agricultural technology transfer system. The areas of discrepanciesand similarities are policy issues for consideration in harmonising agro-technology transfer practices ofthe ADP and university in Nigeria.Comparison of agro-technology transfer practices of the ADP and universityData (Table 2) indicate similarities between university and ADP in the use of farmers’ organizations (t =0.72), existing local communication channels (t = 0.61), in-house staff training (t = 0.70), demonstrationmethod (t = 1.26), and print and electronic media (t = 1.03) in agro-technology transfer. Involvement offarmers’ organizations could enhance employment of existing communication, while adoption of inhousestaff training would enhance staff learning and contact strategies necessary in achieving effectiveagricultural technology transfer to the farmers. Learning by firms and operators of technology transferagencies, has been identified as the key to effective transfer and diffusion of innovative capability(Mytelka and Tesfachew, 1999).28 ATPSWORKING PAPER SERIES NO. 35

Table 2: Differences in technology transfer practices between the ADP anduniversityTechnology transfer Means indicatingissues level of existence (max.=5)ADP University t-cal.Disseminating technologythrough farmers’organization 4.03(1.33) 3.34(1.53) 0.72Categorizing farmersaccording to needs 3.0(1.20) 3.67(1.3) 2.16*Orienting extension servicesto suit client interests 4.02(1.12) 3.67(1.16) 1.87*Disseminating technologiesthrough farmers’ existingcommunication channels 4.16(0.94) 4.05(0.62) 0.61Conducting short in-housestaff training 3.65(1.48) 3.63(1.34) 0.10Provision of trainingincentives to staff 3.39(1.37) 3.42(1.35) 3.33*Use of demonstrationmethods 4.39(1.04) 4.05(1.22) 1.26Use of print andelectronic media 3.06(1.31) 2.74(1.10) 1.03Knowledge of ruraldynamics 4.16(1.17) 3.37(1.12) 2.71**P< 0.05.+ Data in parenthesis are standard deviationsTable 2 shows that ADP and university differed in the practice of categorizing farmers for technologytransfer (t = 2.16), extension orientation towards clients (t = 1.87) and use of external training for staff (t= 3.75). University system (0= 3.67) significantly used farmer categorization strategy in technology

transfer more than the ADP (0 = 3.0). In other words, technology transfer practices of the universitywere more oriented towards meeting the specific farming needs of farmers than those of the ADP.Categorization of farmers into groups for technology transfer is an important survival strategy for agrotechnologytransfer agencies. Categorization meansorganizing farmers according to similar farmingpatterns and socio-cultural interest for the purpose of transferring agricultural technologies that meettheir specific needs. Other areas where the ADP differed from university include provision of trainingincentives (t = 3.33) and field agents’ knowledge of rural dynamics (t = 2.71).ANALYSIS AND COMPARISON OF THE AGRICULTURAL DEVELOPMENT PROGRAMME AND UNIVERSITYAGRICULTURAL ... NIGERIA 29The university system (0 = 3.42) provided higher training incentives to field staff than the ADP (0 = 3.39)and the ADP staff (4.16) had better knowledge of rural dynamics than the university (x = 3.37). Thus, itis suggested that the university system takes complete responsibility for extension staff training, whilethe ADP utilize their rural orientation and concentrate efforts to contact the farmers. In this regard, theuniversity should strengthen their training arrangement and facilities and the ADP should improve onsponsorship of staff training, and payment of necessary incentives to the field staff.Comparison of the socio-economic indices of the ADP and university agro- technology transfersystemsComparison of the socio-economic impacts of the ADP and university agro-technology transfer systems

on the organizational, staff and farmer characteristic was carried out using socio-economic indices(Tables 3 and 4).Organizational characteristics: The ADP had a supervisory to field staff ratio of 1: 8, compared to 1:6 for the university. The university will make more effective supervision of field staff with the smallernumber of field extension staff. The field staff farmer ratio was 1: 200 for the university as against 1:5000 for the ADP.Field staff of ADP move through four supervisory levels to get in touch with the head of the programme,while the university counterpart has a direct link with the head of the programme. The more the supervisorylevels, the longer the chains of communication and the more relevant agro-technology informationcould be diluted and distorted between source and end users. Similarly, the university has less outsideinterference with the organizational procedure and process than the ADP. The university had a strongerlinkage between the agro-technology generation and transfer sub-systems (0 = 4.60) than the ADP (0=2.56).This situation from the perception of the operators of the two systems is based on factors such as thephysical distance between the sub-systems, the age (that is the period of existence of the sub-systems),differences in the qualification of the staff of the sub-systems, and the information technology facilitiesavailable for information exchange between the sub-systems. The greater the physical distance betweenthe two sub-systems, the less the level of linkage. Again, the more the differences in age and staffqualifications, the less the differences in information technology between the sub-systems and the

level of linkage. Linkage between technology generation and transfer sub-systems has been identifiedas a necessary ingredient for success in technology transfer.The agro-technologies transferred and method of transfer used by the university was more compatiblewith the cultural practices of the recipient environment than that of the ADP. Understanding the needsand aspirations of technology recipients is a basic ingredient not only in developing technologiesappropriate to them, but choosing appropriate methods for transferring such technology to them. Theuniversity with better trained and experienced technology transfer staff appears better equipped tohandle the intricate process of identifying the needs and aspirations of farmers. Again majority of ADP30 ATPSWORKING PAPER SERIES NO. 35farmers (87.6%) reported that the ADP system was directed mostly to adults, and that of the universityincluded youths in their programmes.The agro-technologies transferred by the two systems showed a wider distribution involving crops(23.2%), livestock (19.3%), processing (18.7%) agro-forestry (17.5%) and fisheries (21.2%) for ADP,than the university with a distribution of crops (40.1%), livestock (29.1%) and processing (30.7%). TheADP transferred crop based technologies in the area of yam/maize/cassava/egusi or telferia alternaterow intercrop, cassava, rice, maize, sweetpotato and cowpea and the university concentrated on cassava,rice, maize and cowpea. In the livestock area the university concentrated on poultry and cattle and theADP worked on poultry, cattle, sheep and goat. Most of the universities did not transfer technologies onagro-forestry and fisheries.

In terms of intra-organizational relationship among staff, 63.16% of university, compared with 55.94%of ADP staff, participated in intra-organizational relationship. Intra-organizational relationship patternsof staff are of two forms: vertical which takes place between superior and subordinate and horizontal,which takes place between staff at the same supervisory level. The university had higher intraorganizationalrelationship than the ADP. Also 42.30% of ADP and 36.05% of university staff weremobile, indicating low level of staff mobility in the two systems. Mobility of technology transfer staffenhances timeliness in implementing agro-technology transfer programmes. The analysis further showsthat 17.83% of the ADP and 25.81% of university top management staff received in-house or externaltraining, sponsored by their agencies. Under the ADP system, the field agents had regular in-housetraining, mainly the fortnightly training sessions. In contrast, the field extension staff of the university didnot have similar regular staff training on production recommendations. Adequate staff training hadbeen identified as an enabling factor towards achieving the success of any agricultural technologytransfer system (Swanson, 1997).In terms of cost of providing staff training, the ADP spent Naira (N)6,270 compared with university,which spent N4,677 per staff a year. We recommend that the ADP could leave training to the universitydue to the comparative advantage of university in the area.Staff characteristics: Majority of the university (89.5%) and ADP (89.34%) agro-technology transferworkers were males. This indicates inadequate female agro-technology transfer workers in the two

systems. This may bias agro technology transfer efforts toward male farmers, when 70% of farmers inNigeria are females (Anyanwu and Agu, 1996). Inadequate female agro-technology transfer agentshave been identified as a limiting factor in transferring agro-technology to female clientele (Sokoya,1998).The majority of university staff (53%) and ADP staff (51%) were between 40 and 48 years old, and thenext major group, 30% for university and 18% for ADP were 49-59 years old. The university had relativelyolder staff than the ADP. Similarly, 66% of staff of university had work experience of between 16 and 30years and 60% of ADP staff had work experience of 6 and 25 years, the latter being a relatively young/recent agency than the university. The few years of work experience in the ADP could also be a resultANALYSIS AND COMPARISON OF THE AGRICULTURAL DEVELOPMENT PROGRAMME AND UNIVERSITYAGRICULTURAL ... NIGERIA 31of staff turnover caused by poor work condition. The result indicates that agro-technology transfer staffof ADP and university had at least the West African School Certificate, that is 12 years of basic education.About 89% of university and 82% of ADP staff had at least a university bachelors degree. The indicationis that staff of the two agro-technology transfer systems possessed relevant educational qualificationfor achieving the objectives of agro-technology transfer programmes.Selected socio-economic characteristics of agro-technology transfer staff of the ADP and university arepresented in Table 3. The Table shows that a higher percentage of staff of the ADP than the university,owned a personal house, an electricity generating plant and had a better knowledge of rural life.

Ownership of a personal house and generating set, is a reflection of the external funding facility whichADP had, prior to this study. However, the superior knowledge of rural life better equips ADP staff formore effective performance as rural agro-technology transfer agents. Again a higher percentage ofuniversity staff more than the ADP were classified as having improved nutritional status, owned radioand television, were free from superstitious beliefs, and had additional academic qualification, betterpromotional prospect and higher technical skills.Generally, the university system appears to have more positive impact on the socio-economiccharacteristics of staff than the ADP. The implication is that the university will retain high quality agrotechnologytransfer staff than the ADP, as it offers better conditions of service.Table 3: Socio-economic indices of agro-technology staff in the ADP and university systemSocio-economic indices ADP (%) University (%)Own personal house 34.10* -Improved nutritional status 30.67 49.26Electricity generating plant 1.64 -Radio/television 60.33 86.84Furnished parlour and bedroom 38.20 40.33Positive attitude towards jobs 42.11 46.72Freedom from superstition 22.95 36.84Improved knowledge of rural life 85.41 48.95Additional academic qualification 18.20 41.05Promotional prospects 47.54 80.11Higher technical skills 57.89 70.49* Multiple responsesFarmer characteristics: Majority of the university (84.3%) and ADP (92.17%) farmers were malesindicating bias of the two agro-technology transfer systems against women.

The majority of farmers with the university (86%) and ADP (78%) were in the active age group of 40 to60 years. Years of contact of farmers with agro-technology transfer agencies ranged from 1 to 15 for32 ATPSWORKING PAPER SERIES NO. 35the bulk of ADP farmers (73.2%) and 6-20 years for the bulk of university farmers (76%). This indicatesthat farmers with the university system had longer period of exposure to technology transfer influencethan farmers with the ADP system. The university system served mostly farmers without any formaleducation (64%) more than the ADP (40%), which served mostly literate farmers.Table 4 shows that a comparatively higher percentage of farmers under the ADP own personal houses(75.76%), used modern agricultural equipment (71.79%), were mobile (69.39%), paid their tax (85.29%)and possessed positive attitude towards agro-technology transfer (78.26%).Table 4: Socio-economic indices of farmers under the agro-technology transfer systems of ADPand universitySocio-economic indices ADP (%) University (%)Furnished personal house(s) 75.76* 54.55Wrist, table or wall clocks 72.45 42.29Radio & T.V. 87.32 76.67Accessibility to pipe-borne water 45.16 52.94Use of modern agricultural equipment 71.79 53.33Mobility facilities (cars,motorcycles or bicycles) 69.39 55.32Better nutritional statuses 97.02 93.04Membership of farmers organisations 77.20 89.17Access to farm inputs 74.60 86.01Prompt payment of tax 85.39 79.13Accessibility to modern health care 54.31 73.04

Freedom from superstition 70.49 69.61Positive attitude towardsagro-technology transfer services 78.26 42.16Cultivated additional 0.2-0.5 ha in thelast five years 63.00 100.0* Multiple responses.A higher percentage of farmers under the university had access to piped water (52.94%), were membersof farmers’ organizations (89.17%), had access to farm inputs (86.01%), modern health services(73.04%), and in the immediate past five years cultivated additional 0.2 to 0.5ha. of farm land (100%).Farmers’ use of agricultural technology packagesMean scores were used to determine the extent farmers employed technical packages given to them intheir farm operations. Data in Table 5 show that ADP farmers (0 = 4.22) compared to the universityfarmers (0 = 4.39), generally used crop based technologies, while the university farmers (0 = 3.93)ANALYSIS AND COMPARISON OF THE AGRICULTURAL DEVELOPMENT PROGRAMME AND UNIVERSITYAGRICULTURAL ... NIGERIA 33compared to the ADP farmer (x = 4.12), used less of livestock technologies. The analysis indicates thatthe bulk of farmers who participated in the activities of the ADP and university, generally used crop andlivestock based technologies in their farm operations.Table 5: Farmers’ level of use of agricultural technology packages_______________________________________________________________________Agriculture sub-sector ADP UniversityMean (max.=5)Improved crops technologies 4.22 4.39Improved livestock technologies 4.12 3.93Fisheries 4.48 1.43

Agro-forestry 3.05 1.02Use of agro-chemicals 3.46 3.71Storage, processing and utilization technologies 4.10 4.17________________________________________________________________________Furthermore, the ADP farmers almost had monopoly in the area of fisheries (0 = 4.48) and agro-forestry(0 = 3.05) based technologies. Other areas where agro-technology packages were utilized and agrochemicalshad means of 3.46 for the ADP and 3.71 for the university farmers and processing andutilization with mean of 4.17 for the university, compared to the mean of 4.10 for the ADP farmers.Farmers of the university better adopted the use of agro-chemicals, processing and utilizationtechnologies than farmers of the ADP.Farmer-contact methods of the ADP and universityData in Table 6 show the percentage of farmers reporting contact methods adopted by the agro-technologytransfer systems of ADP and university. The analysis indicates that ADP used more of personal contactmethod (78.15%) than the university (63.13). The ADP (62.17) and university (64.05) systems, generallyused the demonstration method. Demonstration technique adopted use of trial plots to concretizedevelopment of necessary skills among the farmers. Comparatively, the ADP performed better than theuniversity in the use of personal contact method, agricultural shows and field days, and the universityused demonstration, rural groups and posters as contact method with farmers. The higher the use ofdemonstration and personal contacts by field workers, the greater the achievement of any agrotechnologytransfer system in securing increased awareness, interest and participation of farmers in

agro-technology transfer practices.34 ATPSWORKING PAPER SERIES NO. 35Table 6: Farmers’ perception of contact methods used by the ADP and universityExtension contact methods ADP (%) University (%)______________________________________________________________________Personal contacts of extension agents 78.15* 63.13Demonstration 62.17 64.05Agricultural shows 44.25 31.37Field days 52.05 29.32Involvement of farmer organizations andrural groups 50.17 60.16Use of posters 28.16 39.05Use of radio 9.45 10.06Use of television 7.06 6.15______________________________________________________________________*Multiple responsesAbout 10% of university farmers and 9.45% of ADP farmers reported use of radio and 7.06% of ADPand 6.15% of university farmers indicated use of television as contact methods. The two systems didnot use radio and television as major methods of agro-technology transfer. Radio and television havehigh potential for contacts, because of their suitability to reach a large number of farmers simultaneouslyand disseminate urgent farm programmes (Anyanwu, 1997). However, the minimal use of radio andtelevision by the ADP and university conformed with the expectation of Osuji (1983), who noted thatradio and television were the least used extension-farmer contact techniques in Nigeria.This study comparatively analysed three sub-systems necessary in implementing a viable agricultural

technology transfer system, namely, technology generation, transfer and utilization of the ADP anduniversity in Nigeria. There is a consensus from the study that the agro-technology transfer systems ofADP and university could be accredited with achievement in terms of set goals and operational targets.However, these agencies have not been supported by coherent and targeted agro-technology transferpolicies. Harmonization of field technology transfer services based on comparative advantages, isrequired to achieve a functional agro-technology system in Nigeria. The frequency of the agro-technologytransfer activities re-located through earlier organizations to the present ADP, and the number of otherorganizations that have been called in to undertake agro-technology transfer activities as part of theirmandate, has decreased. This is a reflection of the unstable nature of the environment in which agrotechnologytransfer activities have operated in Nigeria. These changes usually resulted in the movementof staff from one agency to another and in some cases in loss of status and prospect for careerdevelopment. The university system has had a relatively stable environment with little interference fromoutside. Based on the analysis, one possible policy option to pursue will be to foster a loose linkagebetween the two agro-technology transfer systems, such that the university will concentrate on technologydesign and supply, and the ADP as the implementing arm in the agro-technology transfer process(Figure 6).ANALYSIS AND COMPARISON OF THE AGRICULTURAL DEVELOPMENT PROGRAMME AND UNIVERSITYAGRICULTURAL ... NIGERIA 35

Another policy option will be to merge the two systems and situate all government agro-technologytransfer efforts in the county within the university system ( Figure 7). To pursue this option, we suggestthat one university in each state of the federation be designated as an agro-technology transfer centre.With this option, agro-technology transfer staff will become staff of the university responsible for agrotechnologytransfer in each state of the federation. This arrangement will allow agro-technology transferstaff to enjoy the relatively better condition of service existing in the university. This may help to increasemorale, job satisfaction and reduce staff turn-over. With this option, the federal state and localgovernments can contribute funds and programmes for transfer activities.Based on the findings of this study the following policy issues are critical in achieving success, irrespectiveof the options considered. The university should utilize the advantage of better quality research personneland facilities, to address appropriate technology generation. The crucial technology generation roles ofthe university could be enhanced by utilizing high staff strength of the ADP in identifying field problems.This could be achieved by constituting the field reports of ADP agro-technology transfer workers intocritical inputs for basic research and improving of extension staff training on adaptive researchmanagement. The ADP had more field staff evenly distributed than the university and we recommendthat ADP takes over responsibility for field agro-technology transfer activities. This will include identificationof farmers’ problem and adaptive research trials in farmers’ field. The university in turn could absorb the

ADP as their implementing arm, while concentrating on technology design and supply services andlinking with other research institutes on behalf of the ADP.To take over agro-technology transfer at farmers’ level, ADP should identify existing farmers’ field problemsand subsequently implement adaptation trials and pursue enhanced training of field staff. Consideringthe comparative advantage of university over the ADP in terms of training facilities, qualities of trainingpersonnel and payment of incentives to staff, an agro-technology transfer policy that will allow theuniversity to take over all staff training functions should be pursued.The ADP should concentrate on increasing sponsorship of staff for training and improving the paymentof necessary incentives to staff after training. There will be need to strengthen staff training arrangementof the universities to meet staff training needs. Effective extension staff training under the universities,demands appropriate decentralization and adoption of the zonal and block office arrangement of theADPs in providing extension staff training. The situation could imply improved logistic support for stafftraining and increased budgetary allocation to extension, in order to enhance payment of trainingincentives to trainees.The gender bias in staffing against women is a serious shortfall of the two systems. This bias againstwomen is also manifested among farmers. There is need to pursue a policy that will substantiallyincrease the number and quality of female agro-technology transfer staff in two systems. This will beone major way of ensuring that the majority of farmers in Nigeria, mainly female, are reached. Similarly,there is need for a policy that will make it mandatory for agro-technology transfer institutions and systems

to specifically target their programmes on women.36The ADP should evolve an arrangement for using multiple farmer contact methods. Use of group approachand employment of existing rural communication patterns are policy options that should be pursued.This would enhance effective contact and facilitate farmers’ participation in agro-technology transferservices of the ADP.Examined as an agro-technology system, we observe that the linkage between technology generationand technology transfer sub-systems was weak in the system and strong in the university system. TheADP, as an agro-technology transfer system is a relatively younger organization, compared with thecooperating technology generating agencies. Most of the research agencies generating agro-technologyfor it were established in the 1960s and the cooperating ADPs were established in the 1980s. Ourobservation points to the difference in age of the agencies as an important issue that reduced cooperationbetween the sub-systems. The research agencies perceived the ADP as a relatively young and inferioragency to deal with. Consequently, its capability as an agro-technology transfer system to meet withthe challenges of establishing new inter-organizational relationship with agro-research agencies, wasabsent.In the university system which showed a stronger link between the technology generation and transfersub-systems, this difference in age did not exist.Another policy issue which this study is highlighting is the academic qualification differential existingbetween the two sub-systems under the ADP. Most of the research staff had at least a masters degree

and most of the ADP staff had at most a bachelors degree certificate. Most of the technology-generatingstaff in the cooperating research agencies had comparatively higher academic qualification thantechnology transfer staff. Most of the ADP staff were apathetic in dealing with the research staff. TheChapter FiveConclusion and Policy IssuesANALYSIS AND COMPARISON OF THE AGRICULTURAL DEVELOPMENT PROGRAMME AND UNIVERSITYAGRICULTURAL ... NIGERIA 37Figure 6: A proposed linkage structure for university and ADP in agro-technology transfer inNigeria.RESEARCHINSTITUTESUNIVERSITYADPFARMERSAgro-technologygenerationAgro-technologytransfer38 ATPSWORKING PAPER SERIES NO. 35ADP staff complained that the research staff see and treat them as people without knowledge. Thus, indeveloping an agro-technology transfer system the academic qualifications of the staff involved intechnology generating and transfer sub-systems, should be harmonized.One other policy issue that played a role in weakening the link between the technology generation andtransfer sub-systems of the ADP was the difference or non-synchronization in the period of funding.The ADP came into existence with liberal external funding from the World Bank at a time when the

structural adjustment programme was adversely affecting the capability of the research institutes togenerate agro- technology. This set off balance its agro-technology system. A holistic approach todeveloping or restructuring an agro-technology system, rather than dealing with each sub-system is animportant policy option. The growing knowledge-intensity of agro-production of rural farm level shouldbe complemented by agro-technology generating and transfer sub-systems or institutions.ANALYSIS AND COMPARISON OF THE AGRICULTURAL DEVELOPMENT PROGRAMME AND UNIVERSITYAGRICULTURAL ... NIGERIA 39Figure 7: Proposed merge structure for university and ADP in agro-technology transfer in Nigeria.RESEARCHINSTITUTEUNIVERSITYFARMERSAgro-technologyGeneration andTransfer40Adebayo, A. (1995). Principles and Practice of Public Administration in Nigeria; Revised edition; Ibadan:Spectrum Books Ltd., pp. 18-27.Agwunobi, C.A. (1993). “Impact of the Shell Petroleum Agricultural Extension Programme on theParticipating Farmers in Imo State”. M.Sc. Project, Department of Agricultural Extension, University ofNigeria, Nsukka, Nigeria.Aihonsu, J.O.I. (1992). “Group Farming Approach to Food Production and Rural Development: theExperience of Opticom Farm Scheme in Ogun State, Nigeria”. In Rural Development in Nigeria:

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Extension: A Reference Manual; B.E. Swanson; R.P. Bentz and A.J. Sofranko eds., Food and AgriculturalOrganization of the United Nations, Rome, pp. 171-180.Swanson, B.E. and Claar, B.J. (1983). Technology Development Transfer and Feedback SystemsAnalysis, University of Illinois, Illinois, Interparks.Titilola, T. (1994). “Knowledge System and Sustainable Agricultural Development in Africa: EssentialLinkages”. Indigenous knowledge and Development Monitor , Vol. 2, No, pp. 18-20.Uwakah, C.T. (1985). The Agricultural Extension Approach to Rural Development in West Africa. Universityof Nigeria, Nsukka, Nigeria, No.2, August, pp. 27-36.Van den Ban, A.W. and Hawkins, H.S. (1992). Agricultural Extension, Second edition. AgriculturalUniversity, The Netherlands, pp.7-41.Vengara, N.T. and McDicken, K.G. (1990). “Extension and Agro-Forestry Technology Delivery toFarmers”. In Agro-Forestry Classifications and Managements; K.G. McDicken and N.T. Vengara eds.,Bangkok, Thailand.World Bank (1994). Agricultural Extension in Africa: African Technical Development Series, World Bank,Washington D.C., USA.Zaria, M.B; Arokoyo, J.O.; Omotayo, A.M. and Akpoko, J.E. (1994). “Extension Issues and Prioritiesfrom a Multi-Sectoral Perspective; Issues and Priorities for Nigeria’s Agricultural Extension in the Twenty-First Century. Proceedings of the Inaugural Conference of the Agricultural Extension Society of Nigeria,Nigeria, pp. 89-95.

Bulgarian Journal of Agricultural Science, 15 (No 2) 2009, 146-153Agricultural Academy

COMPARISON OF USE OF IMPROVED AGRICULTURAL PRACTICESBY CONTACT AND NON-CONTACT FARMERS IN KWARA STATE,NIGERIAB. M. MATANMI and G. B. ADESIJIDepartment of Agricultural Extension and Rural Development, University of Ilorin,Ilorin, Kwara State, NigeriaAbstractMATANMI, B. M. and G. B. ADESIJI, 2009. Comparison of use of improved agricultural practices by contactand non-contact farmers in Kwara state, Nigeria. Bulg. J. Agric. Sci., 15: 146-153The study compared the use of improve agricultural practices between the contact and non-contact farmersin Kwara State, Nigeria. A three-stage sampling technique was used in the selection of 189 contact and 163 noncontactfarmers for the study. The data was analyzed with the use of simple descriptive statistics such as frequencycounts and percentages. The findings showed that majority of contact (93.2%) and non- contact (95.7%)farmers were males and also 98.9% contact farmers and 100.0% non-contact farmers were married. The resultsfurther revealed that more than half (58.3%) of the contact farmers and non- contact farmers (52.6%) werebetween 45 and 60 years percentage of the contact farmers that have no formal education is smaller (39.8%)than non-contact farmers (64.0%). The result showed that 22 improved agricultural practices have been introducedinto the state before the study was carried out. These were categorized into seven based practices. Thestudy further showed that contact farmers used more of the improved agricultural practices than non-contact

farmers and there were significant differences in their use of these improved agricultural practices except infisheries. It was therefore recommended that the contact farmer approach to agricultural information disseminationshould continue. However, there is the need to periodically re-evaluate the performance of the contactfarmers and make the needed changes or replacement of those who are not performing to expectations. Also anagricultural extension policy that adhere strictly to the criteria for the selection of contact farmers laid down bythe Kwara Agricultural Development Project (ADP) should be followed strictly.Key words: comparison, use, agricultural practices, contact farmers and non-contact farmers, Kwara ADPE-mail: drgbolaadesiji@yahoo.comIntroductionRural development has been approached frommany perspectives: political, industrial, economic andagricultural. Also, Nigerian government over time hadinstituted various programmes and policies to increaseagricultural productivity Most of such programmes hadbeen scrapped due to their failure in achieving setobjectives but out of the existing few programmes,the Agricultural Development Programme (ADP) however,possesses a high prominence and state-wide status(Olarinde et al., 2005). It is one of such approaches146to rural development. The need to improve agriculturalproduction and rural income led to its establishmentin 1975 to break the barriers to agricultural developmentand more importantly, to meet the needsof the small-holders and rural farmers (Fasoranti,2006).The Training and Visit Extension System was introducedinto Agricultural Development Project to be

the main medium of communicating agricultural informationto the farmers and also for the Training of ExtensionStaff. The Training and Visit Extension Systemhas been in operation in Kwara State since 1988when Ilorin Agricultural Development Project wentstate-wide (MANR, 1988).It is a well known fact that the critical function ofagricultural extension is to enhance the diffusion ofagricultural innovations generated from research, andmore often, the success of an extension program isassociated with the level of adoption of recommendedagricultural innovations.A very important component of the Training andVisit Extension System is the contact farmer. Frequentcontact between a Village Extension Agent(VEA) and all farmers in his circle is not possible.Instead, while being responsible, to all farmers, oneach forthrightly visit the VEA focuses on a small, selectednumbers of farmers “contact farmers” in eachfarmer’s group” and meets with any other farmers whoare willing and interested to attend his visits and seekhis advice. Benor and Baxter (1984) contact farmersare selected according to the following characteristicsBenor and Baxter (1984):·They should represent proportionately the mainsocio-economic and farming conditions of their groupand be regarded by other farmers as able and worthyof limitation;·They should be practicing farmers;·They should be willing to adopt relevant recommendationson at least a part of their land, and allowother farmers to observe the practices, and explainthe practices to them;·As far as the size and composition of farmers’groups permits, they should come from different families;

and·Their farms should be dispersed throughout thegroup area. Tenants, share croppers, young farmers,and women farmers may be contact farmers if theypossess these characteristics. No major type of farmershould be over or under-represented among the contactfarmers of a group. Once a contact farmer becomesdisinterested in the work of the VEA or becomesin other ways ineffective, he should be replaced.In his work on the Training and Visit in Somalia,Chapman (1987) reported an overall adoption rateof around 60% for contact farmers and 26% for fellowfarmers, after four years of extension activities inthree key regions. Khan et al. (1984) reported thatyields obtained by contact farmers in cotton, what,rice, maize and groundnut were higher than those ofnon-contact farmers in project and non-project farmers,while yield difference was significant betweencontact and non-contact farmers for cotton, it wasnot significant for other crops. In Tanzania, Due et al.(1987) found a significant difference in yields betweencontact and non-contact farmers, female headed andnon T and V farmers’ yields per hectare of maize1648,914,837 and 618kg respectively. In Nigeria,Windapo (2002) found that contact farmers weremore aware of maize and Cassava technology recommendedpractices than non-contact farmers. Theywere also more knowledgeable than non-contact farmersin terms of the recommendations since they aremore aware and more knowledgeable; they are alsomore accurate at implementation of recommendations.The objectives of this study are to:· Determine the personal characteristics of contactand non-contact farmers;· Identify the improved agricultural practices introduced

into the KwADP;· Determine the use of improved agricultural practicesby the contact and non-contact farmers in KwaraState Agricultural Development Project.HypothesisThere is no significant difference in the use of selectedimproved Agricultural practices (crop varieties,land preparation, agro-chemicals, animal rearing,tree fruits, soya products and use of fisheries) by contactand non-contact farmers.Comparison of Use of Improved Agricultural Practices by Contact and Non-Contact.... 147MethodologyThe study was carried out in Kwara State of Nigeria.Kwara State came into existence on 2nd May,1967 when the country was split into twelve states bythe Federal Military Government headed by MajorGeneral Yakubu Gowon. Initially the state was calledCentral West State, but was later changed to “Kwara”a name derived from the local name of the River Nigerin some parts of the State. The state was carved outof the defunct Ilorin and Kabba provinces (The Herald,Jan, 30, 2002). The unit of analysis was (1) contactand (2) non-contact farmers. A three-stage samplingtechnique was used in the selection of zones,blocks, cells and villages for the study. There are fourzones in Kwara State ADP namely: Zone A hasKalama as the Zonal Headquarters, Zone B has Pategias the Zonal Headquarters, Zone C has Malete andZone D has Igbaja as Zonal Headquarters respectively.A total of 189 contact farmers were selectedfrom the list of contact farmers with the Kwara AgriculturalDevelopment Project while a total of 163 noncontactfarmers was selected using systematic randomsample of selecting every 5th house in the selected

cells and villages for the study. Variables thatwere measured in the study were improved agriculturalpractices introduced into Kwara ADP and theuse of improved agricultural practices by the contactand non-contact farmers. It was discovered that about22 improved agricultural practices have been introducedinto the ADP before the study was carried out.These were categorized into seven namely: Improvedcrop varieties, improved land preparation, use of agrochemicals,and use of animal rearing, tree fruits, soyaproducts and fisheries.Use of improved agricultural practices was measuredby assigning O for No answer and 1 for yesresponse. The data was analyzed using frequencycounts and percentages to compare the responses ofthe contact and non-contact farmers.Results and DiscussionCharacteristics of the RespondentsOn Table 1 the general characteristics of the contactand non-contact farmers are presented: The tableshows that more than half (58.3%) of the contact farmersand non- contact farmers (52.6%) were between45 and 60 years. This is similar to the result ofWindapo (2002) who found that most of the contactand contact farmers are middle aged in Oyo agriculturaldevelopment programme. About 93.2% of thecontact and 95.7% of the non-contact farmers weremales. Majority of contact farmers (about 60.20%)had some level of formal education. On the other hand,about 64.0% of the non-contact farmers were withoutformal education.These results have an implication on the disparitybetween the adoptions of innovations such as improvedseeds, modern farming practices etc. by thecontact and non-contact. They also have implications

on their productivity (Nasko, 1990). Most of the contact(98.9) and non-contact (100.0) farmers weremarried but 1.1%of the contact farmers were divorced.Results further show that 78.6% of the contact and80.3% of non-contact farmers had between 1-2 wiveswhile 21.4% of the contact farmers and 19.7% of thenon contact farmers had 3-4 wives. Less than onethird of the contact farmers (26.6%) and non-contactfarmers (28.8%) were small sized farmers with lessthan 2 hectares farm size while more than one third(contact farmers-40.2%, and 33.6% non-contactfarmers) had between 2 to 5 hectares. The result alsoshows that 28.4% of contact farmers had less than25 years of farming experience, while it is 36.6% fornon-contact farmers. It also shows that 48.4% ofcontact farmers had between 25-40 years of farmingexperience, but it is 34.8% for non-contact farmers.There are 23.2% of contact farmers with over 40 yearsof farming experience while it is 28.6% for non-contactfarmers.Improved Agricultural PracticesIntroduced into Kwara ADPResults in Table 2 show the improved agriculturalpractices introduced into Kwara Agricultural DevelopmentProject as at the time of this study. The tableshows that about twenty-two improved agriculturalpractices have been introduced into the ADP. These148 B. M. Matanmi and G. B. Adesijitwenty-two improved agricultural practices were asfollows: Improved maize, improve cassava, improvedcowpea, improve rice, improve yam, tractor plugging,animal plugging, see dressing, insecticides, fungicides,herbicides, fertilizer, grain storage, animal vaccination,goat rearing, sheep rearing, poultry keeping, citrusgrowing, cashew growing, soya beans milk, soya

beans cheese, fish keeping.These twenty-two improved agricultural practiceswere categorized into seven based on their similarityin usage, as shown on Table 2.Use of Improved Agricultural Practicesby RespondentsThe results in Table 3 show the use of improvedagricultural practices by contact and non-contactComparison of Use of Improved Agricultural Practices by Contact and Non-Contact.... 149Frequency % Frequency %Age (in years)<45 26 14 31 20.145-60 109 58.3 81 52.6>60 52 27.8 42 27.3SexMale 177 93.2 154 95.7Female 13 6.8 7 4.3Marital statusSingle - - - -Married 189 98.9 161 100Divorced 2 1.1 - -No of wives1-2 136 78.6 118 80.33-4 37 21.4 29 19.7Educ. LevelsNo formal Edu. 76 39.8 103 64Adult/Arab Edu 61 31.9 29 18Primary Edu. 40 20.9 14 8.7Secondary Edu. 10 5.3 7 4.4Tertiary 4 2.1 8 4.9Farm size(Ha)<2 49 26.6 42 28.82-5 74 40.2 49 33.6>5 61 33.2 55 37.7

Farming Exp.<25 years 54 28.4 59 36.625-40 92 48.4 56 34.8>40 44 23.2 46 28.6Source: Field survey: 2007Contact farmers Non-contact farmersTable 1Characteristics of the Contact and Non- Contact FarmersCharacteristicsfarmers in Kwara ADP. Farmers who used at leastone of the improved agricultural practices in each categorywere regarded to have used improved agriculturalpractices. Farmers who did not use any of theimproved agricultural practices in each category wereregarded as not using. As can be seen in Table 2,about 87.5% of contact farmers used improved cropsvarieties compared with 84.5% for non-contact farmers.The table shows that a high proportion of both thecontact and non-contact farmers used improved cropvarieties. This shows that the T and V extension systemhas been able to push to farmers in Kwara ADPimproved crop varieties over the years.Results further showed that 44.5% of the contactfarmers used improved land preparation while 55.5%did not use improved land preparation. Also 45.8%of NCF used improved land preparation while 54.2%did not use it. The data showed that a high percentageof both groups of farmers did not use improvedland. This showed that improved land preparation oftractor plugging and animal plugging, is not very popularin Kwara ADP. This implied that the T and Vextension has not been able to push this improvedagricultural practices to the farmers.Results in Table 3 further showed that a high percentageof contact and non-contact farmers used

Agro-Chemical in their farming operations. About87.1% for contact and 85.1% for NCF respectivelyused Agro-Chemicals. As for animal rearing a highpercentage of contact farmers 87.1% used animal,rearing compared to 13.1% for non-contact farmers.With regards to use of Tree fruits, about 74.7% noncontactfarmers used Tree fruits compared with 23.4%contact farmers. This finding is surprising because onewould expect a high percentage of contact farmers touse tree fruits than non-contact farmers; as for soyaproducts 71.5% of contact farmers used soya productcompared with 63.5% for NCF. Finally, 32.6%of contact farmers used Fisheries compared with30.5% for non-contact farmers. It can be seen thatFisheries even though it has been pushed through theT and V is not very popular in Kwara State.Testing of HypothesisThere was a major working hypothesis set for thisstudy: There is no significant difference in the use ofselected improved Agricultural practices by contactand non-contact farmers.Data in Table 4 is a result of the t- test analysis to150 B. M. Matanmi and G. B. AdesijiS/No. Categorization of improvedagricultural practices Improved аgricultural practices1 Improved Crop Varieties2 Improved land preparation Tractor plugging and animal plugging3 Agro-Chemical usage4 Animal rearing5 Tree fruits Citrus growing, and Cashew growing6 Soya products Soya milk and Soya beans cheese7 Fisheries Fish keepingSource: Field Survey (2007)Table 2Improved agricultural practices introduced into Kwara ADP

Improved Maize, improved Cassava,improved Cowpea, improved Rice,and improved YamSeed dressing, use of insecticides, fungicides,herbicides, chemical storage and fertilizerusageAnimal vaccination, goat rearing, sheeprearing, and poultry keepingshow whether there is significant difference in the useof selected improved Agricultural practices betweencontact and non-contact farmers.There were seven improved agricultural practices(crop varieties, land preparation, agro-chemicals, animalrearing, tree fruits, soya products and use of fisheries)considered. Out of all the practices, six showedsignificant differences. These included crop varieties,land preparation, agro-chemicals, animal rearing, treefruits and soya products. The values were as follows:crop varieties (t=3.913, p=0.00), land preparation(t=3.903, p=0.00), agro-chemicals (t=5.084,p=0.00), animal rearing (t=3.996, p=0.00), tree fruits(t=5.011, p=0.00) and soya products (t=5.062,p=0.00). All these were as a result of the fact thatcontact farmers generally first use new agriculturalComparison of Use of Improved Agricultural Practices by Contact and Non-Contact.... 151No. % No. %a Use of improved crop VarietiesYes 165 87.3 136 84.5No 24 12.7 25 15.5Total 189 100 161 100b Use of improved land preparationYes 77 44.5 71 45.8No 96 55.5 84 54.2Total 173 100 155 100

c Use of Agro-ChemicalYes 162 87.1 137 85.1No 24 12.9 24 14.9Total 186 100 161 100d Use of Animal rearingYes 162 87.1 21 13.1No 24 12.9 139 86.9Total 186 100 160 100e Use of Tree FruitsYes 141 23.4 118 74.7No 43 76.6 40 25.3Total 184 100 158 100f Use of Soya ProductsYes 133 71.5 101 63.5No 53 28.5 58 36.5Total 186 100 159 100g Use of FisheriesYes 59 32.6 45 30.5No 122 67.4 104 69.5Total 181 100 149 100Source: Field Survey (2007)C.F. N.C.F.Table 3Use of improved аgricultural practices by respondentsImproved agricultural practicespractices. Use of fisheries did not show any significantdifference (t=0.420, p=0.675).ConclusionThe study revealed that the percentage of respondentsthat used improved agricultural practices is higherfor contact farmers than that of the non-contact farmers(except for improved land preparation) and therewere significant differences in their use of these improvedagricultural practices except in fisheries .Thefindings also showed that the percentage of the contact

farmers that have no formal education is smaller,about 39.8% and this contributed to their easy acceptabilityof the new technologies while for the noncontactfarmers the percentage of those that have noformal education is higher, about 64.0%. The contactfarmer concept is an important factor in the Trainingand Visit Extension System and in the interface betweenagricultural technology generation and dissemination.Effective dissemination of generated agriculturaltechnology has remained an intractable problemin Nigeria’s agricultural extension efforts. The use ofcontact farmer as a link between the extension agencyand the farming population has been in practice forover a decade in Kwara State. The over all effectivenessof the agricultural information dissemination processwill depend primarily on who was selected toserve as a contact farmer. It is therefore recommendedthat the con tact farmer approach to agricultural informationdissemination should continue. However, thereis the need to periodically re-evaluate the performanceof contact farmers and make the needed changes orreplacements of those who are not performing of expectation.An agricultural extension policy that adheresstrictly to the criteria for the selection of contactfarmers laid down by the ADP should be followedstrictly.ReferencesBenor, D. and M. Baxter, 1984. Training and VisitExtension. Washington D.C. The World Bank.Chapman, M. P., 1987. The Evolution of Training andVisit in Somalia. Agricultural Administration andExtension, Elsevier Applied Science Publishers,22: 151-163.Due, J. M., N. Mollel and V. Malone, 1987. Doesthe T and V System Reach female – headed families?

Some evidence from Tanzania, AgriculturalAdministration and Extension, 26: 209-217.Fasoranti, O. O., 2006. Impact of Agricultural DevelopmentProgramme (ADP) on the Quality ofSocial Existence of Rural Dwellers in DevelopingEconomy: Ondo State ADP Experience. InternationalJournal of Rural Management, London,pp. 213-227.Khan, M., J. Sharif and M. Sarwar, 1984. Monitoringand Evaluation of Training and Visit System ofAgricultural Extension in Punjab, Pakistan, Publ. No152 B. M. Matanmi and G. B. AdesijiImproved practices t-value Significant difference RemarkCrop varieties 3.913 0 SignificantLand preparation 3.903 0 SignificantAgro-chemicals 5.084 0 SignificantAnimal rearing 3.996 0 SignificantTree fruits 5.011 0 SignificantSoya Products 5.062 0 SignificantFisheries 0.42 0.675 Non- SignificantTable 4T-test for equality of means between the contact and non-contact farmersSource: Field Survey 2007212, Lahore, Pakistan Punjab Economic ResearchInstitute.Kwara ADP: Agronomic Survey Report for 1996 CroppingSeason Planning Monitoring and EvaluationDepartment.Ministry of Agriculture and Natural Resources,1988. Kwara Agricultural Development Project, Objectives,Functions, Values and Achievements, IlorinYek Printing Production.Olarinde, A. O., A. O. Ajao and J. O. Ajetomobi,2005. Socio-Economic Characteristics and Profitability

of the Contact and Non- Contact Farmers inOyo Agricultural Zone in a Deregulated Economy.Journal of Social Science, 11 (3): 177-181.The Herald, 2002. Wed. January 30th “Brief of KwaraState”, Kwara State Printing and Publishing Corporation,Ilorin. P.14.Windapo, O., 2002. Knowledge Implementation Accuracyof Maize and Cassava Technology Transferin Oyo Agricultural Development Program. UnpublishedPhD Thesis, Department of Agricultural ExtensionServices, University of Ibadan.Received September, 9, 2008; accepted for printing February, 23, 2009.Comparison of Use of Improved Agricultural Practices by Contact and Non-Contact....

1PROGRESS REPORT OF THE KARI’S FARMER FIELD SCHOOL PILOT PROJECTJoseph G. Mureithi, Project CoordinatorIntroductionThis is a brief progress report of the Farmer Field School (FFS) pilot project that was initiated inMarch 2001. The project aims at incorporating the FFS approach in the Soil Management Project(SMP) and Legume Research Network Project (LRNP) of KARI. The first phase of the twoprojects ended in December 2000 after being on the ground for about six years. Ten technologieswere developed and were ready for scaling up at the end of the first Phase. The two projectsadopted the FFS approach as one of the methodologies for scaling up the technologies because ofthe successes it has had in Asia in dissemination of IPM technology. Since the FFS approach is

new to most project staff, the pilot project was designed to include a strong training component.The project has six main activities, which are;a) Holding of a FFS sensitization workshopb) Training of Trainers course (TOT) on the FFS approachc) Development of farmer training curricula based on the technologies to be scaled upd) Development of monitoring and evaluation tools for the FFS approache) Support of three Msc. studentsf) Running about 45 FFS in five KARI centersFFS sensitization workshopThis workshop was held from 6-8th March 2001 in western Kenya. Its primary objective was tosensitize senior managers of KARI and Ministry of Agriculture and Rural Development(MoARD), researchers and extensionists implementing SMP and LRNP, and farmers on the FFSapproach for information transfer and scaling up of agricultural technologies. About 90participants attended this workshop. The workshop was facilitated by two experienced FFSpractitioners from FAO, Drs Kevin Gallagher and Russ Dilts; Prof. Agnes Rola of PhilippinesUniversity and Dr. Jaap van de Pol who has worked extensively in Africa on soil fertilitymanagement. The workshop covered, genesis of FFS approach and its principles and concepts;FFS ToT course and running FFS in the field; development of FFS training curricula; monitoringand evaluation of FFS; and FFS for integrated soil fertility and nutrient management andconservation. Country experiences on FFS approach from Philippines, Indonesia and Kenya

were shared during the workshop. Participants visited two FFSs that were in session in Busia;one led by farmers and the other led by extension to see in practice what they had learnt duringthe workshop. The last day of the workshop was spent in discussing the way forward for thepilot project and a number of issues were discussed. They included the merits of working withexisting groups vs. forming new ones, backstopping of farmer-led FFS, monitoring andevaluation of FFS process, sustainability of FFS, enhancement of local technical knowledge, FFSToT course, and strengthening research and extension linkages (see Appendix 1).Training of Trainers (TOT) course in FFS approachThe aim of this course is to equip the SMP and LRNP staffs with methods, skills, attitudes andknowledge to design, facilitate and implement FFS in their project mandate areas. The2participants come from KARI centers at Kitale, Kisii, Kakamega, Embu and Mtwapa. The courseis in two parts; the first part is to cover the theory of the FFS and planning and running FFS. Thesecond part is a season long training in the field where participants will initiate and run FFS.FAO Kenya is to provide two facilitators to conduct the training. About 60 participants are toparticipate in this training.The first part of the ToT was held at Egerton University from 12 to 17th March 2000. Topicscovered included introduction to FFS methodology, steps in conducting FFS, organization andmanagement of FFS, and non-formal education methods. It also included field exercises, group

discussions and plenary sessions. During the training participants developed tentative workplansof the schools they were going to initiate in the field. They also developed tentative trainingcurricula of the technologies to be scaled up. A report of the training is available from the ProjectCoordination’s office.The second part of the ToT is season long field-based training on how to run a successful FFS.The workplans developed during the first part of the training were used to initiate and run theschools. KARI Kitale and Mtwapa started their schools in April 2001 because the long rainyseason had just began in their sites. Schools in Kisii were initiated in May/June while inKakamega they were started in late June. Embu was the last to start its schools in late July 2001.Table 1 gives details of the FFS that have been formed and are in session to date.FFS on combination of organic/inorganic fertilizers FFS on low cost soil conservationfor maize production in KARI Kitale method in Kisii. The grass strip is ofVetiver grassThe FAO trainers provide technical backstopping and have scheduled to visit Kitale every firstMonday of the month and Kisii every third Thursday of the month. The Project coordinator alsosupervises the ToT during his routine visits to the Centers. Appendix 2 is an example of abackstopping visit report. The participants have been provided with many reading3materials/publications of the FFS approach to enrich their knowledge on the subject (Appendix

4).Development of farmer training curricula of the technologies to be scaled upDuring part one of the ToT course at Egerton University, participants developed draft trainingcurricula of the FFS they were to initiate in their respective centers. Some of these drafts areshown in Appendix 3. These draft curricula form the basis for preparation of weekly lessons ofthe FFS. The ToT participants meet once a week to prepare the lessons for the following weekand also improve the contents of the lesson of the previous week using feedback from farmers.At the end of the ToT the weekly lessons will be compiled into a farmer training curricula foreach of the technologies to be scaled up. Participants have been encouraged to take photographsof different stages of the technologies being demonstrated which will be used to enhance thequality of the curricula.Development of monitoring and evaluation (M&E) tools for the FFSThe tools were to be developed during an M&E workshop scheduled to be held in June 2001.Due to lack of suitable facilitators the workshop was postponed to a later date. Several meetingsand consultations have been held regarding this workshop and it is now proposed to be held inmid-September. Two experienced facilitators in M&E from the Natural Resources Institute(NRI) are keen to facilitate the workshop. They have shown a good understanding of the aspectsof participatory M&E training we would like offered to the ToT participants. The outcomes ofthe M&E training they are likely to offer are presented here.Understand the basic principles of monitoring and evaluation

Differentiate between the types of information required for learning compared to thatrequired for accountabilityInvolve farmers in order for them to learn more about the quality of training and supportoffered to farmers by the project both during and after FFS training eventsDesign and use tools, qualitative and quantitative, to understand and learn about the extent towhich farmers (female and male, young and old, poorer and better off, more and less literate)are responding to project services through the application and adaptation of knowledge andlinked technology “hard-ware” to their own situations.Assess the attitudes and responses to project services and outputs among non-participatingfarmers/communitiesWork together with farmers and other stakeholders to better integrate processes of M&E intoproject practice, using results to influence decision making at various levels with a view toimproving project delivery.Support for three Msc. studentsThe Msc. training was included in the project so that the students could undertake research thatwould contribute to the development and refinement of M&E tools for the FFS process. They4were also expected to evaluate the rate of technology spread and the impact it is will have onsmallholder farming. The original thinking was that the students would undertake Msc. studiesby research but this was not possible because it is mandatory to take a taught course in the localpublic universities for such training.

KARI Kisii and Kitale nominated a student each for the training and KARI Kakamega wassupposed to provide the third student. The student from Kisii has been admitted in EgertonUniversity while the one from Kitale has been admitted in Moi University. The two students arejoining their respective universities in September 2001 and they are expected to finish theirtaught course in May 2002 and embark on their research work in June/July 2002.Running of FFS in 5 KARI centersSo far 17 FFS have been initiated during the season long ToT course (Table 1) and most of themwill be terminated by the end of the year. It is hoped that a similar number will be conducted inyear 2002 and double that number in year 2003.AcknowledgementWe would like to acknowledge the financial support we have received from the RockefellerFoundation. We are in deed grateful to Dr. Ruben Puentes of RF New York and Mexico and Dr.John Lynam of RF Nairobi for technical support they have given the pilot project from itsinception up to now. Special thanks are extended to Ruben for provided many FFS readingmaterial in Appendix 4.5Table 1: Summary report of Farmer Field Schools initiated during the season long Training of Trainers courseKARICenterName of farmer field school(FFS)Technology being scaled up Number ofschool members

Male FemaleWhen initiated Special topics taught up toend of June1. Bikholwa (Action) FFS Combinations of organic andinorganic fertilizers formaize production18 4 10 April 2001 Poultry and dairyproduction; vegetableproduction; group dynamicsand good leadership; treemanagement2. Bulala (Unity) FFS Food legumes other thanbeans15 10 20 April 2001 What is soil and soil fertilityindicators; types of inorganicfertilizers and applicationmethods; dairy production;nitrogen cycle3. Busime (Love) FFS Management of organic andinorganic fertilizers forvegetable production5 12 20 April 2001 Local vegetables known tofarmers; poultry production4. Twende Mbele (Moveforward) FFSSuitable maize varieties forKitale mandate region4 8 30 April 2001 None5. Upendo (Love) FFS Quality seed production insmallholder farms7 23 10 April 2001 Hybrid seed development;role of Kenya Plant HealthServices inspectorate; seedborne diseases6. Khuyetena (Helping one

another) FFSForage crops establishment,management and utilization12 11 20 April 2001 Group dynamics; benefits ofintercropping; poultrydiseasesKitale7. Mteremko (Steep slope)FFSLow cost soil conservationmeasures5 9 14 May 2001 Control of stalk borer inmaize; plant deficiencysymptoms; maintenance ofsoil fertility, poultryproduction; vegetableproduction;68. Mutua (Last born) FFS Use of plant extracts tocontrol crop pests9 16 21 May 2001 Farm yard manuremanagement and storage;compost making;construction of water tanks,sheep and dairy production1. Riboba (cultivated plot)FFSCombinations of organic andinorganic fertilizers10 18 4 May 2001 Food security; dairy feeding;poultry production; groupdynamics2. Mlango (Door) FFS Improved soil conservationmeasures29 23 4 May 2001 Compost making; low cost

methods for soil erosioncontrol3. Etono (small ediblemushrooms) FFSIntegrated pest managementon bean production8 19 27 June 2001 None4. Keroka FFS Improved fodder production 25 20 10 June 2001 None5. Riomwando (Inheritance)FFSFinger millets varietiestolerant to blast disease5 27 10 July 2001 NoneKisii6. Umoja (Togetherness) FFS Use of soil fertilityimproving legumes11 25 13 June 2001 NoneKakamega Malanga FFS Green manure technologiesfor soil fertility improvement38 25 June 2001 NoneEmbu Karurina FFS Up-scaling green manuretechnology- - To be formed inJuly-Mtwapa Jembe (Hoe) FFS Combination of greenmanure legume with FYMand inorganic fertilizers7 8 28 March 2001 Group dynamics; pest anddiseases of maize and theircontrol measures7APPENDIX 1FARMER FIELD SCHOOLS SENSITIZATION WORKSHOP(6-8th March 2001, Golf Hotel, Kakamega)

Issues arising for the way forward1. Work with existing groups or form new ones?The participants felt there was need to work with already existing farmer groups e.g. the“merry-go-round” as the FFS activities can be conducted concurrently with the initialactivities of the group. However, each KARI center will have to evaluate its own localconditions as situations maybe different between the different KARI centers to be involvedwith FFS activities.In some regions, Farmer Research Committees (FRCs) are already in existence and areconducting field experiments. These FRCs are in the forefront in strategically setting updemonstrations of promising technologies, and they train and assist other new groups insetting up experimental activities. They can thus be transformed into Farmer Field Schools.Some disadvantages of working with some pre-existing groups are:-Old groups may not accept a FFS curricula for only integrated soil & nutrientmanagement topicsWeakness and problems are inherited.2. Farmer-led vs extension-led FFSIt was observed that usually it is graduates from Extension-led FFS who become trainers inFarmer-led FFS. It is not common to find a trainer originating from a Farmer-led FFS.Extension-led FFS have more to learn and share in terms of knowledge and skills, as theinput of extension personnel cannot be ignored.Backstopping is useful to prevent new groups from repeating the same experiment the oldgroups had conducted.

Backstopping by the extension in the Farmer-led FFS should be more than twice a month.In case of setting up new FFS, there was need to include subject matter specialists fromproblem diagnosis and through the season long experiment so as to backstop the project allthe way through.3. Monitoring and EvaluationThe data that the farmers were documenting was technical data, but there was need forfarmers to generate and document the indicators they use for monitoring and evaluation. Forexample, farmers have their own indicators for evaluation of crop varieties and needed alsoto use them in M&E.8It was also felt that Researchers, Extension and Farmers might have different indicators,which should be identified and used in the M&E process. But it was important to set up abenchmark, which should be the basis for future M&E assessments.There was also a feeling that the farmers and trainers can develop and run a M&E systemthat:(i) Provides good data to outside decision-makers.(ii) Strengthen “Farmer Groups” for sustainability.(iii) Allow FFS participants to use data to gather support for their own programs.4. Sustainability of FFSFarmers suggested that they needed small grants (funds) in order to initiate new schools. Theparticipants felt there was need to provide new FFS with basic materials e.g. paper, markers,new seeds etc. so as to assist in the running of new FFS. This kind of support was seen as

different from that of giving handouts.Critical support to the farmers should be in the form of collegial, moral, technical,networking and organization and not necessarily monetary support.Farmers should be encouraged to manage their resources as “Group Resources” to optimizeon available assets.5. Enhancement of Local Technical KnowledgeSince the technical knowledge held by farmers is limited, there is need to supplement it withscientific knowledge from the extension and research personnel. One case in point is the useof the local concoctions against pests and diseases. KARI should come in and test theseconcoctions for proper dosage application to avoid toxicity. Another case is on fertilizerswhere the farmers apply handfuls of fertilizer without an idea on the proper quantities to beused.The frontline extension personnel should consult subject matter specialists from theAgriculture Office or in Research Stations so as to access the available information thatexists and pass on the same to the farmers. It was noted that KARI has been producingextension leaflets/pamphlets with simplified language for the extension and farmers.Any extension leaflet with difficult language can be brought to the notification of KARIPublications Unit for simplification of language.6. ToT courseIt was felt that the initial one-week training was short, but this could be overcome byconducting another joint training week in the middle of the season-long FFS.

More regular follow-up meetings (backstopping) for problem solving and experience sharingwere emphasized. It was suggested that there be weekly or bi-weekly 1-2 days team meetingsfor reviews and planning the way forward. These regular meetings are essential especially atthe implementation phase of the FFS where the teams would consult and exchange ideas withtheir facilitators.9The ToT was expected to also cover the following specific topics such as:-Group developmentFacilitation skillsTechnical skillsManagementMonitoring & Evaluation7. Manual developmentThe teams were advised to start with a draft FFS program and on the basis of experiences onwhat they have learnt, they can develop them into manuals.8. Research and Extension LinkagesThe participants felt there was need to continue the collaboration and linkages betweenResearch and Extension. This would facilitate implementation of some joint activities such asproduction of leaflets/bulletins for farmers.Overall it was felt that the collaboration between Research and Extension should bestrengthened for mutual benefits to farmers.10APPENDIX 2Backstopping visit to FFS of KARI-Kitale on 11th June 2001Comments/observations1) Khuyetane FFS

(Forage crops establishment, management and utilization)Host team concept did not come out strongly. Facilitators were doing most of the things andso the role of host team should be emphasized.Field schools usually deal with comparative studies and this should be emphasized. DuringAESA presentation there was no presentation on comparative studies and this made itdifficult for farmers to notice any differences between plots.There should be summary of presentations across the board by facilitators after all thepresentations have been done. This was not done.Planning for next week should be participatory. That is all the farmers should be involvedand not dictated by the facilitatorOwnership of the FFS should be by the farmers. The farmers should own the FFS and notlook at it as if it is for KARI.Tagged plants should be inside the plot and not at the edge.Group dynamics were good.Overall the field school was well organized2) Busime FFS(Management of organic and inorganic fertilizers for vegetable production)Plot size was Small.Control plot not very clearHost team role was also not clear. One farmer was dominating.2) Bulala FFS(Promotion of alternative food legumes to than beans)Technology being scaled up should be emphasized. Not very clear from the visitLate plantingGenerally FFS process is being followed well although we arrived late and so not muchcould be seen.

General commentsThe Rotational systems by groups between plots should be implementedAESA taking, analysis and presentation should be done on the same day, during the learningday.Farmer selection is very critical and only practicing farmers should be nominated to join theFFS and not those working elsewhere.The officials elected in FFS should be strong.11APPENDIX 3Draft training curricula developed during ToT course of some technologies to be scaled up1. Low cost soil conservation methodsSoil …Definition… Importance…Genesis… composition… Management (generalSoil Erosion… Definition… When?… Why?… How?Soil Conservation… Definition… Importance… When?…Why?Soil Conservation Structures- Biology Structures- Physical StructuresEconomics of Soil Conservation- Maintenance of soil conservation structures

Options/basketBoth biological and physicalBiological structures- Makarikari- VetiverTrash lineNapier grassPhysical structures- Fanya juu- Stone linesFanya chini2. Organic manure management and its use in combination with inorganic fertilizersfor crop productionTeach and trainSoil genesisSoil management technologies12Collection management and use of manuresDemo on compost management preparation and storageCollect materialsSet up compostMonitoringFYM managementBoma compostingCollection of crop residue into cattle BomaTeach aspects of maize productionTeach about seed production such aTeaching on harvesting, storage of maize.3. Quality Seed productionIntroductionBasis for developing varietiesAltitude, rainfall, temperatureLightly methods of developmentType of varieties

Characters of good seedsHybrids, open pollinated (compositesIsolationSelection of crop and variety to plantSource of good quality seedLand preparation and field layout (per crop variety)Planting - site selection and time of plantingWeeding - noxious weedsCrop management - as per cropWeekly observations, monitoring and data collectionHarvesting - time of harvesting andEconomic analysis- Seed processing - (as per crop) threshing, cleaning, pure g. seed- Seed treatment - (as per crop) i.e. use insecticide/ash), fungicide- Seed storage - Temperature, humidity (as per cropData to collectas per crop variety- Include seed processing- Seed storage4. Suitable crop varieties for different AEZ’s in Kitale RegionIntroduction- Basis for developing varieties e.g. altitude rainfall, temperature etc- Diversity of AEZ in the country- Participatory description of the environment13- Establish farmer practices and reasons – (Ground working)Participatory selection of treatments from the basketLand preparation and field layoutPlanting, weeding, top-dressing, pest management (and general crop management)Weekly observation, monitoring and data collectionHarvesting and economic analysis5. Bean varieties tolerant to bean fly and root-rotImportance of beans (food, soil improvement, income generation)Problems related to bean production( diseases, pests, soil fertility)

Problems limiting bean production in the area (Marani)Bean-fly pest-Infestation, Life-cycle, effect on plant vigorRoot-rot disease – Infection, Typical symptoms, effect on cropEstablishment of insect zoo (bean-fly)Farmer evaluations of the different varieties – size, color, taste, yields, cookability (rankingto be one)Special topics as need arisesSeed production – selection, storage, treatment14APPENDIX 4Reading materials issued to FFS ToT participants1. Making Farmers Better Decision - Makers Through the Farmers Field SchoolBy Rola A.C. Provido Z.S, Olanday M.O, Paraguas A.S, Sirue, A.S., Espadon, M.A. and HupedaS.PKasakalikasan. The Philippine National IPM Program2. Rural Learning Networks - Farmer Field School in Integrated Crop ManagementBy Marco Miagostovich3. Economics of IPM – FFS Knowledge Diffusion in Rice Farming Communities: A Case Studyin Iloilo, PhilippinesBy Agnes Rola4. Can the Farmer Field School Replace the T&V System of Extension in Sub-Saharan Africa?By Cees Leeuwis, Neils Roling and Gerard Bruin5. A Note on the Sustainability of the Farmer field School Approach to Agricultural ExtensionBy Jaime Quizon, Gershon Feder and Rinku Murgai6. Output of the Intensive Training of Trainers Course on Farmers Field School - Mabanga7. Guidelines and Reference Material on Integrated Soil and Nutrient Management and

Conservation for Farmer Field SchoolsFAO, ROME, AGL/MISC/27/20008. Community Driven Development; from vision to practiceA technical Source book9. Process – Monitoring Report Pilot Sweet Potato IPM Farmer Field Schools and FieldBy Kim Groenewg10. FFS studies in Vietnam11. Searching for Strategies to Replicate a Successful Extension Approach: Training of IPMTrainers in IndonesiaBy E. van de Fliert, J. Pontius and N. Roling12. The IPM Farmers’ field SchoolAn Indonesian contribution to Sustainable Agriculture13. Do farmer field school graduates retain and share what they learn? An investigation in Iloilo,Philippines15A.C. Rola, J.B. Quizon and S.B. Jamias14. An economic framework for assessing the impact of farmer field schools: A case study inIloilo, PhilippinesA.C. Rola15. Living soilsTraining exercises for integrated soils managementUNFAO Program for Community IPM in Asia, JI Jati Padding no. 38B, Pasar Minggu, JakartaIndonesia16. An introduction to the IPM farmer field schoolRuss Dilts and John Pontius17. Beyond the farmer field school: IPM and empowerment in IndonesiaPeter A. C. Ool, gatekeeper series no. 78

comfortable in field situations than in classrooms. In most cases,communities can provide a study site with a shaded area for

follow-up discussions.The facilitatorEach FFS needs a technically competent facilitator to leadmembers through the hands-on exercises. There is no lecturinginvolved, so the facilitator can be an extension officer or aFarmer Field School graduate. Extension officers with differentorganisational backgrounds, for example government, NGOsand private companies, have all been involved in FFS. In mostprogrammes, a key objective is to move towards farmerfacilitators, because they are often better facilitators than outsideextension staff - they know the community and its members,speak a similar language, are recognised by members ascolleagues, and know the area well. From a financialperspective, farmer facilitators require less transport and otherfinancial support than formal extensionists. They can alsooperate more independently (and therefore cheaply), outsideformal hierarchical structures.All facilitators need training. Extension facilitators need seasonlongtraining to (re)learn facilitation skills, learn to grow cropswith their own hands, and develop management skills such asfund-raising and development of local programmes. Computerliteracy is often included in the training of facilitators, especiallyfor preparing local training materials, budgets and projectproposals. Email is also becoming more widely available. Oncethe facilitators have completed their training and are leading theFFS process, it is easy to identify capable farmers who areinterested in becoming facilitators. Farmer Field Schoolgraduates are usually given special farmer facilitator training(10-14 days) to improve technical, facilitation andorganisational skills.The curriculumThe FFS curriculum follows the natural cycle of its subject, be itcrop, animal, soil, or handicrafts. For example, the cycle may be“seed to seed” or “egg to egg”. This approach allows all aspectsof the subject to be covered, in parallel with what is happening in

the FFS member’s field. For example, rice transplanting in theFFS takes place at the same time as farmers are transplantingtheir own crops - the lessons learned can be applied directly.One key factor in the success of the FFSs has been that there are 5LEISA MAGAZINE . MARCH 2003Kevin GallagherIn general, Farmer Field Schools (FFS) consist of groups of peoplewith a common interest, who get together on a regular basis tostudy the “how and why” of a particular topic. The topics coveredcan vary considerably - from IPM, organic agriculture, animalhusbandry, and soil husbandry, to income-generating activitiessuch as handicrafts. FFS are comparable to programmes such asStudy Circles, religious studies at a church, mosque or temple, orspecialised study programmes for any skill. The FFS, however, areparticularly adapted to field study, where specific hands-onmanagement skills and conceptual understanding is required.So what are the essential elements of a FFS? Below is a list ofelements that commonly appear in successful FFS programmes:The groupA group of people with a common interest form the core of theFFS. The group may be mixed with men and women together, orseparated, depending on culture and topic. The group could bean established one, such as a self-help, women’s, or youth group.Participatory technology groups, for example, sometimesundertake a season of study in FFSs before starting theirresearch. The FFS tends to strengthen existing groups or maylead to the formation of new groups. Some FFS groups do notcontinue after the study period. The FFS is not developed withthe intention of creating a long-term organisation - although itoften becomes one.The fieldFFSs are about practical, hands-on topics. Study Circles andother study methods do not take place in the field, as they areabout more theoretical topics. In the FFS, the field is the teacher,and it provides most of the training materials like plants, pests

and real problems. Any new “language” learned in the course ofstudy can be applied directly to real objects, and local names canbe used and agreed on. Farmers are usually much moreAn Indonesian training coordinator demonstrating techniques forcatching insects during a lesson on IPM in Gambia. Photo: FAO/A. ProtoFundamentalElements of aFarmer Field SchoolA typical FFS session in the original Indonesian setting8:00 Opening (often with prayer)Attendance callDay’s briefing of activitiesStretching exercises8:30 Go to the field in small teamsMake observations that are noted by the facilitator and one otherperson in the group records. Facilitator points out interesting newdevelopments9:30 Return to shade. Begin making agro-ecosystem analysis (see box)drawing and discuss management decisions.10:15 Each team presents results and the group arrives at a consensus onmanagement needs for the coming week.11:00 Short tea/coffee/water break11:15 Energiser or group building exercise11:30 Special study topic or second crop/livestock study. This couldinclude nutrition, or chicken or parasites, or something else ofspecial interest to group.12:30 Closing (often with prayer).no lectures – all activities are based on experiential (learning-bydoing),participatory, hands-on work. This builds on adultlearning theory and practice. Each activity has a procedure foraction, observation, analysis and decision making. The emphasisis not only on “how” but also on “why”. Experience has shownthat structured, hands-on activities provide a sound basis forcontinued innovation and local adaptation, after the FFS itself

has been completed. It is also one of the main reasons thatfarmer facilitators can easily run FFSs - once they know how tofacilitate an activity, the outcomes become obvious from theexercise itself.Activities are sometimes season-long experiments - especiallythose related to soils or plant physiology (for example soil orvariety trials, plant compensation trials). Other activities in thecurriculum include 30-120 minutes for specific topics.Icebreakers, energisers, and team/organisation buildingexercises are also included in each session. The curriculum ofmany FFSs is combined with other topics. In Kenya, forexample, the FFSs follow a one-year cycle including cash crops,food crops, chickens or goats and special topics on nutrition,HIV/AIDS, water sanitation and marketing. FFSs for literacy arealso promoted where there is a need.The programme leaderMost FFS programmes exist within a larger programme, run bygovernment or a civil society organisation. It is essential to have agood programme leader who can support the training offacilitators, get materials organised for the field, solve problems inparticipatory ways and nurture field staff facilitators. This personneeds to keep a close watch on the FFSs for potential technical orhuman relations problems. They are also the person likely to beresponsible for monitoring and evaluation. The programme leadermust be a good leader and an empowering person. He or she is thekey to successful programme development and needs support andtraining to develop the necessary skills.AESA in a typical FFS for riceThe basic format of an IPM Farmer Field School consists of three activities:agro-ecosystem observation, analysis, and presentation of results; a“special topic”; and a “group dynamics” activity. The Agro-EcosystemAnalysis (AESA) is the FFS’s core activity, and other activities are designedto support it.

The agro-ecosystem analysis process sharpens farmers skills in the areas ofobservation and decision-making, and helps develop their powers of criticalthinking. The process begins with small group observation of the IPM andnon-IPM plots. During the observation process participants collect field datasuch as the number of tillers per hill, the varieties of insects and theirpopulations and samples of insects and plants. These data are collected fromten rice hills. The facilitator is present throughout the observation to helpparticipants in their observations.Following the field observation, the farmers return to the meeting place and,using crayons, draw what they have just observed in the fields on a largepiece of newsprint or poster paper. The drawings include:a) pests and natural enemies observed in the fields (pests on one side,natural enemies on the other);b) the plant (or animal) indicating the size and stage of growth, along withother important growth features such as the number of stems/tillers, thecolour of the plant and any visible damage;c) important features of the environment (the water level in the field,sunlight, shade trees, weeds, and inputs).All members of the small groups are involved in the creation of the drawingand data analysis. While drawing, farmers discuss and analyse the data theyhave collected. Based on their analysis they determine a set of managementdecisions to be carried out in the field. A summary of these managementdecisions as agreed by the group is also included in the drawing.One member of each small group then presents these findings and decisions

to the larger group. After this brief presentation of results there is time foropen questions and discussion. Good large group discussions often involveposing alternative scenarios, for example, questions such as “What wouldyou do if....” This cycle of presentation, question, answer and discussion isrepeated until all the small groups have presented their results. Agroecosystemdrawings from previous weeks are kept on hand as a referenceand as material for discussion later in the season.The role of the facilitator is central to the EASA process. In the field, theywill guide participants to see what they may not have seen before, such astiny predators or changes in soil. To ensure a balanced and participatorydiscussion, a good facilitator understands that the more participants talk,the more they learn, and encourages discussion rather than lecturing.During presentations, the facilitator ensures that all participants have anopportunity to present during the season, and that the group covers all theimportant issues. The facilitator needs farming and technical skills andneeds to know how to ask good questions, guide participants throughexercises and ensure that sound management decisions are taken by thegroup by introducing new information when appropriate.FinancingFFSs can be expensive or low-cost, depending on whoimplements them and how they are conducted. When carried outwithin a World Bank-type programme, they are usuallyexpensive, due to high allowances, transportation costs andseveral layers of supervision (about US$30-50 per farmer).Obviously, the greater the distance that facilitators need to travelto get to the field, the higher the cost of transport. Transport isone of the biggest costs in any extension programme. When the

FFS is carried out by local organisations and farmer facilitators,initial start-up costs may be moderate, but the running costs willbe much lower (about US$1-20 per farmer). A trend in EastAfrica is to manage small commercial plots alongside the FFSstudy plots, so that the FFS can actually raise more funds than ituses for inputs and stationary (Okoth p. 27).Final wordFarmer Field Schools are not difficult or mysterious. However,they are meant to empower through education on skills andconcepts (how’s and why’s) and therefore, require anempowering environment. The basis for a successful FFS startswith the programme’s culture of operation - from a nurturingand empowering programme leader and good facilitators, totransparent budgets and open management. FFSs are notdifficult to set up if there is a commitment to, and faith infarmers’ and facilitators’ ability to learn locally and applylearning to local problems themselves.■Kevin Gallagher. Food and Agriculture Organization of the United Nations (FAO).Viale delle Terme di Caracalla, 00100 Rome, Italy. Email: Kevin.Gallagher@fao.org.For more information on Study Circles and “4-H” groups,please see the following websites: www.studycircles.org andwww.fourhcouncil.edu.6LEISA MAGAZINE .MARCH 2003