11

What we learned from the CFC/IPM coffee project (ICO/02)

With

Luis Fernando Aristizábal, Oscar Campos,William Chilán, Armando García, Raúl Muñoz,

Ramón Jarquín, Alberto Larco, Carlos Gonzalo Mejía, Mauricio Salazar.

CABI CommoditiesEgham, Surrey

TW20 9TYUK

May 2002

Jeffery W. BentleyPeter S. Baker

Manualfor Collaborative Research

with Smallholder Coffee Farmers

2 2

CREDITS

EDITORIAL COORDINATION

Héctor Fabio Ospina O.

DESIGN AND LAYOUT

Carmenza Bacca Ramírez

PRINTING

FERIVA S.A.

Cali, Colombia

May 2002

© The Commodities Press1

20021A joint CABI-CENICAFÉ enterprise

33

M

At the core of the global divide

is the vast inequality in innovation and diffusion of technology

[Jeffrey Sachs]

A C K N O W L E D G M E N T S

Many people helped us with ideas, encouragement and hard work. We thank especially thefollowing:

Juan Barrera, Evaristo Calle, Pablo Delgado, Caleb Dengu, Hernando Duque, Falguni Guharay,Julius Jackson, Sean Murphy, K Sreedharan, C Prakasan, Janny Vos, Stephanie Williamson.

Janny Vos read and made valuable comments on an earlier version.

This book would not have been possible without the gracious collaboration of many farmers,including those mentioned in the text.

Finally, we give a special thanks to Sergio Ballón for proof-reading the Spanish version.

4 4

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FOREWORD

“…key ingredients in a successful development strategyare ownership and participation. We have seen again andagain that ownership is essential for successful transfor-mation: policies that are imposed from outside may begrudgingly accepted on a superficial basis, but will rarelybe implemented as intended. But to achieve the desiredownership and transformation, the process that leads to thatstrategy must be participatory.”

Joseph E. Stiglitz, Towards a New Paradigm for Develop-ment: Strategies, Policies, and Processes [The Prebisch Lec-ture, 1998]

This manual stemmed from the CFC-funded Integrated Management ofCoffee Berry Borer project, ICO/02 (1998-2002). The aim of the projectwas to develop cost-effective and environmentally friendly ways of con-trolling the world’s most serious pest of coffee, which would be usefulto smallholder farmers, who supply the majority of the world’s coffee.

But new methods, however well intentioned, are no use if they are notadopted. Over the last part of the 20th century, scientists and develop-ment experts became increasingly worried that much technology wasnot being adopted by the rural poor, and came to the conclusion that aprincipal reason was lack of understanding of the farmer’s perspective,his problems and his capabilities. From this sprang new ways of work-ing with farmers to ensure enhanced uptake; these methods can bebroadly referred to as “participatory”.

It is our contention that these developments have largely by-passed thecoffee industry and because of the secular, global change that has struckit in recent years, this approach must now be more widely understoodand assayed.

It is the purpose of this manual therefore, to explain some of the prin-ciples and practices to those who are interested in improving the situa-tion of smallholder coffee farmers. We warmly thank the Common Fundfor Commodities for allowing us to use their funds to produce this vol-ume.

Jeffery Bentley & Peter Baker, April 2002

PART 1CHAPTER 1. INTRODUCTION

1.1 WHY THIS BOOK?

1.2 WHY COFFEE, WHY NOW?

1.3 COFFEE IS SPECIALCoffee provides social welfare; coffee is a perennial crop; coffee is not a food. Cof-fee has appeal, almost a mystique.

1.4 THE PROBLEMS OF WORKING ON COFFEELarge variations in farm size; coffee is one of the few legal crops that can helpsmallholders escape poverty; coffee is an export crop; Integrated Pest Management;much of the research and extension in coffee is still top down.

GLOSARY

CHAPTER 2. PARTICIPATORY RESEARCH, A PEOPLE-CENTRED APPROACH

2.1 BASIC ISSUESNew knowledge is needed; adapting ideas; FPR is research, not extension.

2.2 FPR (FARMER PARTICIPATORY RESEARCH): A GUIDE TO SOME OF THE TYPES.CIAL. Back-&-Forth; FFS; FFS adapted to research; the Zamorano method

2.3 DISCUSSION OF FPR

CHAPTER 3. WORKING IN THE FIELD, A BASIC ORIENTATION

3.1 THE PLAYERSThe farmer.The farmer’s mind-set; their worries; their constraints; what they think of you, theresearcher.

3.2 THE EXTENSIONISTThe extensionist’s mind-set; their worries; their constraints; what they think of you,the researcher.

3.3 THE RESEARCHERThe researcher’s mind-set; their worries; their constraints.

CHAPTER 4. ASSESSING DEMAND

4.1 BASIC FIELD SKILLSAttitude

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4.2 LEARN FROM EXTENSION AGENTSTips for working with extensionists.They know the area better than you do; know the farmers better; know a lot aboutlocal problems; some will have good ideas; some will resent you; they are sometimeswrong; most are glad to receive some attention.

4.3 APPROACHING THE FARMERSTalking to farmers: some useful tips.Learn from farmers.Everybody knows something, but nobody knows everything; ethnoscience.

4.4 OBSERVE FARMERS’ BEHAVIOURSocial study of behaviour.

4.4 LEARN FARMERS’ RESEARCH NEEDSAppraisalsQuestionnaires; short questionnaire plus sampling; PRA; sondeo; 3 legs; semi-struc-tured interview; participant observation.Avoid getting a naïve collection of obvious problems.Explicit and implicit demands; problem vs. demand; how to ask farmers about theirresearch needs; learn researchable topics; example of a researchable topic.

CHAPTER 5. PLANNING RESEARCH WITH FARMERS

5.1 DECIDING THE APPROPRIATE LEVEL OF FARMER-SCIENTIST COLLABORATIONFarmers’ comparative advantage; scientists’ comparative advantage.The different levels of farmer involvement:

Level 1, contractual, the least participatory.Levels 2-3, consultative & collaborative, more participatory.Level 4, collegiate the most participatory.

Conclusion: deciding on the level of farmer involvement.

5.2 CONTACTING COMMUNITIESPicking communities.Purposeful selection; ad hoc selection; stratified selection.How many communities?Social structure.Local leaders; farmer committees.

5.3 AROUSING COMMUNITY INTERESTIdentifying the problem you are going to work on.Agreeing on priorities.Setting an agenda.Only promise what you will fulfill, getting and keeping extensionistcollaboration.

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CHAPTER 6. CONDUCTING THE STUDY, PRACTICAL HINTSFilling in gaps in knowledge.From diagnosis to management; keeping notes.

6.1 THE SOLUTION EXISTS BUT NEEDS TRAINING

6.2 A RANGE OF OPTIONS EXISTS, BUT NEEDS

STATISTICAL SCREENING

6.3 ADAPTING A SOLUTION FOR LOCAL CONDITIONS:

GETTING STARTED

6.4 ADAPTING A SOLUTION FOR LOCAL CONDITIONS (Continued):

EXPERIMENTAL DESIGN, STATISTICS, THE SCIENCE DEBATEField trials versus one-off experiments; experimental design; statistics; the sciencedebate.

6.5 ADAPTING A SOLUTION FOR LOCAL CONDITIONS (Continued):

RESEARCH PROTOCOLSChoosing treatments; have one or 2 treatments per farm, with a control; number ofreplications; each farm is a replicate; their location; size of replicates; shape ofreplicates; planting and harvest dates; what numerical data will be taken and whowill take it; be prepared to lose some farms.

6.6 ADAPTING A SOLUTION FOR LOCAL

CONDITIONS (CONTINUED): COMMUNITY RELATIONSTiming of visits; use participatory research to validate and reject technology; bal-ance replicability with participation; failure is part of success; keep the statisticaldesign simple; hold workshops.

CHAPTER 7. SUPPORTING FARMERS’ ORIGINAL RESEARCH

7.1 FARMER INVENTIONS

7.2 NEW IDEAS ARE THE FATHERS OF INVENTION

7.3 FARMERS MODIFY TECHNOLOGY (WHICH IS ALSO INVENTION)

CHAPTER 8. PRDUCING RESULTS AND SHARING THEM WITH THE COMMUNITY

8.1 RESULTS OF ADAPTIVE RESEARCHData; analysing data; presenting the data convincingly; don’t over analyse the re-sults; graph everything out before writing, try to be visual; collect farmers’ authen-tic statements; photograph them; give them copies of the research; participatory

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evaluation; inviting local people to meetings.Case histories from the project.

8.2 EXTENSION

8.3 KEEPING THE PROJECT GOINGMonitor how farmers adapt, adopt, & reject technologies; holding farmer ex-perimenter workshops; reward farmer experimenters.Technology evaluation.

8.4 OTHER THINGS TO BEAR IN MIND

CHAPTER 9. DISCUSSION & CONCLUSIONS

9.1 REVIEW OF THE PROJECT CASE STUDIES: WHAT WORKED AND WHAT DIDN’T.Adaptive research; the Colombian project; social research; hot-spots; scientistsoften relate well with farmers; farmer inventions? The ones that got away; look-ing for a method; old friends; many farming communities are remote; if farmersreally participate in trial design, then there are no replicates; gleaning; othercultural controls; in hindsight; sampling; not wild and crazy; a code for work-ing with farmers? What works with farmers? What doesn’t work? Comparewith success stories from other crops; is coffee different?

9.2 CONCLUSIONSThe role of the supervisor; could we have done better?Self-Criticism.Main achievements.Adaptive research; new technology; validations; strategic on-farm research.Rejection; hot-spots; different approaches emerged? Towards a protocol forworking with farmers.The future.

9.3 MAIN ACHIEVEMENTS

9.4 TOWARDS A PROTOCOL FOR WORKING WITH FARMERS

9.5 THE FUTURE, SOME RECOMMENDATIONS

REFERENCES CITED

PART TWOANNEX (Outline of efthnoscience and farmer participation in agricultural research)

CASE STUDIESColombian case study; Ecuador case study; Honduras case study; Mexico casestudy.

PART I

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1.1 WHY THIS BOOK?

This is a practical field guide to what is a relativelynew discipline, especially for coffee.

Coffee, at the producer end at least, is in deep troublefor a number of reasons, including technology-drivenoversupply. Historically, agricultural research hasworked to improve production. But its adoption hasbeen patchy and tended to benefit wealthier farmers.The tendency in developed countries in all crops hasbeen for small farmers to be replaced by largemechanised estates and the migration of farm youthto city factories and services. Life has not always beeneasy for those who stayed on farm, as we have seenrecently in developed countries such as the UK. Wethink this technological process is now underway inearnest for coffee.

1.2 WHY COFFEE, WHY NOW?

Coffee is important. Over 50 countries export coffee,together worth five to 10 billion dollars per year (ac-cording to fluctuating market prices—more than 100million bags of 60 kg each). The number of coffeefarmers that produce the crop is regrettably not known,but must be over 20 million. If we count dependentfamilies and the many other actors down the coffeechain, at least 100 million people depend on coffeefor their livelihood.

Coffee used to be the world’s second most traded com-modity. It is now down to fifth place, behind oil, alu-minium, wheat and coal (Ponte 2001). But it is still

the world’s most important perennial crop and by itsvery nature, requires farmers to invest more thanmany other crops. In the case of coffee this has led toit becoming a culture in some countries, a way oflife.

Hence farmers know a lot about coffee and its imme-diate environment but we have rarely consulted themin any formalised way about their knowledge.

The project from which this book sprung1 was oneof the first to do this in a systematic fashion. It turnsout, when we do ask them, (e.g. Baker 1999, Bentley2000a) that they have very interesting things to say,sometimes profound, sometimes completely errone-ous but frequently unexpected and thought-provok-ing. For example, in Nicaragua recently we spokewith a farmer about CBB2 incidence. She said that ithad been low before, but that next year there couldbe much more, she explained that it was because:

“The price of coffee was low last year. This year the(quality of) the harvest was not too bad, and beforethat we only used chemicals.” (El precio del café elaño pasado fue bajo. Este año se recogió más o menosy antes solo usamos el químico.)

It was a perceptive observation. The logic goes likethis:

1. In the year 2000 and earlier there was little CBB,because people used insecticides.

2. In the year 2000 the price of coffee was higherthan in 2001.

1 The CFC - ICO Integrated management of the CBB ICO/02 1998 – 20022 The coffee berry borer ( Hypothenemus hampei)

Farmers like to participate

“Less obvious than the economic and political signifi-cance of the industry is its impact on scholarship.

Intellectual traditions have been born from the study ofcoffee; some have been overturned by it. The industry

has shaped fields of learning.”

Robert Bates

[World Coffee Conference, London 2001]

1313

3. Therefore people harvested thoroughly andgleaned.

4. Thus they eliminated much of the CBBs’habitat.

5. So in the year 2001 there was little CBB.6. But now that prices are lower, people are not

harvesting as carefully and in followingyears CBB could be a problem.

The central problem we now all confront is that for anumber of reasons, smallholder farmers are findingcoffee-growing increasingly unprofitable and we, asso-called coffee experts, have not even told themabout the great changes taking place. Neither havewe documented what they think about what is hap-pening to them. A way of life may be passing foreverand what will we have learned from it?

It is ironic that whilst coffee farming has caused in-creasing losses for most smallholders, there is increas-ing interest in sustainable coffee farming and a grow-ing number of ways that farmers can add value totheir produce. And remarkably, at the top of the mar-ket, the gourmet sector, there is a shortage of highquality coffee.

Many small farmers could profit from these devel-opments if they only knew how. To help small farm-ers is always a challenge, but the main contention ofthis book is that if we set about the task logically andmethodically we can do it and that we can best suc-ceed through soliciting their active participation. Thisis particularly the case now with the global reduc-tion in government-backed extension services.

1.3 COFFEE IS SPECIAL

Maize, rice, potatoes and other smallholder crops areall annuals that farm families can eat at home, evenwhen prices are low. Compared to these “daily breadcrops,” coffee is unique in several ways.

Coffee provides cash to resource-poor farmers andtheir labourers. It is labour-intensive; in most coun-tries where coffee is grown, poor rural families pickcoffee to earn some of the money they need. Andthey need more of it than previously since neo-lib-

eral policies have reduced state-run social security,health and education services.

Coffee is a perennial crop. This has environmentalbenefits (biodiversity and soil preservation), but it alsomeans that farmers cannot adjust rapidly to rising orfalling prices.

Coffee is not a food. Smallholder farmers who growstaple foods can eat the crop if prices are low. Butlow coffee prices are a disaster. If the people havepaid cash for fertilisers, labour etc., they risk goinginto debt.

Coffee has appeal, almost a mystique. The Colombi-ans recognised this in the 1920s and specialised inmeeting the demand for high quality coffee. Nichemarkets now include organic, bird friendly and fairtrade coffee.

1.4 THE PROBLEMS OF WORKING ON COFFEE

Large variations in farm size. In some countries,many farms are large enough for the farmer to havehis own brand name and be his own exporter. Butcoffee is also grown by many smallholders, who ap-ply much higher levels of management per hectarethan do estate owners. This means that smallholderscan produce better quality coffee than large planta-tions because they are more likely to be able toorganise the labour to harvest at the optimum moment.A smallholder picks coffee alongside her workers,while an estate owner hires overseers. But often small-holder coffee ends up being lower in quality; they dryit badly and sell to intermediaries who mix it withother coffees. Through lack of resources and train-ing, the family farmers fail to realise the full potentialof their crop. So large and small farms have differentresearch needs; but unfortunately, many research in-stitutes do not fully recognise this.

Coffee has been one of the few legal crops that can

help smallholders escape poverty. Few farmers earna middle income by hand-farming staple food crops.In Colombia some families make a decent living3 byspecialising in three hectares of coffee (Bentley &Baker 2000). In many countries, smallholders are more

3 Or at least they used to, until the recent crash in coffee prices.

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diversified. They grow food crops to eat, and theygrow some coffee for the cash they need for clothes,medicine and children’s school supplies.Coffee is an export crop, and so governments payattention to it. Many coffee-growing smallholdershave been visited for years by extension agents, andhave learned more scientific information (and occa-sionally dis-information) than say, grain growers.

Integrated Pest Management: IPM is a difficult, in-formation-intensive and location-sensitive topic, andneeds to be participatory to avoid producing irrelevanttechnologies.

But because coffee has long been an important ex-port commodity, much of the research and extensionin coffee has been top down, driven by political needs.Much of the current thought on farmer participationin research has bypassed coffee. For all these reasons,and the massive changes in socio-economic thinking,environment and trade factors, globalisation of mar-kets, technology and agribusiness, and evolving con-sumer tastes, we need to rethink how to help smallcoffee farmers.

From the disaster that we discover to be 21st centurycoffee-growing, new thinking and actions will haveto come. We coffee experts have failed the farmers;neither having listened to them nor told them what ishappening.

This book is a small step towards trying to redressthis inequity. It is addressed to researchers and otherswho design and carry out projects on behalf of coffeegrowers.

This manual is the direct product of the Project: Inte-grated Management of the CBB, supported from 1998to 2002 by the Common Fund for the Commoditiesand co-ordinated by Peter Baker, of CABI Commodi-ties in the UK. The project was implemented by spe-cialists in coffee institutes in the following countries:

Colombia (CENICAFÉ)

Ecuador (ANECAFÉ)

Mexico (ECOSUR)

Guatemala (ANACAFÉ)

Honduras (IHCAFÉ)

India (Coffee Board of India)

Jamaica (Coffee Board of Jamaica)

This manual reflects what the project did, and whatwe would do differently, if we could do it over again.

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� ANACAFE, Asociación Nacional del Café, the Guate-malan coffee institute

� ANECAFE, Asociación Nacional de Exportadores deCafé, the coffee exporters association of Ecuador

� Biological Control Using nature to control pests. Allorganisms have predators, but some manage to escape themby migrating. The coffee berry borer is one of them, its co-evolved natural enemies stayed in Africa. This projecthelped them catch up with their prey.

� CABI, CAB International is a not-for-profit treatylevel intergovernmental organisation with 41 member coun-tries including several major coffee-producing countries. Itconsists of two divisions CABI Bioscience and CABI Pub-lishing. Its main goals are generation and brokering of sci-entific knowledge for developing countries. CABI Com-modities is an initiative of CABI Bioscience.

� CATIE/NORAD, Centro Agronómico Tropical deInvestigación y Enseñanza . A project of this Costa RicanInstitute in Nicaragua, funded by NORAD the Norwegianforeign aid agency.

� CBB, coffee berry borer (Hypothenemus hampei(Ferrari 1867)) a 2 mm long black beetle that is the mostsignificant pest of the world’s most important tropical agri-cultural commodity.

� CBI, The Coffee Board of India

� CENICAFE, Centro Nacional de Investigaciones delCafé, the Colombian coffee research institute, a division ofthe Federation of Colombian Coffee Growers.

� CFC, Common Fund for Commodities is an intergov-ernmental financial institution, funding commodity devel-opment projects globally. The Agreement establishing theCommon Fund for Commodities was negotiated in theUnited Nations Conference on Trade and Development(UNCTAD) in the 1970s, concluded in 1980 and came intoforce in 1989. Currently the Common Fund has 104 Mem-ber Countries plus the European Community, theOrganisation of African Unity/African Economic Commu-nity (OAU/AEC) and the Common Market for Eastern andSouthern Africa (COMESA).

� CIAL, Local Agricultural Research Committee, a farmerparticipatory research validation committee.

� CIAT, Centre for Agricultural Research in the Tropics,Cali, Colombia

� CIB, Coffee Industry Board of Jamaica

� Cultural control, a broad term involving mostly manualcontrol that includes hand picking of infested berries.

� ECOSUR, El Colegio de la Frontera Sur, Chiapas,Mexico

� Gleaning, the term for cultural control used in India,chiefly for cleaning up after the main harvest.

� ICO, The International Coffee Organization (ICO) isan intergovernmental body whose Members are coffee ex-porting and importing countries. Established in 1963 it ad-ministers the International Coffee Agreement from its Head-quarters in London, and is committed to improving condi-tions in the world coffee economy through international co-operation, helping price equilibrium by developing demandfor coffee in emerging markets and through projects to re-duce damage from pests and improve marketing and qual-ity, enhancing coffee growers’ long-term competitivenessand contributing to the fight against poverty.

� IHCAFE, Instituto Hondureño del Café

� IICA, Instituto Interamericano de Cooperación para laAgricultura

� IPM, Integrated Pest Management, a knowledge-in-tensive strategy for controlling pests where the farmer esti-mates current and future damage to his crop and picks froma range of techniques to optimise profit. The basic princi-pal is that control measures should cost less than the lossesincurred by inaction. It requires knowledge of pest biology,continual monitoring of the crop, the worth of control meth-ods, simple maths and an understanding of commodity pricedynamics.

� Parasitoid, A specialised predator that lays its eggs onor (as in the case of Phymastichus coffea,) in the insect.The egg hatches out and kills its host by consuming it. Para-sitoids differ from parasites in that the former always killtheir host to complete their life-cycle.

� PROMECAFE, Programa Cooperativo Regional parael Desarrollo Technológico y Moderización de laCaficultura, a Central American coffee technology networkformed under the auspices of IICA.

GLOSSARY

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“Farmer participation in agricultural researchis more than talking to six farmers or putting

ten experiments in their fields. Above all, it is asystematic dialogue between farmers andscientists to solve problems and ultimately

increase the impact of agricultural research.”

[Mauricio Bellon 2001, Participatory Research

Methods for Technology Evaluation]

2.1 BASIC ISSUES

A brief account of types of participation, extensionand research and their inter-relations is needed becausewe have found considerable confusion about the ter-minology.

The fundamental point is to decide whether yourproject is about:

a) new knowledge generation and collaboratingdirectly with farmers to help you do this, or

b) adapting and extending to farmers an existingmenu of possible answers to a pressing problem,e.g. low yields.

New knowledge is needed. For instance with the CBB,we simply do not have an adequate method of easilyassessing damage caused by the insect in the field, inorder to judge if or when to apply some control method.We have sampling methods that we as researchers use,but they are time-consuming and we know, from pre-vious experience, that few farmers will use them. Sowe could devise a number of experiments to see whatideas farmers have about the amount of CBB in theirgroves, and how accurate farmers’ notions are, andwhether this might be the basis of a new method (seethe Mexico Case Study for one example). By consult-ing with farmers, we could develop new methods withthem that we might have confidence to believe wouldbe generally acceptable to other farmers.

Adapting ideas . For example, some researchers areworking on new types of CBB traps, and want farmers

to adopt them. They might ask farmers to try proto-types. This could be truly participatory research ifthe researcher evaluates farmer responses and makesadaptations based on their comments. On the otherhand it could be an exercise in extension if one merelyshows farmers how to use the traps and documentsthe rate of adoption.

Farmer Participatory Research (FPR) is research,

not extension. Like other types of agricultural re-search, the goal of FPR is to contribute new knowl-edge, to find things out. FPR is not planting an agro-nomic trial as a demonstration plot. It is not teachingquantitative sampling methods to farmers as a wayof encouraging them to sample.

2.2 FARMER PARTICIPATORY RESEARCH (FPR):

A GUIDE TO SOME OF THE TYPES

We want to give a taste of some different types offarmer participatory research (FPR). The idea is notto get obsessed on methodology, but to realise thatthere are different types of FPR, for different pur-poses. Be creative, and adapt them to your own cir-cumstances. Here are four different approaches:CIAL, Back-&-Forth, FFS4 andZamorano.

4 Strictly speaking, FFS is participatory extension, not research (Kevin Gallagher, personal communication). Nevertheless, even some of its mainsupporters stress how FFS teach farmers to experiment (Dilts 2001). See Vos (2001) for one of many examples which could be given where FFSis part of a participatory research programme.

A coffee farmer tasting his own coffee for the first time

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CIAL (Local Agricultural Research Committee):

technology validation

CIALs were pioneered in the 1980s at CIAT (Interna-tional Centre for Tropical Agriculture) near Cali, Co-lombia. The CIAL is a method for validating tech-nologies, especially new varieties of annual crops(Ashby 1991). The CIAL is now becominginstitutionalised, with booklets on how to organisecommunities to conduct formal experiments. In 1993,CIAT published 13 “Cartillas para CIAL,” large-print,step-by-step guides on how to establish and lead aCIAL (Ashy et al. 1993). Like the name suggests, theCIAL is based on a committee of farmers, chosen byother community members. The CIAL method in-volves a great deal of effort to organise people into aformal structure (president, vice-president, treasureretc.). Researchers give the CIAL a small fund, whichthey use to finance their research. For example, theCIAL gets several new varieties of beans, and rearsthem out on their farms, and evaluates them. TheCIALs work so well for judging varieties of annualcrops that many of them have evolved into small seedcompanies (Ashby et al. 2000). (See the Hondurasand Guatemala Case Studies, this volume, for experi-ences that were somewhat similar to CIALs).

Back-&-Forth: adaptive research

Unlike the CIAL, this is not a widely known method,which is the point: there are a lot of unsung, workablemethods. Back-&-Forth “Ir-y-Venir” was developedin Bolivia in the 1990s to design ox-drawn imple-ments. The context was PROMETA, a DFID-fundedDraught Animal Traction Project at a public univer-sity, Universidad Mayor de San Simón. Back-&-Forthbegins with a diagnostic survey in the communities,to learn what type of animal-drawn tools middle in-come campesinos need. Then a mechanical engineerdesigns a tool (typically a plough, but harrows, weed-ers and planters have also been developed). Research-ers test the tool in laboratory and on-station. Thenthey return to communities for farmer comment, fol-lowed by redesign, lab and station testing and then,after several visits Back and Forth until the farmersare entirely satisfied. Finally it is manufactured(Leonardo Zambrana & Brian Sims, personal com-munication).

Unlike agronomic trials, which usually take a wholecrop cycle, research with machinery is quicker, andBack-&-Forth is well suited to rapid R&D of farmtools. One day we watched Mr Zambrana drive hispick-up truck, with a new plough prototype to a vil-lage near Cochabamba, Bolivia. With some students,he unloaded the plough, borrowed a donkey from alocal farmer and cut a few furrows in another farmer’sfield. Farmers who were harvesting carrots in nearbyfields gathered around. The researchers knelt in thedirt with farmers, who showed them what size andshape of furrows they needed, adding “It’s a niceplough, but to make the furrows we need for carrots,these metal wings have to be a little narrower, but at ahigher angle.” (See the experience with beneficioecológico in the Ecuadorian Case Study, for a nearexample of Back-and-Forth.)

FFS (Farmer Field School): participatory exten-

sion

FFS are now going through a period of rapid expan-sion and change. The original idea was to allow farm-ers to discover the concept of the ecosystem (includ-ing the idea of natural enemies), through field obser-vations, and to decrease the use of insecticides to con-trol brown planthopper in rice (Winarto 1996, Vayda& Setyawati 1995). Farmers met for half a day everyweek, to observe insects and rice plants, while anextensionist facilitated a discussion of whether or notthey needed to spray insecticides, e.g. that the dam-age from insects was not so much real as apparent.Later, FFS resource persons began to notice that somefarmers conducted experiments and invented thingson their own, following FFS. For example, some farm-ers in Indonesia learned through FFS that dragonfliesprey on insect pests. The farmers responded by in-venting perches: sticks in rice paddies where dragon-flies could rest (Ooi 1998). FFS can also be used toexplain the background information that will encour-age farmers to adopt researcher-derived innovations(see the Mexico Case Study).

However, there are criticisms that FFS is too slowand expensive to be cost-effective for extension(Quizon, et al 2000). Also, the quality of FFS maydeteriorate rapidly when it is “up-scaled” out of thehands of master trainers (Matteson, et al 1994). An-

2020

other problem is that there is little spontaneous farmer-to-farmer communication of the FFS message, so thenew ideas are slow to spread from trained farmers totheir neighbours (Winarto 1996, Quizon, et al. 2000).

Can FFS be adapted to research? We suggest thatFFS should be formally adapted as FPR: retool it froman extension device to an R&D method. Besides Pe-ter Ooi’s dragonfly example cited above, YunitaWinarto reports farmers in Java who blended ideasfrom FFS with existing knowledge to generate newtechnology. She gives several examples; in one, farm-ers learned from FFS the life cycle of the white ricestem (WRSB) and learned to notice the adults andthe egg clusters. Previously, the farmers had onlyrecognised the larva of the insect. After training, thefarmers observed adults and eggs of WRSB in ricestubble, and invented a new practice: ploughing ricefields immediately after harvest (instead of just be-fore planting) to kill the moths and their eggs (Winarto1996). This invention would have had much more ofan impact if FFS extension agents had been trained toreport it to researchers, who could have seen it in thefield, validated it, and told other extensionists aboutit. In another case, the CABI IPM participatory re-search with FFSs in Kenya had some positive results5 .Mostly testing neo-traditional, non-chemical controls(spraying milk to control virus, burning organic mat-ter on soil, hot water, chilli etc.) with chemical pesti-cides (Kimani et al. 2000).

In the CFC CBB project, researchers and extensionistsin Ecuador, Mexico and Colombia used a version ofFFS adapted as research, visiting farm communitiesperiodically, to share information with them and in-troduce new ideas to test. (See the Ecuadorian, Mexi-can and Colombian Case Studies for examples of fieldschools adapted for research. See also Vietnam casehistory (Vos 2001) to be included in a CD of theproject, available from CABI Commodities.

The Zamorano method: encouraging farmer in-

ventions

The Zamorano method is based on the simple, factualobservation that farmers experiment on their own, and

on a hypothesis that farmer experiments could be fur-ther stimulated by filling in the gaps in farmer knowl-edge, with short courses on insect bioecology.

The Zamorano method is like FFS in some ways; bothstress training in biology and ecology. A major dif-ference is that FFS trainers return every week: thesessions follow the growth (phenological) cycle ofthe crop. The Zamorano method is based on a shortcourse (about three days) to teach general principles,and teach farmers to observe for themselves. Thislowers costs and raises excitement. We borrowed theidea from the late Elías Sánchez, who used five-daycourses to show soil conservation to tens of thou-sands of Honduran farmers. Zamorano researchersin Honduras taught farmers about insect reproduc-tion, predators, parasitism, and entomopathogens.After training, farmers invented many techniques,most of which related to the conservation and ma-nipulation of large, native predatory insects. Manyfarmers independently invented the idea of sprayingsugar water on crops, to attract ants and wasps tocontrol fall armyworm.

The idea was based on farmers’ existing knowledgethat ants like sugar, combined with the new knowl-edge from the course about the ants and wasps thatare insect predators (Bentley 2000b).

Farmers also learned that parasitic wasps drink thenectar of flowers. One farmer actually experimentedwith flowers of different colours, concluding thatyellow attracted more parasitic hymenoptera to fieldsthan did flowers of other colours (Meir 2000). Meirfound that of 100 farmers who had received Zamoranotraining, 25 had invented something significant (Meir1999). For a critical review see Bentley (2000).

There is some evidence that encouraging farmers toexperiment can be part of a successful, long-termproject (see Boxes 1 and 2). However, our experi-ence has been that farmer experiments are easier tofind than to follow up. Many farmers experiment,but their greatest limitation is that few researchers orextensionists take them seriously enough to validatethem and pass the ideas on to other farmers.

5 Actually, the combination of simple field trials with FFS suggests a kind of CIAL-FFS hybrid: just the kind of creative adaptation we shouldlook for.

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In October 2001, Jeff Bentley and FalguniGuharay visited Pedro Julio Bustos, JuanCarlos Alemán and Carolina Cruz (managerand two master trainers of ESTECA a smallagricultural extension company inNiquiohomo, central Nicaragua). They hadno idea that Bentley had a previous associa-tion with the sugar-water technique when theysaid that they were teaching farmers to usesugar to attract predatory insects to kill pests.Extensionists from Zamorano had taught thetechnique to extensionists in Nicaragua, whostill found it useful 10 years after HubaldaCastro and other Honduran farmers inventedit. By way of comparison, extensionists inCentral America have quietly abandonedmost of the other techniques that were invogue in the early 1990s (like velvet beansas a cover crop, and making compost). Sugarto attract beneficial insects is still acceptableto farmers, because a farmer invented it, andit has farmers’ concerns built into it.

Farmers in Honduras are also still (2002) en-thusiastically reporting the use of sugar wa-ter to control fall armyworm (Robert O’Neil,personal communication).

Box 1 Sugar water, 10 years later2.3 DISCUSSION OF FPR

By their promoters’ admission, the CIALs are bestsuited to adaptive research, especially crop varieties,rather than for inventing new technologies (Ashby etal. 2000). Back-&-Forth also adapts technology withfarmers, but does so in short, one-off sessions; it isespecially well suited to testing new machinery. TheFFS (adapted for research) and Zamorano method bothstimulate farmers to invent on their own, but in bothcases the greatest limitation has been that researchersare not careful enough to document and follow up onthose inventions. If all we do is teach farmers, thenwe are doing extension, which is worthwhile, but it isnot what this manual is about (Box 3). In FPR, farm-ers are our colleagues, and we exchange informationwith them as a way of working together to generatenew information, of which there are three main kinds:diagnosis, bioecological and control tactics. (See Sec-tion 6.3).

Summary of Chapter 2. We have reviewed above avariety of approaches to the subject and we believe indiversity. But like any good scientist, one needs asimple taxonomy to categorize what you are workingon (see Tables 1 and 2 for a summary).

You have to define not only the nature of the problemyou are studying, but your modus operandi. FPR re-searchers must also be interested in the “human” as-pect of their research topic, as well as having the ca-pacity to be a facilitator, rather than a teacher.

.Box 2 Getting slugs drunk

In the mid-1980s, entomologists at Zamorano, Honduras, designed traps to capture bean slugs. The trapswere piles of cut weeds, which farmers had to turn over every two or three days to kill the slugs that hadtaken refuge there. Farmers found the trap tedious and adoption was low (Bentley & Andrews 1991). Butextensionists taught the idea, and farmers began experimenting with other designs of traps. One design,attributed to Nicaraguan smallholder Francisco Vásquez Gómez of Somoto involves burying clay pots upto their necks in the bean field, and pouring some traditional chicha (homemade maize “beer”) into them.In three days, 18 pots captured 289 slugs. Farmers like the pot traps, because they are highly attractive toslugs, and farmers do not have to check the traps every day. The slugs either drown in the chicha, or get toodrunk to take cover from the sun, and die of exposure. Extensionists are now promoting the idea in CentralAmerica (López 1997).

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LEVEL OF

FARMER

PARTICIPATION

1 contractual

2/3 consultative/collaborative

4 collegial

BRIEF

DESCRIPTION

The scientist hiresthe farmer’s labourand land. Research-ers work withseveral individualfarmers.

Researchers workwith committees offarmers, andcommunities.

Farmers do originalresearch, supportedby scientists.

TYPES

Strategic, on-farm re-search.

Adaptive research,e.g. CIALs, back-&-forth.

Zamorano method,FFS adapted for re-search.

USE OF

NUMBERS AND

STATISTICS

Quantitative.Scientist controlsand managesnumbers almostas on-station.

Some numericaldata is taken andanalysed withfarmers.

Little quantifica-tion, or somesimple statistics.

FUNCTIONS

To write a quan-titative descrip-tion of the resultsof many indepen-dent variables.

To adapt a nearlyfinished technol-ogy to local con-ditions.

Farmers inventnovel technology.

Notes: “1” is the least participatory and “4” is the most. Adapted from Biggs (1989); see Section 5.1.

Table 2 Levels of farmer participation, and their characteristics

PLATFORM

CIAL

Back -&-Forth

FFS

FFS adapted forresearch

Zamorano

FOCUS

Validating technology with farmers.

Designing machinery.

Teaching bioecology to farmers.

Teaching bioecology to farmers tostimulate farmer experiments.

Teaching bioecology to farmers tostimulate farmer experiments.

DISADVANTAGES

Farmers are unlikely tocontinue them on theirown, unless they cantransform the CIAL intoa seed-growing busi-ness.

Difficult to adapt to bio-logical topics.

Not traditionally seen asa research method.

Researchers are not al-ways good at followingup on farmer experi-ments.

Researchers are not al-ways good at followingup on farmer experi-ments.

REQUIRES

MUCH STAFF

TIME PER

FARMER?

Yes

No

Yes

Yes

No

Table 1 Comparison of five participatory methods

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If researchers and farmers work together on an experience in which:

� Only researchers learn: it is conventional research, not participatory� Only farmers learn: it is extension, not research� Farmers and researchers learn something: it is participatory research� Neither farmers nor researchers learn anything: it is just goofing around

Box 3 How to tell if an experience is participatory research

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Initial contact with farmers can be difficult

The players. The three main players in FPR are the

farmer, the extensionist, and the researcher. Eachgroup has its own agenda and background. At the riskof stereotyping each of these groups, they are, regard-less of their country of origin, adapted to a similarset of circumstances, to which they have respondedin similar and rational ways, which we describe inthe following sections.

It is probably obvious to most readers that research-ers and smallholder farmers are from different classbackgrounds. What is perhaps less obvious is thatthere are social differences between researchers andextensionists as well. Most researchers have middleclass backgrounds, may have advanced degrees(Ph.D., M.Sc.) and have gone to elite secondaryschools. Many have international experience andspeak English. Extensionists may come from middleincome families, but some are also the children ofsmallholder farmers or of small town shopkeepers,and have struggled to attend a public university intheir own country. Most have a lively command oflocal and national languages, although not necessar-ily of English (Boa, et al. 2001).

3.1 THE FARMER

The farmer’s mind-set. Smallholder farmers valuehard work and private property. They are eminentlypragmatic, with little romanticism (they will not hesi-tate to build a cement-block wall onto a 200 -year-old granite barn). They value money and are reluc-tant to spend it, preferring to save it to buy seed, orused trucks or other useful property. They are busy,and time is precious to them. They are moderatelyhospitable, but often suspicious of outsiders. Theytreat outside knowledge with a touch of scepticism,the way a scientist treats a hypothesis. They have of-ten not had proper medical care, and illness and earlydeaths have struck many families, leaving them with

a permanent sadness. One of the things they like mostabout their lives is being their own boss, not havingto punch a time clock. Yet, they don’t especially en-joy their work, because it is backbreaking, tediousand dirty; they are happy if they can afford an educa-tion and a better future for their children. Most havehad just a few years of schooling, and some cannotread. A few are avid readers. They appreciate the valueof their own practical experience.

Four kinds of farmer knowledge: deep, shallow,

missing and mistaken. There are four basic types oflocal knowledge, depending on whether the things inthe natural world are important to people or not, andif they are easy or difficult to observe (Table 3).

Farmers’ worries. Farmers worry about going hun-gry, about not being able to feed and clothe their chil-dren. In some countries where land title is insecure,they fear having their land confiscated by lawyers andrich people. They worry about thieves (or maraudingarmies) stealing from them. They worry about the ris-ing prices of the inputs they buy, and the falling pricesof the goods they sell. Contrary to naïve opinion, tra-ditional smallholder farmers are not in the least afraidof new technology. They are eager to adopt changesthat will improve production, but they are worried thatthe extensionist or other outsider may not know whathe is talking about, and may make exaggerated claimsfor the new idea, or that the new technique will in-crease risk (to which farmers are averse). They worryabout insects and diseases; they believe that all in-sects are pests and that any insect or leaf spot can bedangerous to their harvest. Pesticide companies profiton such misperceptions.

“The secret of getting ahead is getting started. Thesecret of getting started is breaking your complexoverwhelming tasks into small manageable tasks,

and then starting on the first one.”

Mark Twain

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Easy to observe

Difficult to observe

NOT OF PERCEIVED IMPORTANCE

TO LOCAL PEOPLE

Shallow knowledge

People do not pay much attention to some thingsthat they can observe, because they do not con-sider them worth looking at.

Example: Farmers have observed web-buildingspiders in coffee groves, but may not have ap-preciated their role as natural enemies of pests.

Missing knowledge

Local people are unaware that some things ex-ist, because they are small, nocturnal, camou-flaged, and because necessity has not forced thepeople to notice them.

Example: nematodes, parasitic wasps, micro-scopic fungi.

OF PERCEIVED IMPORTANCE

TO LOCAL PEOPLE

Deep knowledge

Farmers know in detail the thingsthat they can observe, and that theirwork forces them to look at.

Example: Coffee growers know thatbored berries harbour beetles andwhether or not this might affect thesale price.

Mistaken knowledge

Smallholders know the thing exists,because it is so important to them,but misunderstand it because it is dif-ficult to observe.

Example: farmers do not understandhow the CBB spreads. Some con-clude that the insect comes from theirneighbour’s plot, when it may actu-ally be reproducing within the grove.

Table 3 A classification of farmers’ knowledge

Source: Adapted from Bentley & Rodríguez 2001

Farmers’ constraints. Farmers are limited by theobvious: capital. Some farmers are constrained bylabour, but have plenty of land (extensive farming),while others are constrained by land, and lavish theirlabour on it (intensive farming). In most countriesthey are constrained by a near total lack of politicalpower. Many farm communities are unorganised.Their children attend bad public schools, which of-fer basic literacy, nationalism and disdain for theirown cultural and class heritage. Rural schools teacha nagging sense of inferiority, but not enough scien-tific concepts to make sense of pests and disease.

Above all, smallholders are smart. They may lack informal education but they have skills and experiencesthat we researchers do not. For example, farmers inHonduras, Mexico and Colombia could identify “hot-

spots” (high concentrations) of CBB populations thatresearchers thought could only be detected by sam-pling. In Mexico, when researchers told farmers theywanted to create IPM plots to control CBB, the farm-ers quietly took them to the largest hot-spots in thecommunity. The villagers chose the hot-spots as theplaces that would most clearly show the success orfailure of the new ideas. The scientists didn’t realisethat they had set up their trials in the most infestedareas until villagers told them (see Mexico CaseStudy).

What farmers think of you, the researcher. Theythink you know everything, until they get to knowyou. Then they are surprised to realise how many ba-sic things you do not know1 . You cannot train an oxteam, or prepare lunch for 20 hungry workers. Many

1 Our apologies to the scientists who are also farmers, those who grew up on farms and have not lost their roots. This is much more common incoffee than in other crops. It is especially common in some countries like Colombia, that are proud of their coffee culture, where researchers spendthe weekend growing coffee on their family farm. This is an important distinction between participatory research with coffee and with other crops.

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of you even have trouble just walking on the steepmuddy paths of a farm. You call the simplest thingsby mysterious words, yet you often cannot recognisethe most basic crops and weeds on a farm. And oncethey get to know you better, it gets worse. They realisethat you only know your one specialty: you may knowthe bugs, but not know how to fertilise coffee. Or youknow the diseases, but cannot repair a pulping ma-chine. Or you are the anthropologist who knows howto ask a lot of questions, but does not recognise ro-busta coffee when he sees it. In spite of all that, thefarmers still value you, because they know that youknow things they do not know. They want you to keepvisiting them, and they crave your respect. They wantyou to talk to them like adults.

3.2 THE EXTENSIONIST

The extensionist’s mind-set. Most extensionists aremen, or young single women. Extension work oftenrequires one to be away from home for long days at atime. Most extensionists are kind and easy to talk to;they like people. Most were motivated to go into ex-tension by a desire to help people. If left alone in acommunity, they tend to spend their free time playingcards or football with farmers. Yet they don’t mindbeing treated with a touch of deference; in LatinAmerica most extensionists like farmers to call themby a university title (ingeniero). Few extensionists sayto farmers “just call me Juan”. Extensionists have beento university, or at least to technical secondary school.They read, some more than others. They all can write,but few enjoy it, and so extensionists are not enteringthe historical record as much as they could. They iden-tify more or less with the middle class, but their ma-terial aspirations (car, house) are frustrated by theirlow salaries. They value education, but few can af-ford to send their children to elite schools. Many ofthem have traditional religious values, as well as abasic scientific education.

The extensionist’s worries. They are afraid of los-ing their job (except in some remarkable institutionswith solid job tenure for extensionists). Their biggestfear is losing “credibility” in front of farmers, of mak-ing a recommendation which later does not live up toits promise.

The extensionist’s constraints . Few extensionistshave the logistical support they need. It is a rareextensionist who has a car or a motorbike. We havemet extensionists who sleep in schoolhouses, with-out plumbing or electricity, eating tinned sardines.Conditions are usually a little more comfortable incoffee-growing areas, because people and money(used to be) more plentiful around coffee, but mostextensionists have had to rough it at least sometimes.Their travel and expense money is frequently insuffi-cient. They rarely have enough well-written, well-il-lustrated, pertinent technical literature to help themteach farmers. They are usually unable to buy any extratools or supplies. Many have poor access to comput-ers and e-mail; even though there may be both in thelocal office, the extensionist either does not have thetime or the information to make full use of them.

What extensionists think of you, the researcher. Ingeneral he respects you, for your education and yourstanding in the institution. Most extensionists wouldlike to be listened to a little more, to be taken just abit more seriously by researchers. Extensionists cancome to resent researchers who “release” technolo-gies that worked on-station. When those techniquesdon’t work on-farm, the extensionist doesn’t like be-ing blamed by the researcher (“It would work if theextensionists would just teach it right” is a commonresearcher complaint which extensionists resent).

3.3 THE RESEARCHER

The researcher’s mind-set. Why are you thinkingof doing this sort of research? Participatory researchcan be rewarding for scientists who like going intothe field and talking to people. Some people are natu-rally good at this, and most researchers have the ba-sic people skills. We can all learn to improve; the fol-lowing chapters provide some pointers.

The researcher’s worries. Some researchers are wor-ried about whether they can publish the results. Inmany institutes pay rises are based on publications,so anything that is not considered publishable in theirtarget journals is not interesting to them. Others areconcerned about what their colleagues may say (“It’snot science”). If you are one of these, just remind scep-

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tics that one of the most important crop protectiontechnologies for a perennial crop was invented byparticipatory research. Bordeaux mix was first con-cocted by a French farmer in the late 19th century. Hewanted to spray something obnoxious on grapes thatwould repulse passers-by, so they would stop pluck-ing bunches from his vines that hung over a path. Aplant pathologist noticed that the grapes were free offungal disease, and he validated the mix as a fungi-cide (Lang & Clutterbuck 1991). You may be the re-searcher who works with farmers to invent the nextBordeaux mix.

The researcher’s constraints . Lack of time, espe-cially when administrators can invent paperwork andmeetings faster than researchers can avoid them. Oneof the main failings of participatory research so far isthat there has been a real shortage of senior scien-tists in the field, working with farmers. Agriculturalscientists have delegated so much of the farmer par-ticipatory research to technicians, extensionists andsocial scientists that FPR has not had enough seriousfield testing to become a standard method.

Researchers are constrained by a certain conceit thattheir ideas must be adopted by farmers (“How can weget these farmers to adopt our ideas?”) The answer is:invent the things that farmers want to adopt. Partici-patory research helps you to do that.

And in all fairness to agricultural scientists, a wordmust be said about social scientists. Most know toolittle about agriculture to be of much help in research.Most are from the city and have little biological train-ing.

The academic ones have been afflicted with romanti-cism, Marxism and post-modernism to the degree thatthey are simply irrelevant, at odds with the agricul-tural scientists’ basic project. Even anthropologistswho have studied agrarian communities tend to knowonly the farmers’ point of view, and so have difficultyrelating it to the scientists’ perspective. It takes timeand patience for “aggies” and “anthros” to learn towork together.

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“Successful innovation requires supporting institu-tions. There are 48 countries with more than a

million people (in 1995) and with at least half ofthese living in tropical areas: with a total populationof 750m, they took out just 47 of the 51,000 Ameri-

can patents issued to foreign inventors in 1997.”

Jeffrey Sachs

“To see things in the seed, that is genius.”

Lao-tzu

In the previous chapter, we dealt with some funda-mental characteristics of farmers, extensionists and re-searchers. Now we are going to discuss interactionswith farmers and extensionists in order to achieve thegoals of research. And the logical place to start is work-ing with extensionists and farmers to choose the rightresearch topics.

4.1 BASIC FIELD SKILLS

An excellent way to learn about farmers and their prob-lems is to go live in a village for a year, working, eat-ing and talking with people the whole time. It is sucha useful, bedrock experience that it should be manda-tory for agricultural scholars. Few mature researchershave the time, but fortunately there are quicker meth-ods (see especially Section 4.2, below).

Attitude . More important than the method you use, isthe background education and goodwill you take tothe field. As part of a previous project, we once broughtscientists from Cornell to meet farmers in Honduras,to listen to talks and to go to farmers’ fields to seepests. The researchers complained that they had beeninvited to “a growers’ meeting”, so of course they gotlittle out of the experience. Whatever you do, get intothe field and talk to farmers. The PROINPA Founda-tion in Bolivia occasionally closes the office and takeseveryone, even the secretaries and the accountants, tothe field to meet farmers and to climb up to their fieldsto see the test plots they have planned with research-ers.

4.2 LEARN FROM EXTENSION AGENTS

Time is always short and most researchers do not knowmany farmers, so they use extension agents to help

contact the farmers. In most countries it is essentialto approach extensionists first to introduce you tofarming communities; it ensures that the farmers re-ceive you with less suspicion and it helps avoid later“turf wars” between research and extension staff. Ithas some drawbacks, e.g. the farmers naturally asso-ciate the visitor with the people who take him or herto the village, but given time, the villagers and theresearcher can get to know each other in their ownright. Unfortunately some extensionists are ill-suitedto the role of agrarian tour guide, and react by inter-rupting farmers and trying to explain the farmers’business to the researcher. On the other hand the ex-tension agent has much valuable experience, whichcan help the researcher get to the point quicker withfarmers. For example, researchers in India tried to con-vince extension agents to tell farmers to pluck earlyblossoms from robusta coffee, as a way of eliminat-ing habitat for the CBB. One senior extensionist latertook one of the authors to a coffee grove, grasped acoffee branch and picked off a few flowers, showinghow this was not only time-consuming, but also dam-aged the blossoms that would produce the main crop.

Tips for working with extensionists. Extensionistsare professional information brokers, who are used torelating outside information to farmers. With somepreparation, most extensionists can also broker infor-mation in the other direction: from farmers to scien-tists (Boa et al. 2001, Bentley et al., in press). In gen-eral:

Extensionists know the area better than you do.They can help to characterise an area based on agro-ecological principles, (“These are the areas we callthe high-country, and this is the low country.” Or“These are the valley bottoms used for commercialcattle, and these are the hillside areas for smallholdercoffee”). Work out areas to visit with extension agents,rather than just turning the agenda over to them, thishelps to see a representative cross-section and allowsyou to start to see their perspective on the area. Whenleft to their own devices, extensionists often drivevisiting researchers to the most far-flung areas, on thewell-meaning assumption that one needs to “see” themost different areas.

This can make for nine hours of looking out the wind-shield and one hour talking to farmers. Try to makesure beforehand that most of your time in the fieldwill be spent on-farm rather than in-car. If an exten-

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sion agent wants to take you to very far places, ask ifyou can stay overnight there, to spend more time withfarmers.

Extensionists know the farmers better. They knowhow to greet people, whether or not one needs to askpermission before walking onto a farm, and the rightchoice of words. Extensionists know which days aredevoted to festivals and other events, when peoplewill not be working, and may not want visitors. Insome areas, farmers are suspicious of outsiders and atrusted extension agent provides the introduction youneed to start the interview. The down-side to this isthat extension agents also have a bias towardswealthier or at least middle income male farmers whotend to be early adopters of new technology.Extensionists may call them “progressive” farmers,and assume that they adopt innovations because theyare clever.

The extensionists almost always miss the fact that,besides being smart, the progressive farmers are alsousually people with land and with a large, healthyfamily so that the chores get done, even while thefarmer is taking short courses or entertaining visi-tors. Other farmers struggling with illness or largedependency burdens may be just as eager to learn,but don’t have as much time to go to meetings. Ex-tension agents also work in a few communities, notin the whole area. Work this out beforehand and tryto visit some women, poorer households, and othervillages. All extensionists have their favourite farm-ers who may be some of the friendliest or most com-pliant individuals. They are easy to talk to, and it canbe tempting to meet one “progressive” farmer afterthe other, but beware of thereby selecting an unrep-resentative group to work with.

Extensionists know a lot about local problems . Forexample, they know the common names for the area’spests, and can describe most of them in scientificterms (Bentley et al., in press). Extensionists can alsotell you when the coffee harvest is, how long it lasts,if local people prune shade trees themselves or hirespecialists to do it. A good extensionist can help youto ask good questions like “Would you rather growcoffee or maize, and why?” (This is an example of aquestion Ecuadorian extensionists asked, based ontheir understanding that people in the Jipi Japa prov-ince were switching from coffee to maize, but debat-ing it among themselves as they went along).

Be aware that the extensionists have their own

agenda, featuring the (usually narrow) range of con-cerns dealt with by their own institution. Don’t let anextensionist distract you by directing the conversa-tion repeatedly to, say, organic fertiliser, or certifiedseed, or the introduction of pine trees, unless you havebroader interests. NGO extensionists tend to have ananti-chemical bias, and so farmers may downplay theirreal use of agrochemicals in front of NGO staff.Extensionists may have certain unselfconscious so-cial agendas, for example, our extensionist colleaguesin India identified with full-time family farmers, andtended to avoid landless labourers and part-timesmallholders, as well as plantation estates.

The period of stupidity: credit schemes. Althoughit is not as common as it was in the pre-liberalisationera of the 1980s, some extensionists still work as creditagents. Indonesian anthropologist Yunita Winarto de-scribes a classic credit scheme in Central Lampung,on Sumatra, from the 1970s and 80s, which farmersin retrospect now call “the period of stupidity” be-cause the credit scheme obliged them to buy pack-ages of seed, fertiliser and insecticides. Farmers wereorganised to buy the package, and government agentswere assigned to oversee its adoption as a whole.Farmers were allowed little creativity for adoptingparts of the package (Winarto, in press).

The Indonesian scheme is not unlike credit packagesfor maize that Bentley saw in 1987 in Honduras. Ob-viously, extension agents working in credit schemesare biased to see if farmers are adopting the wholetechnology package in an uncreative way, as well asmaking their payments. Credit agents may have ac-cess to communities, but approach them with caution.

Some extensionists will have good ideas . And theywill all have something to say. Some extension agentstend to interrupt farmers during interviews. Askingextension agents’ opinion before going to the fieldcan help them to feel that they have already had theirsay, so they will be less likely to interrupt farmers.You may want to assign extension agents the role ofasking the questions during the interviews with farm-ers. This gives the extension agents a meaningful role,one they play well, and helps them resist the tempta-tion to contradict farmers.

Some will resent you. Because you are a foreigner,or are from the capital city, or because you make more

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An informal setting can be best (spot the extensionist)

money than they do, or because you are interruptingtheir busy schedule to do something they may not in-stantly identify with. This is not usually as big a prob-lem as it seems, just something to be aware of at thestart of the day, if the extensionist seems cold. If youtreat them with respect and courtesy they usually re-spond in kind. Always try to work with severalextensionists, to get a balanced picture and avoidspending too much time with someone who may beatypical.

The entourage . When you are just starting out, andif you are collaborating with an institution that doesnot quite trust you yet, you may think that you aregoing to the field with one extensionist, only to findyourself with two or three extensionists, their super-visor, his supervisor, someone from research, a driver,a student, even a photographer. By the time you realiseyou have an entourage it’s usually too late to do any-thing about it. If the farmer is not nervous around sucha crowd, the host extensionist will be. Ask the farmerto show you her farm. Most of the entourage will thenbreak into small conversation circles and you can talkwith the farmer and the extension agent. Hopefullyyou will keep working with the institution and thecommunity until they relax with you, and you canwork with smaller groups of people.

Extensionists are sometimes wrong . We have heardextensionists say that the three main nutrients forplants are “potassium, phosphorus and sulphur” (in-stead of nitrogen). And while most can tell a co-leopteran from an orthopteran, many can spout offscientific names of insects without being able to tellyou which family they belong to. Take it in your strideand don’t play know-it-all with them.

Most are glad to receive some attention. Someextensionists are posted to remote locations, and mayspend most of their time alone in communities. Manyare lucky to even have a motorcycle to get to theirworksite. Showing some appreciation for their workusually goes a long way to overcoming the resent-ment they may feel about the intrusion into their rou-tine, when a carload of people bursts into the village.Before going to the field with extension agents, spenda few hours discussing the topic and the community.This can be done with individual extensionists or witha group. It helps to:

� Generate hypotheses about farmers.

ACTIVITY 1Talk to an extensionist or a group of extensionists

about the local farming system and about farmer

knowledge. Ask them key questions about coffee

growing, farmer knowledge and coffee pest prob-

lems in the community.

Form one or more hypotheses and identify topics

to ask farmers later. Start by identifying topics that

extension agents are not clear on. For example, in

Sucre, Bolivia, extensionists listed several popu-

lar terms used by farmers to describe fruit tree

diseases. The extensionists disagreed among them-

selves over whether polvillo meant the same as

ceniza , and what were the exact symptoms of each

one. They agreed to ask farmers about this in the

field.

Avoid formal meetings at first

� Give the researcher insight into the localextensionist’s attitudes about farmers.

� Let the extensionists feel that they have been lis-tened to, so they can relax during the interviewwith farmers.

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4.3 APPROACHING THE FARMERS

Selecting farmers to interview. Bellon identifies fourways of choosing people to talk to: incidental, key,randomly selected and self-selected (Bellon 2001).

� Incidental informants are those people thatresearchers happen to meet, including shopkeepers, or farmers asking for a lift by the sideof the road. They are usually easy to meet andtalk to, but be careful to re-confirm anythingthey say with other people. Incidental infor-mants may be biased, and researchers do notusually know their role in the community.

� Key informants are people with specific,important roles in the communities, and includehealers, leaders, master farmers, rural schoolteachers. They are not always representative ofthe community, but usually are articulate andare respected for having certain kinds of spe-cialist knowledge.

� Randomly selected informants are chosenat random off a list of the population (thesociologist’s “universe”). They may be repre-sentative, but in rural areas of Latin America,Africa and elsewhere there is often no list oflocal households, so researchers have to makedo with an opportunistic sample of people theycan manage to meet. But keep in mind that theideal is to talk to many different kinds of people,who represent the different groups in the com-munity. Be sure to talk to women, elderly, eth-nic minorities, people far from the road, thelandless, labourers, smallholder farmers, and notjust the “progressive” farmers the extensionistwill try to steer you towards.

� Self-selected informants are people whoapproach the research team. They are invari-ably articulate and may be farmer experiment-ers, or people who are eager to learn about newtechnology. They may also be looking for po-litical connections, employment or a ride to thecity (adapted from Bellon 2001).

Recomendations.

� Identify objectives or hypotheses before go-ing to the field. Sit down with extensionists orother colleagues beforehand and agree on whatare the specific things to discuss with farmers.

� Work in two-person teams of an interviewerand a note taker. Designate one person to con-duct the interview. This person may be anextensionist or another person who is fluent inthe local dialect. The interviewer will not takemany notes, since he or she needs to maintaineye contact with the person being interviewed.Designate another person to take notes in a blanknotebook. This person may say something fromtime to time, but does not speak nearly as oftenas the designated interviewer. If there are threeor four people on the interview team, still desig-nate just one person as the interviewer. The restshould listen. The more people there are on theinterview team, the more unwieldy it is, and themore difficult it is for the farmers to relax.

� Avoid town meetings, at first. At early stagesof research, e.g. when learning about farmer de-mand, talk to individuals or small groups of ru-ral people. Do not meet with the whole commu-nity until you are ready to plan research with acommunity (see Chapter 5). Extensionists areoften eager to call the whole village together,when the team really just needs to talk to a fewpeople. Town meetings are frustrating for ev-eryone because they waste a lot of thecommunity’s time and energy, and because outof 30 people, only two or three local people domost of the talking. Interviews with individualsand small groups give marginalised and shypeople the chance to talk.

� Take notes, at some time or another. Anthro-pologists routinely take notes during interviews,or record the interview. Extensionists and agri-cultural scientists are often reluctant to write infront of farmers; they think this puts the farmersoff. Usually it doesn’t. On the contrary, thefarmer may feel pleased that someone is payingattention to what she has to say. But if the re-search team is uncomfortable taking notes, theirbody language will communicate that to the

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farmer, who may then feel ill at ease. Farmersare much more likely to feel threatened by a ques-tionnaire form than by a blank notebook. Haveyour notebook in your hand or get it out soonafter arriving. Open it without making a fussabout it and start jotting things down. If the farmerlooks at you, you may say something like “I wantto write down what you tell us, because it is im-portant and I don’t want to forget it.” If you arehonest, the interviewee may sense it, and trustyou. If the farmer seems uncomfortable, stop tak-ing notes, but you must sit down with the teamimmediately after the interview and write an ac-count of it. But this takes a lot longer.

We do not recommend recording interviews, unlessyou really need a verbatim account. Recordings mustbe transcribed to be of much use, and that takes abouteight hours per each hour of tape. If you do tape record,you must have the person’s informed consent. Turnon the tape recorder and speak into it, (“It’s the eighthof April, 2003, and we’re interviewing Anselmo Garcíain Santa Rita de los Imposibles. May we record you,Mr García?”). Unless he says “yes” on tape, you can-not show informed consent.

� Tell farmers who you are and what you’restudying, and who is paying for the study. Theyhave the right to know, and the honest informa-tion may help reduce their anxiety, and get themonto the topic. For example, “My name is PatSmart, I’m a British consultant doing a studyfor some North American coffee buyers. We areinterested in knowing more about how familyfarmers in Latin America grow coffee.”

� Be respectful. Address them as you would asenior colleague, especially if the farmer is olderthan you.

� The farmer has the right to refuse the inter-view. If the farmer is eager to be interviewed,she will ask you to come onto the porch, willoffer you something to eat or drink, or in someother way show a willingness to be interviewed.Do not plead with farmers to talk to you. If farm-ers resist being interviewed just say good-bye.In some parts of the world, you may need to beintroduced before people will talk to you.

� Be a sympathetic listener. Saying “mm,hmm” from time to time, and use the right bodylanguage to show that you are interested in whatthe interviewee is saying. Phrases like “tell usmore about that” often encourage a person toopen up.

� Be flexible, and open to new ideas. Eventhough you have outlined some topics of inter-est beforehand, allow yourself to be surprisedand interested in new twists.

For example, in Ecuador in 1999, while discussingshade and cacao, farmers surprised us by pointing outdifferent ways in which cacao was occasionally theshade for coffee (Bentley et al. in press). If the inter-viewee gets way off your mandated topic, let himspeak for a while and bring him gently back by say-ing something like “What you’re saying about thewater-users’ association is really interesting, but get-ting back to the subject of coffee farming…. Can youtell us a little more about what you said earlier, aboutthe first time you realised that you could do withoutinsecticides?”

� Don’t interrupt a farmer who is speaking.Do not mistake a short pause as a chance to leapin. Wait for a few seconds, and if they have re-ally stopped talking, ask a question (Alexiades1996).

� Introduce the theme in broad terms, to avoidintroducing too much bias. For example if weask farmers about the berry borer, they tend toconcentrate on it, exaggerating its importance.A better tactic is to start talking about coffee, orabout farming in general, and work into the morespecific themes, like individual pests, or shadetrees. This gives you a chance to see how im-portant the specific ideas are in the farmers’broader context.

� Don’t interrogate. Ask as few questions aspossible. Especially in the beginning. People liketo be listened to. Each question costs you rap-port. Not asking questions allows farmers to feelthat we have listened to them. They are thenmore likely to relax and answer a few questionslater in the interview. Listen to the story they

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want to tell before breaking up their train ofthought with questions.

� Do not put the words in farmers’ mouths.Follow the thread of the conversation. If you doask questions, ask clarifications (“What do youmean?” Or, “Why did you do that?”) Or askquestions that follow on the topic (“You weretelling us about pruning shade trees, how do youdo that?”). Do not ask questions that can by an-swered by “yes” or “no.” E.g. point to some dis-eased leaves and ask the farmer about them.This is a better way of getting onto the topic ofdiseases than saying “Do you have koleroga?”

� Avoid jumping in. One problem with largeinterview teams is that one colleague may wan-der off, looking at plants and pests on the farm,then comes back blurting out exciting questionsabout what he has seen. This often knocks thefarmer off track, just as she was getting to theinteresting part of some other topic. If a col-league has been interviewing a farmer, don’tcome in and start asking questions. Those top-ics may have already been covered. Your ques-tion will probably be, at best, a non sequitur.Listen for a while and wait until the farmer getsonto your topic, or until there is a long pause,and people are willing to have a new topic in-troduced.

� Timing of questions. Once you have devel-oped some rapport with the farmers, and theyrelax, you can ask them a few questions in thesecond half of the interview.

� Avoid asking farmers their land size, in-come and other economic details. These ques-tions are about as personal as their sex-life. Wemaintain rapport and learn a lot from the farm-ers by avoiding certain pointed questions, butwe have to sacrifice some quantitative informa-tion in order to do so. If you really must haveeconomic details, ask about them later in the in-terview, and be sensitive to farmers’ discomfortabout discussing them.

� Don’t preach. This is especially importantwhen extensionists or social “promoters” help

conduct the interview. They often cannot resistbreaking in with lectures on their favourite top-ics. This biases the farmer, who quickly learnsto say what he thinks you want to hear.

Do not sacrifice the objectivity of the interview bywearing your heart on your sleeve. For example, afarmer in Nicaragua once asked us if we would liketo see his macaw. He proudly showed us a dead, juve-nile macaw, which he had killed on the farm. It hadbeen amateurishly dried into a grizzly wad of feath-ers, and nailed to the living room wall. We avoidedcriticising him for killing wild birds, but went on withthe interview. There will be plenty of time later in theproject to address dead birds and other issues thatcome up in interviews.

� Do not become exasperated with people. AColombian colleague once wanted to know whysome farmers still planted the caturra variety ofcoffee instead of the Colombia variety. We meta farmer and her mother, who graciously invitedus into their two-room plank house to talk aboutcoffee growing. But when she said that “caturrais a good variety” our colleague actually tookoff his cap and threw it on the floor in exaspera-tion. Of course, the farmer immediately stoppedtalking about the variety and we never did learnwhat she liked about it.

� Take an hour or less for the interview. Leavebefore people start to yawn and look at theirwatch. If you need to talk more, come back later,or go to another farm.

Don’t interrogate. Farmers find questionnaires

more threatening than a blank notebook. With

questionnaires, less is usually more.

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� Ask the host family if they have any questions foryou. This is a nice way to break any tension causedby the questions the team has asked, and it starts toend the interview. The farmers may smile and say no,or ask again who you are and who you work for, orthey may want to know how to control a pest.

� Ask people’s name. It is often polite to be able toaddress people by their names during the interview.The extensionist usually knows the interviewee’sname beforehand, but male extensionists may notknow the names of the women. If you have to inter-view people without being introduced, someinterviewees may be nervous about telling you theirname until the end of the interview. If you do not knowthe person’s name, ask before you leave.

� Thank them for their time and say good-bye.

� Later, review your notes together as a team. Thismay be done in narrative form (“he said this, then hesaid that”). Extension agents may not have enoughtime to help you analyse the interview, or their onlyfree time may be in the car. After several days of in-terviews, the team may start to feel overwhelmed withthe new information from interviews, or they maywonder if they are learning all the key ideas. It helpsto take an inventory every few days, as a team. Drawup a table on large sheets of paper (the kind used fordiscussions at “workshops”), to compare the majorpoints that have emerged from various interviews.

4.4 LEARN FROM FARMERS

Everybody knows something, but nobody knows

everything7 . Farmers do know a lot, especially aboutthings they regard as important, and which they havethe tools to observe. For example, Quechua farmersin Bolivia can pick up a handful of moist, black soiland squeeze it between their fingertips to show thetiny, black seeds of weeds8 . These farmers knowwhich weed seeds are more likely to survive the tripthrough a sheep’s guts, and end up in the manurespread on next year’s potato crop. But farmers don’t

know everything. They tend not to understand howthe market sets commodity prices, the structure ofchromosomes, the existence of insects that are natu-ral enemies of pests etc.

Ethnoscience . Interest in local knowledge goes backa long way, but not in development circles. Anthro-pologists have studied local knowledge since the1960s, with a set of formal techniques and theorycalled ethnoscience (for example, Berlin 1992,Conklin 1962, among many others that could be cited).

The American anthropologist Eugene Hunn’s thought-ful book The Big River describes how Indians alongthe Columbia River still rely on and know a great dealabout wild plants (Hunn 1990).

ACTIVITY 2

Go to the field with the extension agents. Ask farm-

ers about growing coffee. Have a small set (4-7)

of pre-designed questions, based on topics that

emerge from Activity 1. For example, the first

activity is likely to indicate that some farmers per-

form some cultural controls (e.g. gleaning) while

others do not. You may want to ask the farmers to

describe their activities, paying attention to which

cultural controls they mention, and asking them

why they perform those tasks.

Agree beforehand who will ask the questions. (It

may be one of the extension agents.) The impor-

tant thing is not who asks the questions, but lis-

tening to the answers.

Don’t ask them leading questions. For example,

don’t say “How do you control CBB?” The ques-

tion suggests that the farmer should be using some

active control, and he may exaggerate the impor-

tance of insecticides in his reply. Better questions

include “What are the important tasks in coffee

growing?” And if he does not mention borer con-

trol, a more specific question that is still not too

leading is “What do you do when you have CBB

in your grove?”

7 This was a favourite saying of the late Elías Sánchez (“todos sabemos algo, pero nadie lo sabe todo”), though we are not sure who said it first.8 Especially of the invasive species Spergula arvensis.9 For example, anthropologists working with the Kofyar on the Jos Plateau of Nigeria found that the agricultural calendar was essentially full.

New crops had been fitted into the system until there was no slack time left (Stone, Netting & Stone 1990).

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A Place Against Time by the British anthropologistPaul Sillitoe is an encyclopaedic description of envi-ronmental knowledge of a traditional people in NewGuinea. Sillitoe shows that for some subjects (e.g.sweet potato varieties), local knowledge is astound-ingly complex. For other topics, traditional knowl-edge is fragmentary or incomplete (e.g. pests and dis-eases and geology) while for others (like soils) localknowledge is deep and detailed, yet bears little re-semblance to modern scientific accounts of the samesubject (Sillitoe 1996). The gist of ethnoscience islearning local categories for things (insects, plants,diseases, people etc.), and the meanings of those cat-egories. (See Annex, an outline of ethnoscience).

During initial interviews with farmers, we can elicittheir terms for social categories (e.g. wealthy farm-ers, poor farmers, labourers, cattle owners etc.). Farm-ers can tell us which local families belong to whichcategories, which may help to ensure that all groupsare represented in the research. Farmers may be askedto draw calendars of their activities (including off-farm labour), which will allow researchers to identifylabour bottlenecks9 . Local classifications of soil, cli-mate, crops etc. will give scientists a starting placefor studying local knowledge (for filling in gaps infarmer knowledge, learning new information, design-ing collaborative research; see Bellon 2001).

4.5 OBSERVE FARMERS’ BEHAVIOUR

Social study of behaviour. For example, coffee ber-ries dropped onto the ground are a habitat for CBB,

so in every country we need to know what percentageof farmers pick coffee off the ground (or allow othersto do so). In Ecuador, we know that during the har-vest, some labourers cut open two sacks and sew themtogether, and then carefully gather all the berries thatfall on them. But we do not know how common thispractice is. These are just some of the agronomic prac-tices that influence CBB populations. Some of themmay seem trivial, but they are not and we need to knowabout them. Researchers could either validate this in-formation or use it as the basis for a new technology.

Visit coffee groves to see what the production lookslike. Look around to see if the groves are weedy, ifthere are coffee berries on the ground, or coffee seed-lings sprouting from fallen berries from previous har-vests.

4.6 LEARN FARMERS’ RESEARCH NEEDS

Appraisals. Early in a project’s life, the staff needs aformal learning experience with farmers, in order torefine ideas about what the existing farming systemis and what the real research demands are. We give afew examples of method below. The main idea is togive the reader a flavour for the wide range of meth-ods that exist. There is no orthodox method, and newones can be created and old ones can be combined. Acreative research team designs a practical study thatis consistent with the topic at hand.

Questionnaires. Long questionnaires are the mostabused and over-used social science tool in existence.As Robert Chambers pointed out years ago, they tendto be too long, they ask the wrong questions, and mostprojects do not budget enough time to analyse thenumbers or write the results (Chambers 1983). Betterquestionnaires are shorter, and more to the point, basedon a qualitative understanding of local people. Thisproject started with a questionnaire in most countries,and they were fairly well done, largely because thestaff already had a sophisticated idea of what to askthe farmers. The questionnaires suggested that mostof the farm families had under five hectares in coffee,and most also had some other crops. Most hire labour,used insecticide and had had problems with CBB.

The Honduran questionnaire reported that 36% offarmers claimed to apply insecticides only on hot-

ACTIVITY 3

Visit a community and participate in or observe

people perform a task related to coffee growing.

For example, watch people harvest, weed, glean, or

plant coffee. Participate if you feel it is appropriate.

Be able to describe the task:

� Amount of labour required

� Tools needed

� Productivity

(See the Ecuadorian case study)

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spots. Qualitative interviews (and formal studies, seeMexico and Colombia Case Studies) later supportedthe idea that farmers can identify hot-spots, and ap-ply a control measure just where it is needed. Wheninterpreting questionnaire data one must always bearin mind that the reliability is low. For example, inEcuador, 77% of farmers denied stripping the coffeeberries from the trees. The extensionists said in factstripping coffee was much more common, and thestudy of post-harvest machinery (Ecuador Case Study)reconfirmed the extensionists’ notion.

Short questionnaire plus sampling. We have beenworking on a hybrid research method combining aone-page questionnaire with direct observations. InMexico, researchers asked farmers if CBB were dis-tributed uniformly or not. Most farmers said the CBBlived in manchones (large spots). Researchers askedwhat caused the large spots of CBB, and visited thespots with the farmers. The researchers confirmed thatthe spots were indeed infested with CBB, and tookdata on shade, proximity to roads and other data, toverify local knowledge of why the CBB are more com-mon in some parts of the grove. (See Section 3 of theMexico Case Study).

PRA. The Participatory Rural Appraisal (originallycalled “Rapid Rural Appraisal”) has been used exten-sively to assess the demands of rural people for de-velopment projects. It was developed in the late 1970sin India and Nepal, and was championed by RobertChambers. There are already several good manualson how to do a PRA, including one in English byMcCracken and colleagues (1988) and one in Span-ish by Katrin Linzer (1995). There are many shorterarticles on PRA, especially in the journal devoted toit (PLA Notes).

One of the strong points about PRAs is that research-ers go to a village and stay there, for four days andnights, or longer, giving them contact with rural peoplethat may otherwise not be part of their experience.The PRA stresses listening to villagers, rather thanlecturing them. Another valuable lesson from the PRAis the reliance on a set of tools (interviews, transects,agricultural calendars, local oral history and others).A religion didn’t quite spring up around PRA, but itwas a refreshing change from the questionnaire, andfor a few years doing a PRA was a required start forany donor-funded project. Since 1995, Stephen Biggs

(1995, Biggs & Smith 1997), Paul Richards (1995),Robert Rhoades (1998) and others have severelycriticised the PRA: arguing that it is simply a neworthodoxy, that it can be manipulated to back up theagenda of the facilitators, that it is paternalistic andthat it treats rural people like schoolchildren. Villageleaders can manipulate PRAs so that ethnic minori-ties, the poor and other groups are excluded from dis-cussions.

PRAs take up a lot of rural people’s precious time.Another problem with the PRA is its emphasis ondrawing pictures and charts. Rural people are expertspeakers, not expert artists, and their drawings canlook naïve, which may, at a subliminal level, rein-force some researchers’ stereotypes of campesinos assimple and unsophisticated. PRA facilitators also tendto leave all the drawings in the community, and todocument little of the experience later in writing. Onthe other hand, Nazarea-Sandoval (1995) skilfullyanalysed farmers’ drawings to learn about their atti-tudes about IPM and farming in the Philippines.

PRAs are now being rapidly dropped from the agendaof formal development, and have not been replacedby any other social science research method. The lackof yet another new orthodoxy is a positive step. But italso means that development professionals, many ofwhom have no social science background, are nowleft without a model of how to interact with commu-nities. While the PRA was due for some well-deservedcriticism, it is disconcerting that the development com-munity is throwing the method out like last Sunday’snewspaper, without incorporating its better ideas intoan improved method.

Three legs: local extensionists can outline a lot of in-

formation for you in a hour or two

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The PRA was valuable because it induced many se-nior researchers to talk to farmers. It was relaxed(Chambers 1992). Researchers actually slept in a vil-lage for three or four nights, while now we seem tobe returning to drive-by visits. PRA’s toolbox of vari-ous methods was flexible enough that social scien-tists were just starting to use it for empirical studiesreported in academic journals (e.g. a study of vil-lages in Eritrea: Tesfai & de Graaf 2000).

Sondeo. The sondeo is a sensible, practical method,developed in Guatemala (Hildebrand 1981). It waseclipsed by the PRA, but it is worth considering again.An ideal sondeo is carried out by 3 social scientistsand 3 agricultural scientists. Finding enough socialscientists was often a limitation, but the idea was thatevery day one social scientist would team up with anagricultural scientist to walk around in the country-side and chat with farmers.

The team would sleep in a provincial town and visita different village every day. The sondeo involvessome nice touches, like buying a watermelon in alocal market, slicing it up under a shade tree and in-viting passing farmers to sit and eat some and chatabout their work for a few minutes (Peter Hildebrand,personal communication). The sondeo starts on Mon-day, with a final write-up by Saturday. It is a quick,interdisciplinary way to get a description of aprovince’s agriculture.

Three legs . During a previous CABI project withcoffee in Colombia in 1996, Jeff Bentley and JohnStonehouse began experimenting with short PRA-type workshops with extensionists, who enjoyeddrawing maps and charts about the adoption of IPMtechnologies.

The extensionists were pleased to have someone asktheir opinion about farming systems in their area.Along with other colleagues we later found thatextensionists or other grassroots technical peoplecould provide a quick overview of an area. Talkingwith extensionists is no substitute for interviewingfarmers, but a two to four hour session can be a pro-ductive start to formal social research. Theextensionist’s perspective allows triangulation (hencethe three legs) between the scientists’ and farmers’

ideas. See Bentley et al. (in press) for a more com-plete description and a case study of a survey of farmerknowledge in Peru.

Semi-structured interview. The interviewer hassome topics in mind, but is open to other ideas aswell. The semi-structured interview is one of the mostversatile methods, and can be adapted to almost anytopic. It also forms the basis of the sondeo, partici-pant observation and many other methods. Speakinghas a “natural” feel to it, because language is innatelyhuman. Farmers have large vocabularies, highly ab-stract grammar and can develop as complex a conver-sation as anyone. Asking farmers to draw somethingduring a PRA does not always elicit the kinds of wise,perceptive statements that are common in theirspeech. See some of the farmer quotes in the Colom-bia Case Study for examples. The hardest part of aninterview is not asking the questions, but listening andwriting up the answers. See also the tips for inter-viewing farmers in Section 4.3.

Participant observation. This is the most powerful,versatile and objective way of getting a qualitativeview of another people. It involves living in a com-munity for a year or two, going with people as theygo about their business and then describing it. Par-ticipant observation is an old method.

The classic account based on participant observationis the description of inter-island ritual trading inMelanesia by the British-trained, Polish anthropolo-gist Bronislaw Malinowski (1922), whose fieldworkwas conducted during the First World War. Twentyyears earlier, the American anthropologist FrankCushing wrote of his 7 years among the Zuni of NewMexico, from pottery (Cushing 1886) to creationmyths (Cushing 1926)10 . Participant observation iswell suited to studying smallholder agriculture, be-cause the researcher can work alongside the farmersand see what they actually do, and it continues to bethe preferred research tool of anthropologists. PaulSillitoe’s (1996) beautiful account of local knowledgeof agriculture (including pests) among the Wola ofNew Guinea is based on many years of participantobservation. Yunita Winarto’s description of a farmerfield school in Java is the most meaningful accountavailable of the impact of an IPM program, because

10 Nothing is sacred. See Hughte (1995) for a cartoon parody by a Zuni artist (published in American Anthropologist).

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she lived in the village long enough to “get” the farm-ers’ perspective (Winarto 1996).

Few senior agricultural researchers can spend a yearor two in a village, but most of them can sponsor stu-dents to do so. Students have the time, and their sti-pends are well within the budgets of most projects.The senior researcher must visit the student occasion-ally, read her thesis and otherwise provide leadership,but participant observation can be an effective wayfor an agronomy student to learn social science skills,or for an anthropology student to learn about agricul-ture. This cross-disciplinary experience will pay divi-dends to agricultural development for the rest of thestudent’s later career. Participant observation as stu-dent projects are of uneven quality. Some people aremore insightful observers than others, and some stu-dents find it difficult to express what they havelearned. They are affordable, so sponsor two or threestudents to do participant observation, and at least oneshould return good results, especially if you:

� Give them clear objectives.� Demand occasional reports or ask to see their

field notes, to make sure they are on the righttrack.

� Visit them in the field once in a while.

Avoid getting a naïve collection of obvious prob-

lems: be aware that all people in the community maynot have the same needs. Wealthier people, men andmembers of the dominant ethnic group may take thefloor to exclude or manipulate others. Even assumingthat the researchers have talked to people represent-ing the various groups of the farming community, aswe see in the following section, people may not beable to articulate all their research demands.

Explicit and implicit demands . Explicit demands,the things people tell researchers they need, are notalways very useful. A small town mayor in Boliviaonce told Bentley that their greatest need was to learnto use highly toxic chemicals. Many rural people arehighly in favour of insecticides, or may want to killbeneficial insects. A common demand is for price sup-ports for agricultural products or subsidies for seedsand fertiliser. Researchers still have to learn farmers’explicit demands, but must also dig deeper. For ex-

ample, coffee growers have explicitly demanded con-trol of the CBB. But few if any smallholders in LatinAmerica demanded that entomologists bring parasitichymenoptera from Africa, because farmers did notknow that the wasps existed. Still, entomologists cor-rectly perceived that if the releases were successful,they would satisfy the farmers’ demands for pest con-trol. Likewise, people cannot demand nematode con-trol if they do not know the worms exist. Similarlythey cannot ask for help setting up inspections forbird-friendly coffee if they do not know about suchprogrammes.

Of course, there’s a fine line between intuiting people’simplicit demands and paternalistically imposing yourown agenda. At conferences one may run into “par-ticipatory extremists” who think that a project shouldonly do what farmers specifically mention. But fewof these people are running projects. One of the mostserious efforts to incorporate farmer demand has beenthe Swiss-funded ATICA project in Cochabamba andChuquisaca, Bolivia. Beginning in 1999, they gath-ered community demands in meetings in about 100villages in six municipalities. Even so, project lead-ers realise that these demands (mostly for pest con-trol and soil-&-water conservation, it turns out) mustbe refined with technical help to ensure that the re-sulting projects are sensitive to social, technical, fi-nancial, natural resources and gender issues (ATICA2001). See the Ecuador Case Study for an example ofhow researchers responded to an implicit demand fora study of the relationship between coffee varietiesand CBB incidence.

Problem vs. demand11 . Farmers’ problems usuallyboil down to a limitation to profitable farming, e.g. apest or marketing problem. A demand is a functionalsolution to that problem. For example, the CBB is aproblem. But so is the high cost of labour.

The demand is for an insect control that either saveslabour or costs little money. That is one reason farm-ers like insecticides; they are affordable, time-savingand they kill insects, at least in the short-term. Insec-ticides may not be a lasting response to the demand,because they often cause resistance in pest popula-tions and kill beneficial insects, although farmers don’tknow that when they start using them.

11 This idea was first suggested by Andre Devaux, a CIP researcher in Lima, Peru.

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In an example from India, farmers wanted control ofa lepidopteran pest (Helicoverpa sp.) of pigeon pea.A project promoted two technologies: crushed neemkernel extract and NPV virus. Both had to be pre-pared by farmers, who did not like grinding theunsavoury neem kernels on their food preparationstones; nor did they like mixing and spraying 500 deadcaterpillars to get the NPV. Farmers would use thesealternative insecticides only if NGO staff preparedthem, but rarely mixed them themselves (Tripp & Ali2001). The innovations were not spreading spontane-ously, because they were directed at a problem, butdid not satisfy the demand.

How to ask farmers about their research needs . If6 people from the city drive their car into a village

ACTIVITY 4

Rank research demands on a scale of 1 to 10.

Based on your experiences with the previous exercises, decide which are the most important researchdemands from farmers. Include explicit and implicit demands. Visit farmers and discuss the researchabletopics with them. It may be helpful to ask farmers to rank them. When ranking, the order is not so importantas which ones farmers regard as indispensable. For example, while testing new forage plants in Bolivia (onanother project), we saw that farmers accepted the ones that survived local conditions, and rejected theones that died. Asking them to rank seven or eight dead species of grass seemed silly to the farmers. A newspecies could either survive local conditions or it could not. The meaningful question was: which newplants would they sow again? Likewise with research demands, try to determine which ones are essentialand which ones are not.

Modify the demands according to farmers’ suggestions.

Let the farmer have his say

and blurt out “what are your problems?” farmers willhave high hopes that the researchers will then solveall these problems (e.g. building bridges and roads,creating and staffing schools and health care centres).Avoid raising expectations that you cannot fulfill.Even after carefully explaining that the researchersare in the community to help with agricultural re-search, villagers may have unrealistic expectations.Some rural people think that scientists already knowthe answers to all the health problems with crops andanimals, and may become disillusioned when re-searchers explain the need to do more research to learnthe answers. Farmers may exaggerate the importanceof insect pests, naming every large, herbivorous in-sect in the ecosystem, believing that the project willdonate insecticides.

Learn researchable topics. It is important to knowthe right format for asking questions (what anthro-pologists call eliciting frames). We have already dis-cussed avoiding leading questions, like “do you per-form sanitary harvests?” Or “what kind of insecticidedo you use?”.

Avoid asking “what are your problems?”. Such a ques-tion induces farmers to exaggerate their problems. Italso raises expectations. In many parts of CentralAmerica, the lack of enough clean water at harvesttime is a real problem that keeps farmers from wash-ing their coffee. Unless the team includes hydrolo-gists, and is prepared to work on water supplies, itmay be best not to raise local people’s expectationsthat the project will work on water.

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Example of a researchable topic. Sampling is keyto Integrated Pest Management, yet in most projects,farmers are reluctant to sample. Initial social scienceresearch on our CFC CBB project suggests that farm-ers need sampling techniques that are less mathemati-cal and use less labour. This is where things get tricky:farmers are not going to just come out and say “weneed a new sampling method.” You have to figure itout, based on what they say and do.

“What this village needs is more mango variet-

ies”. When gauging implicit farmer demand be care-ful not just to impose your own biases. For example,there was a mango breeder who met with farmers invarious communities of a certain South Asian coun-try, and after each meeting concluded that farmers’main research demand was for more improved mangovarieties. Be more open to new ideas.

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“We trained hard, but it seemed that whenever wewere beginning to form up into teams we would be

re-organised. I was to learn later in life that we tendto meet any new situation by re-organising, and a

wonderful method it can be for creating the illusionof progress while producing confusion, inefficiency

and demoralisation.”

Author unknown, commonly but wrongly attributed to

Gaius Petronius

“Three key decisions for a scientist using a partici-patory approach are deciding where to work (in

other words, selecting a site), who to work with (whoparticipates?), and how to work with them.”

[Mauricio Bellon 2001 Participatory Research Methods

for Technology Evaluation]

5.1 DECIDING THE APPROPRIATE LEVEL OF FARMER-SCIENTIST

COLLABORATION

Farmers and scientists know different things. Depend-ing on the research topic each will have a greater orlesser contribution to make. Researchers may have tochose early in the study whether to delegate more ofthe research to farmers, or to conduct most of a giventrial themselves (for example, see the experiment withtraps, Ecuador Case Study). The decision depends onwhether scientists or farmers have the greatest com-parative advantage for that topic.

Farmers’ comparative advantage. They know theirown labour and capital constraints. This is especiallyimportant for research on cultural controls. For ex-ample, the farmers know when they have time to per-form the cleansing harvests and gleanings that helplower CBB populations. Farmers have the ability toextrapolate qualitatively. Farmers also know the de-tails of their own environment (things like, “this isthe shadiest part of the grove; this is the part that yieldsthe most; these are the CBB hot-spots”).

Scientists’ comparative advantage . Scientists under-stand numbers, not just high-powered statistics, butalso more prosaic concepts like percentages and prob-ability.

Scientific concepts—like genetics, organic evolution,insect ecology, sexual reproduction, geological time,

price-setting through supply and demand—may seemobvious to many researchers, but can be revolution-ary topics to farmers.

The different levels of farmer involvement.

In 1989, Stephen Biggs proposed the following fourlevels of farmer participation in research.

1. Contractual (farmers participate the least)2. Consultative3. Collaborative4. Collegiate (farmers participate the most)

� Level 1, “contractual”,- the least participatory.For a while, agricultural development experts almostlost sight of the fact that on-station research is stillimportant. The Colombian beneficio ecológico(“Becolsub” ecological coffee processor) is one ex-ample of a successful technology recently developedon-station, with little input from farmers. In anothercase, British scientists in Bolivia recently broughtabout 20 legume crops to the country for local test-ing. They needed a quick, quantitative evaluation ofeach species’ response to local conditions, and de-cided to do the first round on-station, which minimisedtravel time, costs and allowed easier control over thecrop. Later trials of the more promising legumes willlater be conducted with farmers (Sims & Bentley, inpress).

In Ecuador, researchers on this project tested CBBtraps, and worked with different designs and baits.They needed some simple, numerical data (e.g. howmany CBB fell into which kind of alcohol). Rather

Farmers can help with experiments

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Box 4 Consultative research (scientist discussesresearch with farmers).

Example: Inventing picking mats with farmers inIndia

In 1990, the CBB came to Kerala. Coffee Board en-tomologist C. B. Prakasan is from Kerala, but wasworking in Coorg, Karnataka from 1992 to 1996.In Kerala he had seen people tying a mat or tarponto the tree at harvest, which is a traditional prac-tice, to keep the berries from rolling down steepslopes. Prakasan thought that the same idea couldbe used for CBB control. Prakasan askedThammaiah, an extension inspector, to make somebags. Thammaiah told some labourers to cut opensome gunny bags and stitch them together. With theactive involvement of Mr. H. K. Dhruvkumar, thethen Junior Liaison Officer of Siddapur, Coorg,Karnataka, they demonstrated the picking mats in avideo film on CBB in 1994. Then without any trials,but as a hypothesis, the researchers took the mats tothe field. The extension service started teaching themats to growers in the village of Ammathi, Kodagu,and the mats were adopted by the Coffee Board forCBB management.

Box 5 Collaborative research (scientist and farmerwork together)

Example: participatory research with plantingstyles in Ecuador

Researchers and farmers evaluated two types ofseedbed and two types of transplant, for a total offour treatments. The experiment was conducted onfive farms, each of which was a replicate. The seed-bed treatments were 1) the seedbed and 2) directplanting.

From the seedbed, the coffee was transplanted toeither standard, black-plastic bags, or to a raisedplatform that is 30 cm tall and composed of threeparts black earth, two parts decomposed livestockmanure and one part sand. Coffee was planted 15cm apart.

Afterwards, the agronomists weighed some of thecoffee plants in the laboratory. They also evalu-ated the treatments with the farmers. Now they arestudying the adaptation of the seedlings to thecoffee grove.

The scientific recommendation had been to useplastic bags. But the best results were obtainedwith coffee that was not germinated in a seedbed,but planted directly into a raised platform, andnot into a black-plastic bag. The extensionist/re-searcher (Evaristo Calle) concluded, “we learnedthat the farmers’ practice might be best”.

than trying to involve farmers very much with thisparticular experiment, the researchers decided to carryit out themselves, on-farm, but with most of the deci-sions taken by researchers (see Ecuador case study).

� Levels 2-3, “consultative & collaborative”, -moreparticipatory. This is the kind of research most oftenthought of as participatory. It involves more or lessequal collaboration between scientists and farmers. Ittakes place on-farm. Farmers not only provide landand labour, but make an intellectual contribution tothe research. The trials have some of the format ofon-station research. The example in Box 4 shows thatresearchers in India invented a new harvest technol-ogy based on traditional farmer picking mats. In Box5, some of the treatments for an experiment in Ecua-dor were farmers’ existing practices. In both casesfarmers contributed intellectually to the research.

� Level 4, collegiate: “the most participatory”. -This is potentially the most important and rewardinglevel, where farmers conduct their own research, andresearchers support them as colleagues. Because thefarmer leads the research, the method is more open-

Box 6 Farmer invention stimulated by learningabout a technology

Staff of the CFC CBB project taught Colombianfarmers to use boxes (tolvas) with greased plasticcovers for storing freshly harvested coffee berries.One of the farmers (Wálker Cano) made a radicalmodification of the technology. He invented agreased plastic drum with backpack straps, forholding and hauling coffee berries in the groveduring harvest. Colombian researchers then helpedMr Cano and other community members to vali-date the invention, and invited them to a farmer-experimenter workshop where other farmers couldlearn about it (see Colombia Case Study).

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ended. Perhaps for this reason researchers are gener-ally slow to recognise opportunities to work this way.The scientist has four main contributions to make tofarmer-experimenters.

� Share scientific concepts with themthat may inspire them to see the world in adifferent way.� Show them new techniques, which thefarmers may later modify.� Validate. Reconfirm the functionalityof the farmers’ invention.� Moral support. Recognise their efforts,and help other farmers to learn about theirinventions.

One example is from Zamorano, where agronomiststaught Honduran farmers that wasps and ants werenatural enemies of insect pests. Several farmers thenbegan spraying sugar water and fruit extracts on maizeto attract predatory Hymenoptera to attack fall army-worm. Luis Cañas later wrote a Ph.D. thesis in ento-mology at Purdue University, validating the innova-tion (Cañas & O’Neil1998). See also the HonduranCase Study for an example of a large, commercialfarmer who invented a novel method of strip applica-tions of insecticide, based on new information helearned from the Project.

Conclusion: deciding on the level of farmer in-

volvement. For a project trying to achieve an impactat community-level, level 2-3 (see above) is probablythe most appropriate. They are methods for workingwith groups of people, adapting not-very-novel newtechnologies for local conditions. If you need a rapid,quantified response to research questions (e.g. re-sponse to fertiliser), level 1 (the least participatory)is best. Level 4 (farmer’s own research, supported byresearchers) is best done with individual farmers. Itis well suited to developing (some kinds) of technol-ogy, but not for spreading it to other farmers.

5.2 CONTACTING COMMUNITIES

Picking communities. Communities can be chosenat random, purposefully, or self-interestedly. Samplesmay be ad hoc or stratified. However, “in many casesthis decision (of where to work) is pre-ordained for

administrative, political or logistical reasons” (Bellon2001:16).

� Random selection. In theory this should be simple.Take a map of the area, or a basic geography. Writethe community names on slips of paper and pull someout of a hat. Few projects start this way. Researchersalmost always have some characteristics in mind andare not particularly interested in working in randomvillages.

� Purposeful selection. One strategy is to choosethe communities that suffer in the most extreme wayfrom a given problem. This ensures that the problemis of interest to the community. One of the best ex-amples of this was the case of the Mexican project(see Mexico Case Study), where researchers carefullyselected the communities that had the most concernsabout CBB, in order to ensure local interest in theparticipatory research. Other forms of purposeful sam-pling might include electing the communities:

� closest to a national park, with coffee grownunder natural forest trees, in order to work withshade management and biological conserva-tion.

� that produce the highest quality of coffee,to make sure that the project result is sociallyand environmentally sound coffee, that canalso be sold on a premium market.

� Selection through self-interest. No one will admitto having chosen their project sites this way, but de-velopment projects are occasionally chosen with thecomfort of project staff in mind. Latin Americansmallholders live in some remote areas, and projectstend to avoid the most distant ones, working with vil-lages near the main highways, around the nicer cities,in the least violent countries. In part this is becauseproject leaders want to live in cities where there areschool and job opportunities for their own families,and field sites are chosen near those cities. Coffeeprograms have not always had this luxury, because ofthe importance of coffee in the nations’ macro-economy. Coffee programs have made more of an ef-fort to reach a broad range of coffee growers.

� Ad hoc selection. The course of least resistance isto simply keep working in the community where one

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Coffee Coffee

monocrop and other crops

High altitude

Low altitude

Table 4 Example of matrix for selecting four types ofcommunities, with two variables

has always worked, or where ones friends haveworked. This is not quite as cynical as it seems. If theresearchers already have rapport with a community,it may be easier for them to work there than if theyhave to start all over again, getting to know a differ-ent group of farmers, all of which takes time. Theproblem may be that such communities are not nec-essarily representative (usually being on the highway,near the research centre and have already been vis-ited by many extension agents and researchers). It isusually a good idea to avoid the most difficult or dis-tant localities, at least to start with, until you can fullyappreciate the problems of your chosen topic. Youhave to get a result to your project in a finite time andyou should allow for that which you cannot foresee.

� Stratified selection. Researchers may chose sitesbased on two, or at most three contrasting variables.For example, communities in an area could be classi-fied into four groups, using a simple matrix, accord-ing to two variables, altitude and degree of crop di-versity (Table 4).

Whichever method the project uses to choose com-munities, also bear in mind that most areas have agro-ecozones, with different pest problems, and differentcoffee qualities in each one. An area typically has 1)a high zone of high quality and low pest problems, 2)a medium zone of acceptable coffee quality and morepest problems, and 3) a low or marginal zone of poorcoffee and lots of pests. Choosing communities withthese zones in mind does not mean choosing villagesin each one. E.g., a project interested in gourmet cof-fee and cloud forests would only work in the highestzone. In the year 2010 if a major increase in worldcoffee drinking has boosted prices of even mediocregrades, a project with a pest bias would choose towork in zone 3. A project with a social mandate mightchoose to work in zone 2 if the area was home to alarge constituency of coffee-growing smallholders,

with an agronomic problem that could be solved byresearch, thus increasing coffee quality.

� Post-FFS FPR. Another option is to conduct oneor more FFSs, and build on them for FPR in later years.The experience reported in Kimani et al. (2000) isone example. If you decide to do this before estab-lishing the field schools, you will still need to takeinto account all of the information in this section onchoosing communities. Setting up FPR with existingor earlier field schools is possible, and is a kind of adhoc selection.

� How many communities? The number of commu-nities to work with depends partly on the project’shuman and financial resources. Our CFC CBB projectin Colombia worked with nine communities, becauseeach of the three researchers could cover three (eachresearcher also had two assistants). Three or four com-munities per researcher is about a maximum load, al-lowing a visit per week to each, and time for prepara-tion, writing and administration. This could bedoubled, by going once every two weeks to each site.

Another consideration: how much of a direct impactdoes the project intend to have? If the project is de-signed to invent a better beetle trap, and then dissemi-nate it by mass media and conventional extension toa large area, then one or two communities in eachmajor agro-ecozone is probably enough. If a projectwants to have an immediate impact in a certain area(e.g. if environmental activists want to stem illegalclearing of forests in a national park), then research-ers may want to work directly with all or most of therelevant communities.

Social structure. Local leaders . Some rural villagesare highly organised and others have a structure asloose as a bag of marbles. In some countries, likeBolivia or Mexico there is a formal, political struc-ture at the village level, with local leaders who canhelp call community meetings. In some countries, e.g.Honduras, each household must be individually in-vited to meetings. Each country is different, and localextension agents can explain ways of approaching acommunity to start a research project with them.

In our CFC CBB project, we used a wide range ofways to contact local leaders. In Mexico, project staffcontacted leaders of the ejido (land reform commu-

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nity) organisation, who helped get in touch with localleaders. Likewise, in Colombia, researchers contactedextensionists from the Coffee Growers’ Federation,who introduced them to local leaders. In that case,the biggest problem was “turf,” the extensionists hadto be constantly reassured that the researchers werenot “doing extension.” In Ecuador when our projectstarted, the village level organisations were weak. Oldself-help groups had been established, but were inac-tive. Still, project extension agents went to villages,asked who were the former leaders of the self-helpgroups, and simply introduced themselves and askedthe former leaders if they would help the extensionistsinvite their neighbours to a community meeting. InHonduras and Guatemala, the project simply contin-ued working with communities where researchers hadlong-standing relationships.

� Farmer committees. Local research committeesare useful. When working on level 2-3 research, withseveral replicates of the treatments, in several farms,the best way to work with the farmers is in smallgroups, or committees. Take care to choose the com-mittee with the community. If an extension agent picksthe committee, he will probably choose “progressive”farmers, men that he gets along with, but not neces-sarily people that the community would choose. Re-searchers should meet on a regular basis with the com-mittee, taking data and discussing the trial’s progresswith the farmers. The whole community need not nec-essarily meet again until near the end of the season,when the committee can explain the results to theirneighbours.

5.3 AROUSING COMMUNITY INTEREST

It takes time to develop these skills – we all makemistakes - don’t get discouraged, keep trying, try arange of things. Local people do not expect the projectstaff to be perfect. As long as researchers and exten-sion agents keep their appointments with the commu-nity, and observe the following protocols, odds aregood that the people will collaborate with the projectuntil the end.

Identifying the problem you are going to work on.

Chapter 4 discussed how to identify researchable prob-lems with farmers. These still need to be formallypresented to the communities, for their approval. It is

important that the whole community gives an opin-ion of the research agenda. Go to the community witha research agenda (based on interviews, sondeos etc.with farmers in the area) and present it to them toratify, modify and reject, item by item. Take a team offour or five facilitators. After an initial meeting, di-vide the community into interest groups (e.g. men,women, farmers, other occupation groups, elders,youth). Many rural communities have ethnic minori-ties who should be consulted. It is common for com-munities to have ethnic, religious or political factions.Indians (native Americans) are disenfranchised inmuch of Latin America, as are “tribal” peoples in In-dia. After the civil wars in Central America there wasbad feeling between people who had fought on oppo-site sides. If local social relations are strained it willtake skill and local understanding to create a spacewhere all the groups can be consulted. For example,researchers may want to contact influential membersof the minority community, and hold a smaller meet-ing in a private home, to ensure that their concernsare met.

At the first meeting it is important to go beyond justpresenting farmers’ problems back to them. They maybecome bored and frustrated. Also, present an outlineresearch agenda, to show community members thatthe project team has started to think of possible solu-tions. By dividing community members into four orfive groups, even if the groups are random or chosenad hoc by the people themselves, it will give a chancefor more people to talk. The facilitators can help themwrite their concerns on paper, and express them in aclosing session with the whole community. If you re-ally did learn the demands for research in the firstphase of the project, at the close of the first meetingwith the community, you will be able to say some-thing like, “We learned by talking to you earlier thatyour problems are X, Y and Z. This afternoon weproposed A, B, C and D. Your comments in the workgroups have helped us to see that we need to take thefollowing into account…”

Agreeing on priorities. In theory, the researcherschoose the research agenda with the community. Inactual practice, even the projects with the most po-litically correct rhetoric start with an agenda and lookfor communities that will accept it. The reason issimple. Any community can have a complex agenda,much of it involving large capital expenses. Virtually

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all rural communities want an access road, electric-ity, drinking water, school, health care etc. Some com-munities in special circumstances demand irrigation,more land, secure land title, paid jobs, protection fromother settlers, etc.

Agricultural research is rarely as important to a com-munity as any of the above, although the current prob-lem with low coffee prices has now become a majorproblem in communities that specialize in coffee. Thisis not to say that agricultural research and training isunimportant to communities, because it is important.Even so, farmers may be concerned about several top-ics, e.g. soil conservation, soil fertility management,water management, livestock health, crop manage-ment (usually for one to four commercial crops and20 to 30 subsistence ones), seeds, pests (arthropods,weeds and diseases), for several crops.

Few institutions can keep up with farmers’ potentialdemand for research, let alone with a ruralcommunity’s demands for roads, schools and othercapital-intensive development. Institutions have asmaller agenda, determined by their interests and theircompetence. Thus an institution and the communitiesmust negotiate their joint agenda in good faith, whatis called concertación in Spanish. They must do a kindof categorisation:

a. An important part of the community’sagenda, but not of interest to the institution.(“We don’t build roads.”).

b. Part of the institution’s competence, butof little use to the community. (E.g.: research-ers may know a lot about CBB, but is not apest in some communities):

c. Of interest to both. (E.g. a technology tolower coffee production costs and increasequality).

The community and the project team agree on topicsof the last category. Try to understand the communi-ties’ explicit demands and design a research agendathat they will buy into. Avoid “snowing” the commu-nity by forcing them to accept the project’s agenda.On other projects, we have heard farmers mouthingback the extensionist’s environmental rhetoric (“Wenever use chemicals; that would damage the environ-

ment”) but later discussing the use of insecticides inthe extension agent’s absence.

Maize scientists in Oaxaca, Mexico, asked a group offarmers to prioritize their problems. Of eight majorproblems, the top three were all with coffee (lowprices, shortage of labour, lack of washing and dry-ing facilities). The maize researchers opted to workwith problem #5—small maize harvest (Bellon 2001).This example shows two things: 1) None of the de-mands were for pest research. This is often the casewith coffee, and researchers who have been trainedas entomologists or agronomists are currently obligedto deal with marketing and processing problems, 2)Farmers are generalists, growing maize, coffee, pep-per, bananas and 20 other crops, and livestock as well.Scientists are specialists of one crop, or one aspect ofa crop.

Setting an agenda. During one of the first commu-nity meetings, agree with local people on the topic(s)for participatory research (see Section 6.1). We sug-gest:

� Setting regular dates for return visits, for ex-ample, every two or four weeks, on the same dayof the week and the same time of day.

� Starting preparing for the research after cof-fee harvest, before they have started their tasksfor the following year (e.g. pruning, weeding,fertilisation).

� Working out an agenda with the communitybased on their interests (e.g. pest and diseasecontrol, improving quality), adding other topicsthat they may not realise are also important.

The greatest limitation on the agenda is scientists’ cre-ativity. Farmers will test nearly all of the ideas thatare presented to them. Present new ideas (diagnosis,bioecology and control) just before the time of yearwhen they must be implemented. For example, dis-cuss the importance of a first fruits harvest a week ortwo before the first berries are ripe, to give farmerstime to decide to try the technique, but not time toforget about it.

� Set a large agenda and allow farmers to choosefrom it. A consistent problem in participatory research

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is scientists who set a small agenda of pet ideas, andwho refuse to accept the fact that the farmers consis-tently reject these ideas, and for good reason.

For example, before the CFC CBB project started,researchers in Colombia insisted that extensioniststeach farmers to culture an entomopathogenic fungus(Beauveria bassiana, Bb) at home. In theory it was anice idea: farmers would boil rice, put it in old rumbottles and grow fungus on the rice, later to spray onthe coffee groves, controlling CBB with non-toxic fun-gus. In practice, it was complicated, farmers did nothave enough room at home to cook and store the fun-gus, contamination of the fungus-on-rice culture wascommon and it was not always easy to come up withenough empty rum bottles. In the end, thousands offarmers adopted, then abandoned, Bb culture. Theextensionists were upset at having lost credibilityamong farmers, and the researchers were also embar-rassed. The whole sad event could have been avoidedby discussing and fine-tuning the research agenda withfarmer colleagues, by setting up some farmer groupsto try the technology on a pilot scale before launch-ing a regional effort.

� Only promise what you will fulfil. Communitymembers do not expect project staff to know every-thing or to solve all their problems. They just expectpeople who are honest and follow through. Somepeople think they need to promise a lot of things toensure community participation. This is not true andin the long run is counter-productive. If local peopleask for something you know you cannot fulfill, donot tell them that you will look into it. Just tell thatthat you cannot do it.

Getting and keeping extensionist collaboration.Some projects use extensionists as the foot soldiersof participatory research, - conducting communitymeetings. The results are not always very rewarding.Extensionists think like extensionists, not like re-searchers: extensionists like to show farmers newthings to try. Extensionists tend to be poor at docu-menting their work. They also tend to give little im-portance to farmer inventions. For example, in Indiaa farmer unrolled two large picking mats, and showedus how he had modified them, by slitting them to themiddle on one side. This allowed pickers to pull themat right around the tree. The farmer also said he wasthinking of experimenting with a rope and a set of

holes, “like a shoelace” that would allow labourers totie the slit shut. The shoelace would take more time,but would keep more coffee off the ground. The farmersuggested that the mats should come already cut witha slit. The extensionist could have reacted by saying:

a) “What a great idea, I’ll tell other farmersabout it.” Or -

b) “That’s interesting. Let’s try to validate itand see how much time it takes and how muchcoffee it saves.” Or even -

c) “Yes, I’ve seen other farmers do similarthings.” But no, he said -

d) “We have enough trouble as it is gettingour manufacturer to make the mats. We can’tget them to add another specification.”

In spite of such wasted opportunities to support farmerresearch, extensionists are often skilled at dealing withcommunities, and are more willing to go to a commu-nity every week than most researchers are (the aver-age scientist has classes to teach, a department to run,committees to sit on….). The best solution is for am-bitious young researchers to accept the challenge ofcollaborating with communities (as was the case withour Mexico and Colombia projects). Another solu-tion is for researchers to work closely withextensionists, going with them to the field on some ofthe visits (as in our Ecuador project).

If the project hires and supervises extensionists di-rectly, the secret to keeping them is paying a premiumsalary and attending to basic good management. Ourexperience in Latin America has been thatextensionists quit low-paying programs and gravitatetowards higher-paying ones; some have even emi-grated. If extensionists are paid a decent wage andgiven adequate moral and logistical support, they willprobably stay. If they feel that their boss won’t listento them, that they cannot get access to a car or a mo-torbike when they need to go to communities, or ifthey cannot get advances for subsistence expenses,then they will look for work elsewhere.

Working with extensionists on someone else’s

project is not as easy. A research program frequentlysigns an agreement with another institution to carry

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its ideas to farmers. It can work well, but the grassrootspersonnel are sometimes caught in the bind of beingasked to do additional work with no additional re-ward. On our Ecuador project, researchers offered theextensionists in another institution a modest, US $20bonus per month to collaborate with us. More thanthe money, the extensionists appreciated the gestureof good will, and many of them actively supportedthe Project until it was completed.

Most agreements for extension services involve pay-ing for them. Success depends in part on the attitudeof the extensionists’ supervisor. If he or she feels thatthe services are reasonable, and communicates this

idea to the extensionists, they will be likely to carryout the tasks responsibly. It is useful for the institu-tion that contracts the services to host a training eventfor the extensionists. Good training will impress theextensionists with the intellectual authority of the con-tracting institution, and create loyalty, while bad train-ing will create cynicism. Continue working withextensionists and their supervisors in the field. Makepayments to the extension service based on comple-tion of certain milestones (so many agronomic trialsestablished in so many communities, data taken, re-port written etc.) rather than on a strict calendar ba-sis.

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In previous chapters we have discussed how to iden-tify researchable problems, about the need to distin-guish problem from demand, and how to select re-search sites. We have also stressed that there are dif-ferent levels of FPR (either farmers or scientists may

take the lead, or they may collaborate equally). Onceyou have defined the research demand, the level offarmer involvement depends on the type of solutionsavailable. In Figure 1 we see that there are four maintypes of solutions:

� The solution exists but needs training (Sec-tion 6.1)

� A range of options exists, but needs statisti-cal screening (Section 6.2)

Figure 1. Knowing where you are and what your are doing

When the only tool you own is a hammer, every problembegins to resemble a nail.

Abraham Maslow

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� There may be a solution, but it needs adapt-ing for local needs (Sections 6.3 to 6.6)

� The solution does not exist (at least not yet)(Chapter 7)

Each of these situations requires a different tactic.

6.1 THE SOLUTION EXISTS BUT NEEDS TRAINING

The solution may come from scientists, farmers, fromanother country, but sooner or later a technologyshould be developed that is ready to be taught to farm-ers on a mass scale (see Section 8.2). The most im-portant thing is that a technology is not ready to ex-tend simply because it works in the lab or on the sta-tion.

Paul Starkey reports that the wheeled tool carrierworked for 30 years on experimental stations in In-dia. It was like a cross between an ox-cart and a Swissarmy knife. Ploughs, harrows and other tools couldbe bolted onto the cart. But farmers would never adoptit, because it was not practical on farms. It was tooheavy, so it tended to tip over, and it was too difficultfor one person working alone to change the tools(Starkey 1988). In the history of CBB control therehave been similar experiences with Bb, sampling andother techniques that work just fine when used byagronomists, but are not practical for farmers. If youhave a half-baked idea, finish it with a group of farm-ers (Section 6.3) before taking it to mass extension.

Certain coffee varieties, the effects of shade trees (e.g.Inga spp.) and clean harvest are some of the ideas incoffee IPM that are ready to extend to farmers (atleast in some places).

6.2 A RANGE OF OPTIONS EXISTS, BUT NEEDS

STATISTICAL SCREENING

We have slightly modified Stephen Biggs’ classic ideaof four types of FPR to suggest that there are threelevels of farmer involvement in research: contrac-tual, collaborative and collegial.

Recall that contractual level 1 participation, with agreater role for the researcher, is more appropriate

for data-intensive research. Less participation fromfarmers means that the trials are more uniform, morereplicable.

In level 2/3 collaborative participation, if the farmersreally participate, they will begin changing the treat-ment design, so that each replicate begins to divergefrom the others. Soon each replicate is its own treat-ment. (This is what happened in our Honduran case).In this case, statistical and numerical analyses are dif-ficult (unless you have many replicates).

However, in many cases the researcher needs a rapid,quantitative evaluation of a spread of variables, be-fore designing the technology. For example, we mightneed to know the amount of weed suppression by 10different cover crops, or the biomass of 20 new le-gumes, or the yield range of eight new coffee variet-ies. There are many treatments, each of which mustbe standardised and replicated. The research couldbe done on-station, but doing it on farms gives you acertain reality check from the beginning. In the caseof the CBB, in earlier projects our colleagues did sev-eral experiments on-farm, with cultural control, tounderstand the arithmetic relationship between thenumber of berries left on the ground and CBB popu-lations (see Baker 1999, Chapter 6).

Such statistical research can be done as level 1, con-tractual FPR, where several farmers each agree tomanage one set of replicates. (See Section 6.5 below;it is difficult for one farmer to manage more than onereplicate). The participating farmers may be organisedinto a committee, although this is not strictly neces-sary. The main point here is that the researcher is pro-viding almost all of the intellectual contribution (thedesign of treatments), but wants to test the treatmentsunder “real” conditions.

The researcher contracts the farmer for land andlabour. Be sure that the farmer understands the im-portance of not modifying the treatments as he goesalong (see the Honduran case, where one farmerstumped half of one of the treatments). It is usuallybest for the researcher (or students, or assistants) tocollect the numerical data, not the farmer. Provide anincentive for the farmer not to harvest the crop beforeyou have collected your data (“I will pay you Xamount to leave the berries on the trees until I comeon a specified date to count the borers …”).

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12 Which takes the longest to grow? Which provides the best shade? Which requires the least labour tomanage? Which provides the most food and other products?

It is always a good idea, when designing a project, torequest some funds to pay for such contingencies ascompensation to the farmer for any losses occasionedby trials and experiments.

Once the team has screened a large number of op-tions, the best ones can be presented to farmers tovalidate under their conditions (Section 6.3). On theother hand, if you do not have a large number of op-tions to screen, but need a straightforward qualita-tive judgment of a few options, it makes more senseto skip level 1 research, and go directly to level 2/3collaborative research (Section 6.3) (e.g. see our Ec-uadorian case on coffee varieties).

6.3 ADAPTING A SOLUTION FOR LOCAL CONDITIONS:

GETTING STARTED

This is the bread and butter of FPR. It involves col-laborative (level 2/3) research with one or more com-munities to validate and adapt new ideas. Unlike con-tractual field trials (level 1), which may be done withseveral individual farmers, collaborative researchshould be done with groups, because you are look-ing to bounce the idea off the farmers. A group offarmers will be more likely than an individual to thinkof and voice changes in the idea. The technology maybe a new kind of coffee pulper, a pest sampling strat-egy, or a comparison between Inga and bananas asshade12 .

During the first meeting with the community, re-searchers and farmers should have agreed on researchdemand and possible solutions (Section 5.3). Duringa second meeting with the community, begin to es-tablish a committee of the individual farmers, whowill collaborate with the research. By this point, youshould already have your topic (at least a rough sketchof it), which will determine the times of year for theresearch (e.g. a technology for processing coffee canonly be tried at harvest time). The committee can belargely self-selected, which at least ensures havingthe more enthusiastic people to work with. Or thecommunity can nominate farmer-researchers. Themost important thing is to select the committee in a

public meeting, so that other community membersknow who is selected. It also helps the local farmer-researchers to take ownership of the trials, so that laterthey don’t say, “this is the agronomists’ experiment; Idon’t know what they’re doing here.”

Practical hints. With annual crops, several topicsmust be introduced about the same time, when thecrop is planted. One advantage of participatory re-search with coffee is that topics can be introduced ata more comfortable, less confusing, pace: e.g. at prun-ing time, at weeding, when making seedbeds, at flow-ering, when fruit is set, at harvest.

Thus, introduce each research topic with the sequence:

1) problem diagnosis2) background knowledge upgrade3) action (management, control)

� Problem diagnosis includes information onhow farmers can distinguish the problem fromother phenomena. For example, how to detectCBB, how to distinguish CBB from other smallbeetles.

� Background knowledge is the biologicaland ecological (or other real world) knowledgethat the audience needs to know in order to un-derstand what may be (for them) a counter-in-tuitive action.

� Background knowledge makes the proposedaction intuitive. For example, farmers may thinkthat insecticide is the only solution, if they be-lieve that insects have no natural enemies andthat pests never die unless poisoned. Explain-ing that the CBB is a living organism, with aspecific life cycle and that its only habitat isthe coffee berry will help farmers understandand support a cultural control method.

� Action includes new ideas about how tomanage or control a pest. Be sure to explainhow each control idea is linked to the back-ground knowledge (why the action works).

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TYPE OF

KNOWLEDGE

Deep

Shallow

Missing

Mistaken

EXAMPLE

How to harvest coffee

Coffee diseases

Parasitic Hymenoptera,nematodes etc.

Dumping coffee pulpinto bodies of water.

DON’T

Bore farmers out of theirminds by spending a wholeafternoon telling them thingsthey already know, e.g. thatthe ripe, red berries are theeasiest to process.

Confuse farmers by usingscientific names for diseasesthey know by other names.Give them lots of irrelevantdetail.

Make people feel like idiotsfor not knowing that thesethings exist.

Lecture community memberslike they were school chil-dren. Use lots of rhetoricfrom deep ecology.

Table 5 Do’s and don’ts for teaching ideas, by type of knowledge

DO

Ask the farmers them-selves to explain thetopic. They can often doso quickly and effec-tively. Add any clarifica-tions if they are neces-sary, and use theirremarks as a bridge intorelated topics

Use local names todiscuss the diseases.Discuss why the treesbecome diseased andshow them improvedcontrol strategies.

Use microscopes,rearing chambers andother devises to helpfarmers see thesecreatures. Explain theirecological roles.

Show the people that youunderstand why they dowhat they do. Convincethem that it is in theirown best interest to savethe pulp for fertiliser.

Filling in gaps in knowledge. We have suggestedabove that there are four kinds of knowledge (seeSection 3.1). Whether you decide there are four, three,or six kinds of knowledge is not quite as important aswhether you make a serious effort to inventory farmerknowledge during the first phase of the project, aspart of the assessment of research demand. Use thatinventory now to prepare training sessions with thecommunities. During the demand assessment phaseresearchers learned from farmers, and now they re-turn the favour, helping farmers to understand somekey scientific concepts. Each researcher has to un-derstand what farmers know, do not know, or misun-derstand, and whether the available scientific knowl-edge is relevant or whether it needs fundamental re-search. It is no longer enough to develop techniqueson-station and then blame extensionists when farm-

ers reject the ideas. You as a researcher may be in-creasingly exhorted to not only develop new knowl-edge but also promote it and ensure that it is put touse. In order to do this you have to create a frame-work of the relevant knowledge and its use and placeyourself the farmers and extensionists within thatstructure. Making a table or a diagram is probably theeasiest way to clarify what each group of stakehold-ers knows. Once you have done this, you may findyour work more satisfying and easier to defend againstcritics. We here offer you a few ideas; one is that thereare basically four types of knowledge that you aretrying to create and broker (Table 5). Another is thatit is a process that can be codified in boxes and ar-rows (Figure 2). Maybe one or both of these will helpyou. But you might want to develop your own analy-sis.

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The style of teaching must take its cue from the typeof knowledge, for example:

Keeping notes (Farmer statements as data for evalu-ating technology). Keeping a written record of whatfarmers say is important, especially their observationsabout the technologies (e.g. “How much does thismachine cost?”; “Where would we get replacementparts?”; “Who knows how to repair it?”). Unfortu-nately, most agronomists have not been trained to takethis kind of data. For example, if farmers say they are“too lazy” to use a new technique, they are sayingthat it is too labour-intensive to be attractive to them.Agronomists’ training emphasizes making a neat, geo-metrical layout of a field trial, and taking mostly quan-titative data. University agronomy training shouldinclude a course on introduction to journalism, withthe who, what, when, how, why and where of a simplenewspaper story. Fortunately, agronomists are usually

friendly and sympathetic to other people, and haveall the basic sensibilities and talent that it takes to payattention to farmers’ statements. A workshop can behelpful in teaching field agronomists to write someof this material. For example, we recently had an ex-perience in Bolivia where an anthropologist observedan extension agent teach farmers to use a microscopeat a small-town fair. The anthropologist (Bentley)wrote up a simple, seven-page narrative describingwhat the extensionist said, and the farmers’ reaction.Bentley sent the file by e-mail to extensionists. Theexample was clear enough that six of them wrote simi-lar, straightforward accounts.

6.4 ADAPTING A SOLUTION FOR LOCAL CONDITIONS (Continued): EX-

PERIMENTAL DESIGN, STATISTICS, THE SCIENCE DEBATE

Field trials versus one-off experiments . Normal, ag-ronomic research can take years: setting up the check-

Figure 2. Identifying problems and solutions, a simplified schematic of the coffee berry borer

problem and attempts to solve it

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erboard field trials with stakes and string, and takingdata on them from planting to harvest, and then re-peating it several times more to compensate for an-nual climatic variation. This style of research is usu-ally born of necessity, but bear in mind that in somecases, a one-off trial can be done instead. This is es-pecially true with tests of machinery (see Section 2.2on “Back-&-Forth”, FPR). The new water-savingpulper, mentioned above, can be tried in one sessionwith farmers. Another way to test it (after showingthe community how to use it) is to leave it with themfor a week or two and come back and discuss it withthem.

Experimental design. Researchers who have investedyears in an idea regard it as a kind of brain-child. Thescientist comes to love the idea like a child, and can-not bear to see it be criticised. “It’s not a bad technol-ogy; it’s just misunderstood.” In coffee, researcherscontinue to promote ideas like Beauveria bassianaand mass release of Cephalonomia wasps, in part be-cause researchers have invested so much in them inthe past that some scientists become unscientific andcannot accept the technical problems with these con-cepts.

Set up field trials with the idea that the treatmentsrepresent hypotheses that can be rejected, not brain-children that need to be proven to the community. Afield trial in a community is an experiment, not a dem-onstration plot.

Statistics. Numbers are like food. Don’t put more onyour plate than you can deal with. Collect basic dataon cost, plant health, harvest, etc. Enter it into an Excelspread sheet as you collect it. That way you enter thedata when it is fresh in your mind and you can clean itmore easily. If you cannot enter the data in the sameday (or at least the next day) as you collect it, youmay be collecting more data than you will be able touse anyway.

Don’t make the statistics any more complicated thanthey have to be. Simple descriptive numbers are of-ten more meaningful. (E.g. “The new technology costus $100 per hectare, but it increased the value of har-vest by $200”).

The science debate . Agricultural science and socialscience both deal with very complex realities that are

poorly modelled, with many independent variables.In that sense they have more in common than eitherhas with a hard science like physics. Even entomol-ogy is natural history, not really a hard science. Re-search with production agriculture is not science ei-ther, but engineering. We are trying to figure out howto produce more, at higher quality, to earn more whilenot increasing costs, and also not increasing risks. Thisis more complicated than just testing a hypothesis.Unlike the civil engineer, trying to figure out how todesign a specific bridge that will hold so many tonsof four-door sedans, withstanding maximum veloci-ties of wind and water, the agricultural engineer de-signs systems that must be implemented over and overagain, by thousands of people. Agricultural systemsare subject to:

� user failure “I was going to weed, but I gotsick, and my son-in-law didn’t have time to weedit for me until a month later.”

� a very large set of different natural environ-ments (based on interactions of soil, altitude, rain-fall, slope, exposure to sun, previous crop, pre-vious fertiliser and pesticide applications etc.)and huge annual variation in weather.

� large annual variation in factor and outputprices “The coffee was worth so little last year,and we had no money; we tried offering it to har-vesters on a 50:50 basis, but many of themwouldn’t even harvest it for half the crop”).

It is not so much that agriculture is unscientific perse. It is just that its outcome is determined by so manynatural and human variables that in the end, the farm-ers’ practiced, qualitative evaluation may be as im-portant as the quantitative judgement derived fromthe scientists’ incomplete set of numbers.

6.5 ADAPTING A SOLUTION FOR LOCAL CONDITIONS (Continued):

RESEARCH PROTOCOLS

Start as soon as the community selects a committeeof experimenting farmers (probably the second com-munity meeting) to discuss with farmers the nuts andbolts of the test plots, including treatments (includ-ing size and shape) plus dates and data.

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Choosing treatments. Form an idea before the com-munity meeting regarding the treatments you want totry. Start by eliciting their ideas in a brainstorm (“Whatare some things we could try to eliminate more CBBwhile processing coffee?”) Feel free to suggest someother ideas, and allow farmers to criticise them.Farmers may suggest the same things that the research-ers would have suggested (“Now that we know thatmal de hilacha is a fungus, let’s try controlling it witha fungicide, like Bordeaux mix”). Even so, the factthat farmers suggest the idea helps them to own it,more than if the researcher simply presents it to them(Sherwood 1997). Each farmer will be comfortablewith one or at most two treatments, plus a control.

Have one or two treatments per farm, with a con-

trol. This also saves the farmer labour, which helpsensure collaboration in following seasons. The par-cel is split into two or three sub-plots, with one as thecontrol and the other(s) as treatment(s). If you needto test more treatments, use more farms.

Number of replications . Three or four per commu-nity is often about as many as they and the fieldagronomist will enjoy working with. Any more thanthat and farmer-researchers and their facilitator can-not visit them all during each meeting.

Thus, each extensionist or field researcher may haveabout nine to twelve replicates in all the communi-ties. This is merely suggestive, not a hard-and-fastrule, but it does begin to suggest the high cost of par-ticipatory research. More replicates can be added ifparticipation is level 1 (less participatory—see Sec-tion 6.2): the agronomist goes to the community andinstead of facilitating a meeting goes straight to theresearch plots and takes the data, with or without thecollaborating farmer. Level 1 (contractual) FPR is atrade-off, less collaboration from community mem-bers, but more data and more replicates.

� Some advice: researchers usually make themistake of doing too many treatments and too fewreplicates. They do this because they underesti-mate the amount of variation in the measuredvariable(s). It is usually better to do, say, three orfour treatments and as many replicates as pos-sible and then analyse the results to see how clearthe results are and how well you can separate themwith parametric or non-parametric statistics.

Each farm is a replicate. Farmers typically experi-ment with new varieties of crops by planting a fewrows of the new variety. Farmers are usually enthusi-astic about testing new varieties or other techniques,if the experiment does not cause them a lot of extrawork. Having several replicates in a single plot addsto the farmer’s time and management load. Avoid ex-tra labour demands on the farmer by planting onlyone replicate per farm. This also maximises the num-ber of farmers who can participate.

Their location. There is a trade off betweenreplicability and access. Good coffee is grown in themountains, and groves can be a good hike from thefarmstead. Walking with a research committee froma typical coffee grove to three or four others can taketwo hours or longer. But if the experimental plots areplaced in areas with the easiest access, the trial mayhave serious biases (towards flat land, near the home-steads) and be unrepresentative.

Size of replicates. Allow farmers to explain whichare the easiest sizes for them to work with. Farmerstend to make sizes smaller for treatments they do notthink will “work.” Other than that, most groves arelaid out in lanes of trees, and farmers will have anidea of the minimum number of lanes per treatment.Often farmers prefer rather large treatment sizes, asmuch as a hectare sometimes. Also, if each farm is areplicate, as it should be, then each farmer may preferdifferent treatment sizes. Agronomists, on the otherhand, like to have each treatment and each replicateexactly the same size. But bear in mind that this is notnecessary. A scientific comparison is based on a re-sult per unit of input (e.g. coffee harvested per per-son/day, or per hectare). These results can be calcu-lated, as long as the edge-factor is accounted for, andthe replicates can be of different sizes.

Shape of replicates. Rectangular is usually the cho-sen shape for researchers, but irregular shapes areoften easier for farmers to work with. Do not insist onrectangular treatment plots. Small fields are rarelyrectangular, especially on mountainous, smallholdercoffee farms and insisting on rectangular treatmentplots, of a predetermined size, creates left-over cor-ners and edges that are hard for the farmer to work.Talk to farmers about a shape and size of treatmentplot that you are both happy with. Go easy on stringand stakes.

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Planting and harvest dates. This is according to nor-mal farmer practice for each area. It places a strain onthe field agronomists to meet commitments on manyfarms at about the same time of year, especially atharvest time. Farming is a no-nonsense business. Acoffee-growing family is often short of cash, and soneeds to start harvesting at a certain date, in order tomake more money to hire labour to pick the rest ofthe crop before the harvest season ends and workersmove on. Farmers may not be able to arbitrarily post-pone a harvest until researchers have taken their data.Researchers must be in close contact with the farm totake the harvest data as soon as it is appropriate. Ifthey delay even a few days, some farmers will har-vest anyway, even though the data has not been taken.Others will keep from harvesting the plot, inconve-niencing themselves and damaging rapport with theproject.

What numerical data will be taken and who will

take it. The farmers need little or no numerical data.They decide to use technology or not, based on anobjective, qualitative evaluation (“Chemical fertiliserreally helps coffee to grow and produce more, but Ijust did not have the money to buy it this year”). Asdescribed above in Section 6.4, limit the data taken tobare essentials. The more participatory the researchis, the less replicable it will be, and less data shouldbe taken. Take the data during the periodic meetingswith the local research committee. Discuss the mean-ing of it with them. Document their feedback.

Be prepared to lose some farms . In our experienceit is very common for farmers in some way to affectthe course of an experiment, so you have to be pre-pared for this eventuality. E.g. some farmers will har-vest the crop before you can measure the yield. Oth-ers may migrate, lose interest, die or for some otherreason drop out of the experiment. Have 50% or moreextra replicates than you need, to ensure completingenough of them. If it is vital that an experiment is notinterfered with, you may have to go to great lengthsto avoid this, e.g. by building up to the experimentthrough preliminary phases to make sure that thefarmer understands his role.

6.6 ADAPTING A SOLUTION FOR LOCAL

CONDITIONS (CONTINUED): COMMUNITY RELATIONS

Timing of visits. In most of the countries where ourCFC CBB project worked, researchers set a calendarfor visits with the community at one of the first meet-ings. It is important that everyone knows when you’recoming back. Remind them at the end of each meet-ing when you will return. The biggest complaint ofrural people (at least in Latin America) about agrono-mists is that they make appointments and don’t showup. Honouring your commitments for meetings helpsthe villagers build trust in you. Do not schedule moremeetings than is needed. Depending on the topic etc.,you probably need to go at least once a month.

Use participatory research to validate and reject

technology. In Colombia, researchers with this Projecttaught farmers in nine communities many techniquesfor controlling CBB. Farmers and researchers vali-dated most of the technology, especially the use ofsticky covers to trap CBB during post-harvest. Farm-ers rejected most forms of numerical sampling as be-ing too tedious and time-consuming; those research-ers who had worked in the field with farmers weresensitive enough to farm conditions to respect thefarmers’ rejection as reasonable.

Balance replicability with participation. The morefarmers contribute to the design of individual trials,the less replicable the plots become. Researchers ona (very good) DFID-sponsored project in Boliviaworked hard to be participatory. Researchers and farm-ers planted 150 test plots of perennial cropping sys-tems, including intercropping of trees with annualcrops, and legumes to regenerate degraded pastures.The farmers decided what to plant and how to man-age it. This led to two problems: first, farmers chooseto work with more profitable systems, like citrus, sofor some of the native trees there was only one repli-cate planted. Second, as each farmer changed themanagement style (over three years) to suit his or herconditions, the replicates became so different fromeach other that they essentially weren’t replicates13 .

13 For example, one treatment was forage groundnut between citrus, but the second year of those who had this treatment, some left it in, otherspulled up the groundnuts. Others tried to get rid of the groundnuts, but they were too well rooted. Thus each year the “treatments” became moreidiosyncratic.

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ACTIVITY 5

Plan an experiment with farmers.

The experiment was designed to be analysed statisti-cally, but in the end, qualitative evaluation was per-haps more important. For example, researchers learnedthat farmers preferred citrus to peach palm (Bactrisgasipaes), and that velvet bean (Mucuna pruriens)was better adapted than the forage groundnut (Ara-chis pintoi), and that over time, farmers tended to keepsome inter-cropping, but to simplify some of the com-binations (Pound et al. 1999).

Failure is part of success. A project that makes nomistakes is not doing anything interesting. Most con-ventional experiments fail. So we would expect fail-ure in participatory research.

People who don’t admit failure aren’t learning fromit, or allowing others to do so. For example, in ourEcuador Project, researchers tested alcohol-baitedtraps with farmers, to monitor CBB. During a com-munity meeting after the research had been completed,we realised that farmers had made the spectacular er-ror of assuming that a dozen small traps had some-how decimated the CBB population for the whole

community. Researchers carefully explained why thiswas impossible (see Ecuador Case Study). It was anhonest mistake, gracefully salvaged.

Keep the statistical design simple , because of theabove mentioned problems with replicability. Have afew key variables to measure and be prepared to evalu-ate the results qualitatively. If you really need somenumbers, sometimes you can get farmers orextensionists to rank the results of treatments and thenyou can work with these numbers. Another alterna-tive is to have very large sample sizes, to filter out thestatistical noise of large, individual variation in trialmanagement.

One treatment at a time . In general, treat all of theexperimental plots the same, except for the variableyou are testing. Sometimes, however a treatment maybe composed of two linked behaviours. For examplea straw mulch on a seedbed may require less water-ing than an uncovered seedbed, otherwise the seed-lings will rot.

Hold workshops with participating communities toevaluate the test plots at the end of the experiment. Itis also important to record the observations of indi-vidual farmers during the growing season and at har-vest.

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If something fails, admit it frankly and trysomething else, but above all try something.

Franklin D. Roosevelt(referring to efforts to end the Great Depression)

We now come to perhaps the most fascinating andrewarding type of FPR, when the farmers suggest so-lutions to R&D demands. One way is for scientists tolearn traditional and contemporary knowledge fromfarmers. This knowledge may be quite widespread infarm communities, but not necessarily known (or atleast not taken advantage of) by researchers. Duringthe CFC CBB project, Mexican scientists Juan Fran-cisco Barrera and Ramón Jarquín noticed that farm-ers in Chiapas found numerical sampling difficult andtedious. Barrera and Jarquín also noticed that farm-ers seemed to know the location and size of the CBBhot spots in their coffee groves. In 2001, Jarquín andcolleagues conducted research to confirm this hypoth-esis (see Mexico Case Study). Now that we realizethat farmers know where the hot spots are, research-ers in the future may be able to design lower cost con-trol strategies aimed at only infested parts of the grove.

7.1 FARMER INVENTIONS

Agricultural scientists and anthropologists have bothtended to see farmers as tradition-bound. For exampleDaryl Forde is often cited as one of the first “culturalecologists” and one of the few British anthropologiststo study North American Indians. In his book Habi-tat, Economy and Society, originally written in the1930s, and still in its fifth edition in the 1960s, Fordewrote:

“Adaptation proceeds by discoveries and inven-tions which are themselves in no sense inevi-table and which are, in any individual commu-nity, nearly all of them acquisitions or imposi-tions from without. The peoples of whole con-tinents have failed to make discoveries thatmight at first blush seem obvious.” (Forde1963:463).

But in 1972, the American anthropologist AllenJohnson wrote about inventions by smallholders in

Brazil (Johnson 1972). Few scientists were ready forthe idea, and Johnson’s paper was ignored for 15years1 4 , until noticed by Paul Richards, RobertRhoades and others who rediscovered farmer experi-ments in the 1980s. Advocates of farmer participa-tion have parroted the idea. Yet in practice, most FPRis little more than demonstrating outside ideas to farm-ers (testing bean varieties, concocting garlic and chillisprays, trying cover crops).

Farmers actually invented everything that was usedon farms until formal research started about 1840(Pretty 1991). And farmer inventions can still be asource of ideas for scientists. Many scientists find thishard to accept, but if you have reached this far in thebook, then you are probably ready to explore the idea.

Box 7 gives one example of the sort of modest farmerinvention that we commonly observe in communities.See also the “first fruits” invention in the HondurasCase Study.

One problem with farmer inventions is that the paceof change generated by them has been slow. Perhapsthis has been because we have not had a formalprogramme to find, validate and promote farmer ideas.Farmer inventions are so common that many can beelicited by a sympathetic listener in just an hour (Box8).

The idea of collecting a large number of farmer ex-periments is appealing, because it can be used to win-now a few highly productive ones from many prosaicones.

If 100 farmers invent things, at least of few of thosehave to be worth the time it would take to learn aboutthem. For example, the first experiment listed in Box

14 A notable exception was Brokensha et al. (1980).

Box 7 A farmer method for spraying hot spots

In El Tigre, Honduras, Santiago Amaya is a mediumfarmer, with eight hectares of coffee. He applies in-secticide only on CBB hot spots. Mr Amaya walksthrough his grove, with the backpack sprayer loaded.When he sees a tree with many perforated coffee ber-ries, he sprays that tree.

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In August, 2000, during a course on participatoryresearch methods, Mexican coffee scientists JuanFrancisco Barrera and Ramón Jarquín visitedHonduran farmers at El Tigre to ask about farmerexperiments. In about an hour, a group of fivefarmers revealed that they had done the followingexperiments:

1. A coffee-manioc-maize-bean intercrop, to takeadvantage of land after stumping coffee.

2. A coffee-manioc-banana intercrop for the samereason.

3. Comparison of shade of two kinds of Inga spp.

4. Trial of a new variety, IHCAFÉ-90.

5. Trial of the variety Pacamar.

6. Use of coffee pulp as fertiliser and to control thefungal disease Rosellinia sp.

7. Trial of new brand names of endosulfan.

8. Various activities to control mal de hilacha(Pellicularia koleroga), including shade manage-ment and fungicide.

9. Application of lime to control root rot.

Box 8 Eliciting examples of farmer experiments

8 could improve the profitability of stumping coffee.It would be easy to validate the practice and recom-mend it to other farmers. Even assuming that indi-vidual scientists are able to innovate faster than grow-ers, farmers have a great numerical advantage. Half amillion experimenting farmers should be able to cre-ate useful techniques, which could be adapted anddiffused.

ACTIVITY 6

Learn about farmers’ research.

Visit farmers and ask about experiments they have doneon their own. Identify a few experiments and plan someadditional research that builds on them.

7.2 NEW IDEAS ARE THE FATHERS OF INVENTION

If necessity is the mother of invention, its father is anew idea, a new piece of biological or ecological in-formation. Use the social science research methodsmentioned in Chapter 4 to study farmer knowledgeand behaviour. This will prepare us to speak to ouraudience, to know:

� what topics they are interested in?� what are the gaps in their knowledge?� what are the topics that confuse them?

Farmers invented several technologies as a result ofnew ideas they learned through the CFC project. Forexample, Honduran farmers invented strip applica-tions of insecticides near stumped groves and controlof CBB in dry berries (see Honduras Case Study) anda Colombian farmer invented a new kind of barrel forharvesting, which would capture borers emerging fromfreshly picked berries (see Box 6 and Colombia CaseStudy).

Box 9 Example of a farmer innovation, basedon new ideas about fertiliser

Hecbert Bowen has a mixed, lowland orchard ofcoffee, cacao and other species in the communityof Ayacucho, near Santa Ana de la Vuelta Larga,in Manabí, Ecuador. Mr Bowen was worried aboutsoil fertility problems, because his grove had pre-viously been planted in sugar cane, and he thoughtthe soil was largely depleted of nutrients, and thatthe structure was damaged. After learning aboutorganic fertiliser from extension agents, MrBowen experimented on his own with mixes ofcacao husks, chicken manure, cut weeds and saw-dust, applied as aprons around the coffee trees.He noticed that the soil retained more moistureunder the organic matter, which also suppressedweeds. This had the advantage that when labourersweeded his coffee, they were less likely to swingtheir machetes near the trees. This helped avoidmechanical damage, which leads to a “machetedisease” (mal de machete, probably Ceratocystisfimbriata). Mr Bowen calls this fertilisation tech-nique “la gata” (the jack), because it helps to raisecoffee trees taller and faster.

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7.3 FARMERS MODIFY TECHNOLOGY

(WHICH IS ALSO INVENTION)

When presented with new technologies, 99% of thetime or more, farmers adapt that technology, some-times in subtle ways, at other times more boldly (seeBox 10).

So studying farmers’ own innovation is initially moreof a descriptive process, though requiring good ana-lytical skills to determine what exactly they are try-ing to do and then to determine whether it is reallyhaving a desired effect. This is where you the re-searcher can make an impact, because you can takean idea and then develop it into a more formal experi-ment, either with the farmer or on a field station, whereyou can study it in detail in more controlled surround-ings. You may even be able to see something signifi-cant that the farmer does not consider important, andyou can encourage him to further develop his ideas,if you think he has the talent and inclination to do so.

Published studies of farmers’ innovations are rare, butthe ones that exist can be of considerable interest be-cause they give insight into what could be a powerfultool for people-centred R&D. We have already citedseveral (Johnson 1972, Ooi 1998, Winarto 1996,Bentley 2000b, Meir 2000, and some of the case stud-ies in this book: especially Colombia, Mexico andHonduras). Paul Van Mele (2000) has discussedfarmer inventions in Vietnam using weaver ants tocontrol pests in fruit orchards. Sherwood & Larrea(2001) observed that 59% of farmers who had con-

In one major modification in Colombia, farmersnoticed occlusion chambers for wasps, during avisit to the main Cenicafé campus. Some of thefarmer-experimenters built their own chambers,so they could put CBB-infested coffee fruit there,in 1 kg batches, allowing the parasitic wasps toescape, but not the CBB. The farmers made thechambers for a cost of about $5 each, comparedto $20 for the ones made at Cenicafé. The farm-ers substituted bamboo for much of the lumber,and bought only the cloth (muslin, available inthe nearby small towns).

Box 10 Farmers experiment with occlusionchambers

tact with the World Neighbours Güinope Project inHonduras had modified or invented technologies af-ter the project. Classic studies include Paul Richards´account of traditional experimentation in Sierra Leone(Richards 1985, 1986, 1989), and Hugh Brammer’sobservation that smallholders in Bangladesh inventedwheat transplanting systems (Brammer 1980). Rob-ert Rhoades (1987) summarized much of what wasknown about farmer experimentation through the mid1980s. Edited volumes include Brokensha, Warren &Werner 1980, Gamser, Appleton & Carter 1990,Haverkort, van der Kamp & Waters-Bayer 1991,Scoones & Thompson 1994, van Veldhuizen et al.1997. Last but not least, the journal Honey Bee, pub-lished in English and various languages of India, isdedicated to describing farmer experiments.

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It is better to teach one idea to hundreds ofpeople rather than hundreds of ideas to one

person.

Roland Bunch (Two Ears of Corn, 1982)

8.1 RESULTS OF ADAPTIVE RESEARCH

Your written results will be the only permanent recordof your work so you need to think carefully aboutthis. But unlike normal scientific work, where yourresponsibility ends after you have written up and pub-lished, you have an additional responsibility to informthe farmers with whom you have been collaborating.They need to understand what you have done together,its significance and what lies ahead and why you mayno longer be visiting them when the study is over.You need to make a graceful exit.

Data processing. As we have said above in Section6.3, don’t take more data than you can write up. Don’tlet it pile up; enter the data into the computer as yougo along (the same day, or next). There are now manyhand-held devices where you can enter data directlyto a spreadsheet and then download to a computer,and these are increasingly cheap and reliable. It couldsave you literally months of effort so think hard aboutgathering, storing and analysing data effectively. Getadvice from statisticians where available, but don’tbe ruled by them; through our own experience we havefound that as in all professions, there are good onesand bad ones.

Analysing data. Analyse what you have soon; thiswill also help you to see which data is the most use-ful. Some measurements may prove unnecessary. Atypical error of many projects is to take more num-bers than they can later analyse. Don’t waste farmers’time if they are reluctant to help take the data. Theyare probably busy. The main thing is to maintain goodrapport with them until the end of the season, whenyou can discuss the results in a community workshop.

Don’t over analyse the results. Nobody cares if theincidence of CBB was 1.51% or 1.59%. The differ-ence is not significant. If several different treatmentsyielded similar, low pest or disease incidence, admitthat the difference is insignificant and perhaps eventhat it has more to do with background noise (rain,

drought, micro-environmental differences betweenplots, an especially clean harvest the year before etc.)than with the experimental design.

Graph everything out before writing, try to be vi-

sual. Or at least try to have a point. Even if you donot present a lot of graphs to the farmers, graphinghelps to have things clear in your own mind and nowwith computer programmes, it’s easy: in a few min-utes you can graph every variable against every other.If you do this you will sometimes see unexpectedthings (see the Ecuador Case Study for examples ofsimple graphs). We learn to interpret graphs in schoolbut farmers who have been to school less may have adifficult time reading graphs. However, natural lan-guage is hardwired into the human brain, and farmershave as sophisticated a grammar as researchers do.Try to convince them of research results by talk andby showing them things in the real world.

Presenting the data convincingly. What farmers findmost convincing is another farmer. Even if they donot know the farmer, they can tell by his dress andspeech that he is a farmer, and will identify with him.If another farmer says, “I tried pruning my coffee treesto control diseases, and I found that it only took a dayto do, and my coffee was much healthier as a result,”it will be more convincing than all the graphs andphotographs an agronomist can show. If you are think-ing ahead to a follow-up extension program, considertaking some videos of farmers, to show later to otherfarmers, possibly on television.

Collect farmers’ authentic statements. Do notbowdlerize them or rewrite them into dead prose. For

A Colombian coffee farmer; don’t only participate with

stereotypes.

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instance if the farmer says “vergón” don’t write“bueno”. If the farmers say “what is the medicine wecan use to get rid of this nematode?” write that. Don’twrite “the villagers requested chemical control foreliminating certain soil pests.”

Photograph them. In some parts of the world peopleneed to be asked permission before taking their pho-tograph. In other places people don’t mind. Be sensi-tive to the differences. Many rural people have fewor no photographs of themselves. If you tell them thatyou are going to send them a photograph, then do so.It is most probable that in your final presentation whatthe local people will most enjoy will be the photos ofcommunity members.

Give them copies of the research. They will appre-ciate the thought, even if everyone in the communitydoes not read the report. They may show more inter-est in short statements about the people and the com-munity, and statements in clear language about themost appropriate technical results of the project (e.g.“We found that many groves in the community haduneven shade, and that some shade trees need to bepruned and others planted in order to achieve an even,medium shade”). Most Latin American smallholderfarmers do not understand the concept of percentages;they understand absolute values much more clearly.

Participatory evaluation. Hold participatory evalu-ations with the community to discuss the results withthem. Before the meeting starts, arrange to have acommunity leader open the meeting, and then turnthe time over to you. Do not simply call the meetingto order and start talking; it undermines local author-ity.

The event should not last more than two hours. Set atime to start, and if few people come, wait 20 minutesand start anyway.

Treat the event more as an open house. As other peopledrift in, present the results again to them. Explain topeople that if they have already heard the results andwant to leave, that you won’t mind. The main thing isto collect their opinion about the research. Small, re-laxed groups are better for this than a formal, townmeeting where two or three dominant farmers do allthe talking. Cover the following points:

� The treatments (the things we tested).� The results (which treatments achieved

the de sired results; modifications in thetreatments, made by farmers).

� Recommendations for the future(technology ready-to-adopt, technologythat needs more research).

Inviting local people to meetings. Each area has itsown style. Tightly organised communities have peoplewho can invite others to a meeting. Consider makinga written invitation to the participatory evaluation.Most farmers can read, and even those who cannot,will ask another family member to read the paper tothem.

Case histories from the project. A useful way ofpresenting results can be a case history, especially ifthe results are more qualitative than quantitative. Itgives you a chance to present more of the issues andproblems and it may be more acceptable to those thatcommissioned the work than to present the results asa scientific study. See specific case studies of FPR inthe following countries in Part II:

Colombia, Ecuador, Mexico, Honduras.

8.2 EXTENSION

Successful participatory research generates techno-logy that must still be extended over a broader impactarea. Participatory research is not a substitute for ex-tension, because it impacts relatively few farmers di-rectly. This book is not about extension but in Table 6we summarise some of the models for extension in-cluding direct, indirect, and mass media. In your re-port you may want to make recommendations aboutwhat next steps to take to transfer any useful resultsof your research.

Ultimately, participatory research has to be judgedby the new technologies that it generates, but espe-cially by the ones it succeeds in handing over toextensionists in a form that they can use. This will bea challenge: essentially you will have to assess theusefulness of the technology (including an estimate

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TYPE OF

EXTENSION

Direct

Indirect

Going public

FFS

Mass media

BRIEF DESCRIPTION

Face-to-face community andindividual meetings, led by anextension agent.

Work through NGOs and oth-ers who have extensionprogrammes in communities.Teach their extension agentsand give them pamphlets andother support material.

Demonstrations in fairs andother public places.

Weekly meetings and discoverylearning.

Television, radio, newspaper.

Advantages

Can be of high quality, de-pending on the extensionagent.

Can allow the programme tohave a large multiplier effect.

In an hour or 2 you canpresent an idea to severaldozen people from severaldistant communities. You canalso distribute seeds, litera-ture, and other materials.Allows audience feeback.

Good for knowledge inten-sive technologies such asIPM.

Can reach a large audienceat low cost. Messages can betargeted to farmers, e.g.broadcast early in the morn-ing. Quality of the messagecan be quite high (using pro-fessional communicators,clever scripts, local lan-guages etc.)

Disadvantages

Can be expensive and oflimited range (except inthe case of certain massprograms, e.g. that of theColombian Coffee Grow-ers’ Federation).

Quality of the messagedelivery may decrease.Unless you pay and su-pervise other institutions,they may not be motivatedenough to transmit themessage well.

The setting can get hec-tic. Works better withshort messages and visualdemonstrations. Theextensionist must have atalent for showmanship topull this off.

Costly and slow, needs at-titude change by exten-sion and research.

Feedback from the audi-ence is limited. Some“channels” of communi-cation are limited, e.g.one cannot show thingson the radio.

of costs-&-benefits) and give the extensionists asmuch help as possible in how to transfer it.

If we take the CBB as an example, IPM is the sug-gested method, but this involves several techniques,so how should the extensionist organise the topics?Should he start by transferring the most important (e.g.good harvesting) or perhaps the easiest (e.g. pruningor chemical fertilisation) or the one the farmers wouldfind most exciting and engaging (e.g. releasing para-

sitic wasps). A good participatory project with pro-longed farmer interaction, might give you some ideason how to help the extensionist.

8.3 KEEPING THE PROJECT GOING

Most projects are short, frequently they are only juststarting to yield the most interesting results when funds

Table 6 Extension taxonomy

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run out. And in our experience, many of the advancesof a project can rapidly dissipate once it is finished.So you should build this pessimistic (but realistic) as-sumption into the work. Beginning in the second yearof the project, continue to document results, but alsostart to encourage farmers to innovate on their own,so that you stand the maximum chance that at least afew of them will feel permanently empowered by yourstudy.

8.4 OTHER THINGS TO BEAR IN MIND

Monitor how farmers adapt, adopt, & reject

technologies.One of the biggest shortcomings fromthe project from which this book was developed, wasthat researchers and agronomists tend to see farmerparticipatory research along the model of on-stationresearch. They emphasise variables like yield and pestincidence rather than costs and feasibility problems.The Colombian part of the project did a better jobthan most at reporting on farmers’ evaluations of tech-nologies. For example, they described teaching for-mal sampling to farmers, who then rejected it becauseit was too time-consuming, and because the farmersalready knew which parts of their groves had hot spotsof CBB, and thus needed control measures (Colom-bia Case Study). Most of the country projects anx-iously showed how many farmers had adopted tech-nology as a result of contact with the staff. But fewresearchers were willing to report on how farmersadapted technology to fit their own conditions. Thisis the greatest intellectual stumbling block to FPR,researchers will not realise that a farmer can improveon a scientist’s ideas.

Holding farmer experimenter workshops is a quick,inexpensive way of learning and reinforcing farmer

experimenters. Invite farmers who have done experi-ments to meet together and explain and demonstratetheir research to each other. Write a proceedings vol-ume (Aristizábal & Salazar 2000, López 1997,Rodríguez & Bentley 1995 a&b).

Reward farmer experimenters . Researchers, writ-ers, and artists can be motivated to be creative notonly by the promise of more money, but by the hopeof winning recognition. Pulitzer, Oscar and Nobelprizes, and admission into the National Academy ofScience are just some of the rewards that inspire pro-fessional people to work harder. As the renownedanthropologist Bob Netting used to say, “People cannever get enough prestige, yet it is so easy to make.”Reward farmers who invent really useful items withthings like:

� Their picture and name in the newspaper.� A handsome presentation plaque.� A special dinner in their honour.

Virtue that is praised, grows.

Technology evaluation. There has been a lot writtenon how to involve farmers in evaluating and validat-ing research by scientists. The CIAL method is per-haps the best known (Ashby et al. 2000). Sperling &Scheidegger (1995) describe how farmers can be in-volved in evaluating pre-released varieties of beans.Mauricio Bellon discusses several techniques forevaluating technology with farmers. One of the moreinteresting new ideas is that researchers can showfarmers new varieties of maize (in the field, at matu-rity) and then offer them for sale to farmers (at thecost of local maize grain) and use the sale informa-tion to quantify which varieties farmers prefer (Bellon2001).

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There is an almost gravitational pull towardputting out of mind unpleasant facts. And our

collective ability to face painful facts is nogreater than our personal one. We tune out, we

turn away, we avoid. Finally we forget, and forgetwe have forgotten.

Daniel Goleman

9.1 REVIEW OF THE PROJECT CASE STUDIES:

WHAT WORKED AND WHAT DIDN’T15

On the CFC CBB project, scientists and farmersseemed more comfortable working together on adap-tive research, in more or less formal platforms (e.g.community research committees or with designatedfarmer-experimenters). Researchers were not as in-terested in trying to supporting farmers in collegiate,level 4 research, where the farmers proposed and man-aged the topics.

The adaptive research went smoothly. Researchersproposed ideas that were novel, at least to the farm-ers, like the use of coffee pulp as organic fertilizer,and forage groundnuts as cover crops (in Guatemala).In most Project countries, researchers either intro-duced or reinforced gleaning to control the CBB. Thetendency for farmers was to adapt the recommenda-

tion, not necessarily collecting berries from theground, but by performing an especially thoroughharvest, which they found less tedious than groundgleaning, and which also gave them more marketableberries. In a nice piece of validation of this adapta-tion, Colombian researchers showed that the berriesfarmers collected during cleansing harvests paid forthe labour needed in 98% of the cases (see ColombiaCase Study).

The Colombian Project developed a functional, prag-matic structure for collaborating with farmers. It wasbased on the existing community groups, which weresupported by municipal extension agents of the Co-lombian Coffee Grower’s Federation, with ideas forresearch provided during weekly visits by scientistsfrom the Federation’s Cenicafé research centre. Inother words, like much that happens in Colombia, thework was based on a sui generis model rather than ontrendy concepts from the “development literature”.The Colombians adapted half a dozen researcher ideasto farmer conditions and encouraged the further de-velopment of one of the farmers’ own ideas. Farmer-researcher meetings were also successful in provid-ing feedback to Colombian scientists at the station,who did not visit communities, an important but of-ten neglected part of FPR.

Social research. Because of the importance of har-vest techniques for managing the CBB, the anthro-pologist recommended studying harvest systems inGuatemala and Ecuador. The idea was to get a basicpicture of how workers harvest coffee, e.g. how muchtime they spend per tree, if they work alone or in pairs,

15 The reader may want to refer to the case studies at the end of the book before reading this chapter.

Some farmers like to be photographed Others are not so sure

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the tools used (baskets, mats etc.) and how many ber-ries are dropped onto the ground and left on trees (tobecome CBB habitat). The anthropologist also sug-gested comparing the thoroughness of harvesting onsmall, family farms vs. on large estates. The nationalresearchers showed interest in the topics, especiallyin Ecuador, where they did carry out a small study onharvesting. In both countries researchers lacked con-fidence in conducting the study. The anthropologistoutlined a research protocol, but it may have seemedtoo unusual or too time-consuming for local research-ers. It probably did not help that the anthropologistpointed out that the study of harvest technology wassocial research, but was not participatory. This seemedto discourage researchers, who were thinking of par-ticipatory research as a kind of holy grail. Longer ormore frequent visits by the anthropologist may havehelped to conduct this research, since the agronomistsreally were interested in the results, but needed a bitmore advice on method.

Hot spots . Project entomologists (Baker and others)had been suggesting for several years that a functional,compromise technology would be the application ofinsecticide to hot spots: places in groves with highdensities of coffee berry borers. It would control CBBwithout lots of tedious labour, and would leave largeareas of the grove as un-sprayed refuges for benefi-cial insects. Then farmers in Mexico and Hondurastold the anthropologist (Bentley) that they could al-ready identify hot spots, and applied insecticide onlyon those spots. Bentley and national researchers dis-cussed the idea of documenting farmer’s innovations.Mexican researchers (Jarquín and Barrera) did con-duct a study which supported the idea that farmerswere able to accurately identify hot spots. Some moreresearch is needed, and unfortunately the idea cameto light so late in the Project’s life that little could bedone with it.

Scientists often relate well with farmers , when theymeet them. In every case, when we observed scien-tists and farmers interacting, they had things to say toeach other. Scientists did not talk down to farmers orpatronise them. We feel that many researchers couldwork productively with farmers, if given the chance.The main barrier seems to be that senior research sci-entists find it difficult to take time away from teach-ing, administration and the laboratory bench to go tothe field. Institutions need to make more of an effort

to get scientists and farmers together. The Colombianapproach, of bringing farmers to Cenicafé is promis-ing. Any method would probably be worthwhile, aslong as scientists and farmers interact. Don’t rely onextension agents to do all the interaction with farm-ers.

Farmer inventions? Researchers and even extensionagents have a hard time relating to the idea that afarmer might invent something. The staff tends to treatsuch observations as amusing, or as irrelevant or un-important, not as something to pick up and work on.Even the formal, participatory research movement ismuch more comfortable with involving farmers in last-link, adaptive trials (Ashby et al. 2000). We have al-ready mentioned how, in India, a farmer suggestedmaking a slit in the picking mats, to make them easierto fit around trees, and to keep more fruit from beinglost on the ground. In the case of the hot spots, (men-tioned above) Mexican researchers obviously thoughtthe idea was of some merit, but did not emphasise itin their presentation to other researchers at the finalProject meeting in Costa Rica in October, 2001. Westill have a long way to go; just getting the researchcommunity to recognise farmer’s experiments andsupport them requires a major change in perception.

Looking for a method. From the beginning of theProject, national staff wanted the protocol for partici-patory research spelled out in great detail. They weremore comfortable with experiments that resembledexperiment station trials, in part because the methodwas easy to extrapolate from their university train-ing. Experts brought in to teach participatory research(the senior authors included) were more interested inphilosophical issues, which the national staff foundfrustrating. It took us a while to begin working onnuts-and-bolts recommendations for how-to-do par-ticipatory research. To their credit, the nationalProjects all did something worthwhile, and unique.

Old friends . Most projects have their “pet farmers”,although “farmer buddies” might be more accurate.These are the people who are willing to receive lotsof visits, who converse well with outsiders, and whohave benefited enough from the project to say some-thing nice about it. The farmer buddy is also willingto carry out the project’s field trials. Some projectsfoster whole groups of buddies, in a safe, friendly vil-lage.

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During this Project, the Guatemalan researchersworked with Chocolá, a community they have col-laborated with for years. On the other hand, in Mexico,Ecuador and Colombia, the staff worked with com-munities that they contacted specifically for thisProject, although in each case they used existing net-works16 to contact the villages. In Honduras, research-ers seemed to use a mixed approach, working with ElTigre and Agua la Piedra, which have had a lot ofprevious contact, while also starting work with somenew places. The advantages of working with the samefriendly people year after year should include lowertransaction costs (you don’t have to explain who youare and what you want to do each time; you alreadyknow them and can get right to work). Another ad-vantage is that after several years of training, the old,friendly villages should have received many freshideas from researchers, which should stimulate morecreativity. However, we did not observe any majordifferences. Researchers rapidly gained rapport in thenew communities and completed research with them.

Many farming communities are remote. Except forChocolá in Guatemala, El Tigre and Babilonia inHonduras and some communities near Chinchiná,Colombia, most communities are several hours’ driveaway. One does not just drop in on them. It costs a lotof time and money to visit distant communities. It addsto the cost of participatory research and is anotherreason for organising one’s calendar of visits care-fully with local people.

If farmers really participate in trial design, then

there are no replicates. This may seem counter-in-tuitive. But as we saw in the Honduran case, the ex-periment was designed to have one treatment (IPM),and a control (farmers’ practices). Yet, in each case,farmers introduced changes (one applied insecticides,one gathered first fruits, one stumped part of the plot).On the one plot where farmers did not change the IPMtreatment, researchers took advantage of the fact that(only on this one farm) the IPM plot was far awayfrom the control, so the entomologist introduced para-sitic wasps on the IPM plot. In other words, farmersare individuals, and when they have the freedom tochange a variable, they will do so in individual ways.

Each plot will be different. In the Honduran case in-stead of having a treatment plus a control on four rep-licates, we ended up with eight treatments and no rep-licates. One wonders about the statistical validity ofthe large amount of data taken on these plots. In suchcases, we need to spend more time thinking about whythe farmers made the changes they did, their opinionof them, and collect some basic data on costs, planthealth, and harvest.

Gleaning. Picking up coffee berries from the grounddoes help control the CBB, and uses no insecticide.But it is so tedious that we are reluctant to recom-mend it highly, especially with the costs of labour ris-ing and the cost of coffee falling. Some of the berriesthat are recovered can be sold, which pays for thegleaning, if the price is right, but if these gleaningsare of poor coffee it only adds to the world’s stock of‘triage’ which some national and international bodiesare now trying to destroy. Some countries (Mexico,Guatemala, Ecuador, India) have traditional gleaningpractices. In most cases, it is the very poor who askpermission from neighbours to glean their groves,spending the day stooped over to collect two to threekilos of berries which can be sold for a dollar or less.In Ecuador, Project extensionists were encouragingfarmers to pick berries up off the ground, but mostteam members in Latin America were not keen to re-inforce gleaning. However, in Colombia it rains moreoften, so coffee flowers and bears fruit all year, andthe berry CBB is a much greater problem there.Cenicafé in Colombia recommended Re-Re (regularpickings and gleanings). Farmers did not adopt glean-ing, in part because of the high labour costs and thetedium, but they did start to harvest more frequentlyand more thoroughly as a result of Cenicafé recom-mendations (Castaño 1998).

Other cultural controls. Because of the above prob-lems with gleaning, what farmers need are techniquesthat help keep berries off the ground and from beingleft on trees, but which need less labour. The pickingmats in India are one of the few practices that seem tobe labour saving, and help keep berries off the ground.Some Ecuadorian harvesters sew two fertiliser bagstogether and spread them on the ground to recover

16 The Union of Ejidos in Mexico, the lapsed self-help groups in Ecuador, villages organised by extensionists of the Coffee Growers’ Federation inColombia.

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berries. We hypothesise that this practice profitablymanages the CBB, but our initial study of this systemwas incomplete.

In hindsight. The ethnographer (Bentley) had moreof an impact on Project researchers by working withthem in the field than through workshops. The projectstarted in mid 1998, but the anthropologist did notstart working with the researchers until the projectheld a workshop in Chinchiná, Colombia in May 1999,to design participatory research. But by then the coun-try programmes had planned their research, and theworkshop did not give them the guidelines in methodthat they expected, so interventions by the anthropolo-gist and other FPR experts at that workshop were oflittle value. But Bentley’s visits to each Project beganto have an effect. Bentley, Jarquín, Barrera and oth-ers noticed that farmers perceive hot-spots in Mexicoand in Honduras, and this made its way into the re-search, at least in Chiapas. In Guatemala, we plannedthe groundnut and pulp experiments during Bentley’svisit (June 2000), and researchers presented the re-sults in October 2001. In Ecuador, most of the researchwas planned during Bentley’s trips there (May 2000and June 2001). In retrospect, Bentley and Bakershould have supported each country by visiting themin the field and planning their research on a case bycase basis.

Sampling. An inordinately tedious sampling methodcropped up in Ecuador, Honduras and India, althoughin different form in each one. In Ecuador, extensionistswere using it in 2000, but by 2001 seemed to haveabandoned it. In Honduras the project was payingfarmers to do the sampling on the IPM plots understudy (because the data was useful to researchers, butfarmers would not have done it without payment). Andin India, extensionists made numerical sampling amajor part of their work in pilot FPR villages, althoughfew farmers seem to have adopted sampling on theirown.

Not wild and crazy. Project researchers proceededcautiously, planning a few studies that they were con-fident would yield results. With the exception of theColombians, who worked on over a dozen ideas, mostcountries studied two to four topics.

The Ecuadorians were especially open to new ideas,but Bentley encouraged them (perhaps mistakenly)

to stick with five topics, arguing that it was better todo a more thorough job on a manageable number ofideas. As a result, we were aware of some promisingtechniques that we did not study. Cenicafé recom-mends stumping trees every five years, to maximizeyoung woody growth, to increase yields and havesmaller, more easily managed trees. This method mayalso help manage the CBB but a study on this wouldhave taken too long for the present project.

A code for working with farmers? A code of con-duct for working with farmers might evolve from thismanual and similar efforts. In FPR we need a code ofconduct that emphasises the positive things we needto do to facilitate productive research with farmers,more than a list of thou-shalt-nots.

What works with farmers? One thing that works isgoing to an organised community with a nearly fin-ished technology for them to validate. The commu-nity often finds something useful in the idea. We hadseveral examples of this during this Project.

� Control of CBB with sticky covers inColombia

� The caturra coffee variety in Ecuador� IPM techniques in Honduras� Organic fertiliser in Guatemala

In India, Ecuador, and Colombia researchers are work-ing on CBB traps with farmers. While a final trap has

Sometimes you have to stop and lend a hand.

(Colombian project staff handing out plastic

sheeting from an experiment, to earthquake

victims).

victims)

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not been developed, scientists in all three countrieshave worked side by side with farmers, hanging thetraps in trees, pouring in the alcohol bait, evaluatingthe results. Because of this, the scientists realised thattheir traps are not ready. Had they tried the traps on-station, they might be under the impression that thetechnology was complete.

One-off trials with machinery are really worthwhile.The water-saving mechanical pulpers (beneficioecológico) developed by Cenicafé, Colombia seemedlike such a good idea for dry areas of Ecuador. Yetwatching farmers and extension agents try to makethe Colombian machines work in Ecuador immedi-ately showed how we would have to either re-designthe machinery to handle unripe berries, or work withEcuadorian harvesters to pick only ripe berries (Ec-uador Case Study).

What doesn’t work?

Researchers rarely notice farmers’ own innovationsor even farmers’ adaptations of new technologies.Studying farmer adaptations is important: it may helpus to simplify or improve a technology.

In most cases, even formal experiences in communi-ties do not provide enough feedback from farmersback to researchers.

Agricultural scientists and agronomists are uncom-fortable writing qualitative results, for example, in theabove case of the Ecuadorian trial of Colombian ma-chinery, the researchers would not write up the re-sults, because they could only be done in narrative,not in a table of numbers. This is not to criticise theEcuadorians; few other researchers wrote narrativeaccounts of what actually happened in the field.

Compare with success stories from other crops.

Success in other crops has been more modest thanothers like to admit. The FAO Asian Rice IPMProgramme was successful because President Suhartooutlawed a number of major pesticides. Even in this‘classic’ case however, the long term effect of this isless than clear. As Oudejans (1999) puts it “It appearsthat after 1987, when the Minister of Finance with-held the subsidy for pesticides and the budget for pro-curement was lower, the large stocks which has beencarried over from year to year were gradually mar-keted. When, by 1992, the stocks were exhausted, the

purchases of pesticides went up again to meet thedemand of government agencies and private parties.”

Some final comments on FPR platforms . In Chap-ter 2 we discussed platforms for farmer participatoryresearch. We have tried to incorporate the best of eachin our approach, but some constructive criticisms maynow be in order.

Some leaders of the FFS approach insist that FFS isextension, not research (Kevin Ghallager, personalcommunication). Others emphasize how FFS teachesfarmers to experiment. Some of the informal experi-ments that farmers do after taking an FFS are trulygeared to learning new insights; like farmers in Indo-nesia who cut rice plants, to mimic different kinds ofinsect damage, to then follow the life history of theplant (and see how much grain it yielded) (YunitaWinarto, personal communication). We recommendthat FFS be used as a tool to stimulate farmer experi-ments.

The Zamorano method stimulated hundreds of farm-ers to experiment. Those of us who were involvedwith it over-emphasised the teaching program, anddid not spend enough time documenting and follow-ing up on farmer experiments. The basic idea of teach-ing farmers background information (the fathers ofinvention) is still sound and deserves more replica-tion and write up.

The CIAL actually has much in common with exten-sion. In practice, CIALs and FFSs are converging(Braun, et al.2000). In the field, many of the agrono-mists who use them, use both and are blending them(e.g. enriching field schools with CIAL-like trials).

The CIAL needs to learn more topics, and to workmore with inventing and modifying technology, ratherthan just validating and teaching it. Back-&-Forth isstill being used successfully by its home institution(CIFEMA in Cochabamba). It would be highly pro-ductive if such a practical, rapid method for invent-ing farm machinery could be adapted to IPM.

Is coffee different? When we started to write thismanual, in November 2000, we thought it was. Nowwe’re not so sure. But then the complex and interest-ing thing about IPM is how each crop and each pestIS different. The bit about hot spots was really inter-

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esting, and you don’t see a phenomenon like that inevery crop.

9.2 CONCLUSIONS

Participatory research is not easy, and unlike conven-tional research, an established protocol is only emerg-ing now. Like all research, FPR takes time. ThisProject could have used another two years.

The notion of farmer participation has spawned lotsof rhetoric and some modest results, especially inadaptive research, doing the final tweaking at the vil-lage level.

Few people are asking (yet) about issues like cost-effectiveness of staff time or of the technologies. Fromour experiences with the CBB project, we found thatthe researchers were much more heavily influencedby their previous experience in their own countriesthan by trends in development “literature.”

Some of our colleagues had worked for years in con-ventional research with the CBB, and many of themhad worked with farmers; those experiences formedthe intellectual foundation for much of the project’splanning.

We may have been too ambitious. Most projects onlywork in one country. We worked in six (not countingJamaica). One thing that saved us is that in each coun-try researchers were involved on some level; theynever turned everything over completely to the ex-tension agents. The researchers had met before, atCBB conferences, so they knew each other, and sharedinformation with colleagues in other countries.

Pests can be maddening to research, because one yeara species may almost disappear, only to return in forcea few years later. Towards the middle of this Project,the target pest, the CBB, suffered a dramatic declinein many countries. We are still not sure whether thiswas due to the fact that farmers had adopted techni-cal recommendations, or because of the stochasticfluctuation of the insect’s population. But by the endof the Project, farmers no longer felt that the CBBwas nearly as serious a problem as the serious ero-sion of the price of coffee.

Could we have done better? Yes. But we certainlydidn’t fail. Every country programme did some re-search, of value, and it was based on their own ideas.Each one was unique. This shows a high degree offreedom of thought. Having said that, we flounderedaround quite a bit at the start over the idea of “partici-pation.” A year into the project we were still asking:

� Which farmers would participate?� What would they contribute?� What research methods would we use?� And even: Is FPR really research or is it

just an extension tool?

By the end of the Project, much of this had beenworked out, which is one reason we decided to writethe project results as a manual. It is not so much areport of what we did, as much as guidelines abouthow we would do it next time.

Self-Criticism. We have raised criticisms of ourproject, in the interests of credibility and honesty. Wehad a good team of professionals, and any shortcom-ings reflect not so much personal failure as the diffi-culty of collaboration between scientists and farm-ers. By comparison, cover crops have been a favouritetopic of participatory research and development inLatin America since the mid-980s. Yet a recent bookon the subject suggested that, despite the fanfare fromNGOs, researchers are only now starting to under-stand the limitations of these crops and that:

“In most cases the methodologies used so farhave not allowed researchers to engage withcampesino community realities. This has ledto extractive and inappropriate research. TheInstitutions acting as links between communi-ties and research institutions have to increasetheir capacity to suggest research topics andtheir negotiation power to establish contactsbetween research institutions and communities,which would serve to define topics, productsand cost/benefit distribution” (Anderson et al.2001:117).

That’s an amazing revelation: FPR in cover crops in-dulged in extractive research that did not engage withfarmers’ reality, even though some very good NGOsand research institutes and universities were involved,and in spite of how easy cover crops are to work withcompared to coffee.

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Our Project tried the more difficult task of research-ing a cryptic insect pest in a tree crop, in only threeyears, yet we still came up with some worthwhile re-sults.

9.3 MAIN ACHIEVEMENTS

The Project produced a substantial list of R&D con-tributions:

Adaptive research:

Forage groundnut as a cover crop (Guatemala)Coffee pulp as fertilizer (Guatemala)Use of Caturra variety (Ecuador)Observations on problems with beneficio ecológico(Ecuador)Re-Re (economic validation, Colombia)

New technology, developed by scientist-farmer col-

laboration:

Manure slurry to control coffee diseases (Ecua-dor)17

Picking mats (India)Strip applications near stumped groves (Honduras)Picking dry berries in March, then spraying (Hon-duras)Greased bin covers (Colombia)Greased harvesting barrel (Colombia)Trap trees in stumped groves (Colombia)

Validations by scientists of farmer technologies:

Traditional planting styles in EcuadorTraditional harvesting in Honduras

Strategic on-farm research

With alcohol-bait traps (Ecuador, Colombia, India)And with wasps (all countries)

Rejection by farmers of unworkable technologies:

Beaveria bassianaSampling

Researchers in all countries reconfirmed the impor-tance of harvest systems for CBB control and the factthat new harvest and gleaning techniques must ac-count for labour costs and the price of coffee.

Finally, and perhaps most importantly was the workwith hot spots. Researchers in Honduras and Colom-bia observed that farmers identify them. The Projectstaff in Mexico conducted a detailed study of farmerknowledge of hot spots. This is a real breakthrough.It means that future researchers can recommend thatfarmers apply any given technology just to hot spots,and need not undertake cumbersome numerical sam-pling to find them. Though they still need to find outhow farmers do it, so that it can be incorporated intofuture extension activities.

Did different approaches emerge? As seen in theprevious section, there was a great deal of differenceon the specific technologies studied by each of thecountry Projects. Many topics were only studied inone country.

Colombia and Mexico and to a lesser extent Ecuadorpaid formal attention to selecting communities andnegotiating research with them. Honduras and Ecua-dor worked in places where they were already com-fortable.

All of the country Projects based their work on exten-sion. The senior authors heartily support the notionthat participatory research involves bringing farmersup to speed on chosen concepts of diagnosis, bioecol-ogy and pest management as part of participatory re-search. But FPR is not just extension.

Farmers must build on what they learn to help re-searchers create new knowledge, otherwise the expe-rience is not participatory research. In this Project, aweakness in all or most of the countries was a lack ofresearcher interest in farmer innovations and in theways farmers modified techniques learned fromprogrammes.

9.4 TOWARDS A PROTOCOL FOR WORKING WITH FARMERS

In a linear sequence, the life cycle of an FPR projectshould be something like this:

1. Pick a topic.2. Pick a region.

17 The manure slurry was invented elsewhere, probably in Nicaragua, but agronomists working with farmers on our project observed that thetreatment was not just a foliar fertiliser, but also controlled disease.

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3. Do a needs-analysis.4. Determine implicit and explicit demand.5. Don’t just identify problems, identify demand.6. Identify gaps in farmer knowledge (deep, shallow,

missing, mistaken).7. Document research by farmers.8. Pick the communities.9. Decide the appropriate levels of farmer collabora-

tion.10. Establish farmer-researcher committees; also iden-

tify individual farmers to work with.11. Train farmers (fill in the gaps of knowledge).12. Include diagnosis, biology and ecology, manage-

ment.13. Design experiments.14. Conduct experiments with farmer committees and

individuals.15. Do community evaluations.16. Document results: farmer improvements on the

technology, farmer complaints (new evidence ofdemand).

17. Validate farmer inventions.18. Link with extension (direct, indirect, mass me-

dia).

9.5 THE FUTURE, SOME RECOMMENDATIONS

If the participatory approach is to become part ofmainstream research, as we believe it should, thenthis inevitably implies that it should be taught in uni-versities. Indeed there is now a need to radically over-haul the curriculum for agriculture students to takefuller account of the problems that 21st century farm-ers face. Although the subject matter of this manual

is new, there is now enough methodology and of suf-ficient rigour, to support an initiative of this approach.

Recommendations, specific to coffee IPM would in-clude:

� Continue research on hot spots.

� Use hot spots as the basis for extensionrecommendations (“Apply technology X inthe hot spots, instead of in the whole grove,to save on expenses”)

� Continue to closely monitor the relation-ship between the price of labour and the costof coffee (for cultural controls).

� Continue validating some of the newtechnologies (e.g. manure slurry for controlof disease, forage groundnuts). Recommendsome of the new technologies in extensionprogrammes (e.g. greased covers on bins,picking mats).

� Work with alternative marketingprogrammes.

� Validate mass media as an alternative toface-to-face extension.

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* Based on a seminar given at El Cajón, Honduras, August 21-24, 2000, by Jeffery Bentley, funded by the CFC CBB Project. Many thanks to theparticipants: Valeriano Chay Méndez, Oscar Campos, Juan Francisco Hernández, Raúl Muñoz, Angel Trejo, Hugo Paz, Mario Williams, RodneySantacreo, Juan Francisco Barrera, Ramón Jarquín.

PART II

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FPR (Farmer Participatory Research)Farmers can participate in research bycontributing:

LandLabourIdeas

Of which the ideas, or knowledge, are the most im-portant.

Development scholars agree on this, but formal de-velopment efforts have made little progress on howto understand farmer knowledge. Yet the anthropo-logical methods and concepts of ethnoscience havebeen widely used by academics for 30 years. Ethno-science is not overly difficult to understand, and canbe helpful for documenting farmer knowledge andincorporating it into agricultural research.19

ETHNOSCIENCE:INTRODUCTION

Folk categories of knowledge are formed by mentalconcepts attached to word labels.

These concepts are organised into taxonomies, whichare usually hierarchical (“kinds of things,” e.g. a dogis a kind of animal.) All languages use taxonomies,although there is a fair amount of leeway in how tax-onomies are formed. E.g. Quechua may not classifythe condor as a bird. Many languages spoken in theAmazon do not have specific words for “parrot.”

This is especially true for insects, which traditionalpeople often lump into broad categories which includearthropods, worms, even rodents and lizards (Brown1984). These are actually minor differences in classi-fication and do not mean that traditional peoples mis-understand the way the world is put together.

Brent Berlin (1992) has proposed 6 levels of folk tax-onomies, which are repeated cross-culturally:

0. Kingdom1. Life form

2. Intermediate3. Generic4. Specific5. Varietal

Each of these levels has its own linguistic properties.Most striking is that folk taxonomies use generic andspecific labels much like Linnaean names: e.g. “hielonegro” (where “hielo” is the generic term for mostplant disease and “negro” is the specific name forsevere disease).

Folk taxonomies make much use of residual catego-ries, e.g. “just a bug” to label left-over, or under-clas-sified organisms.

Some folk taxonomies are in the form of partonomies,or sets of categories that are “parts of” another, e.g.parts of an ox plough, or parts of a plant or of an in-sect.

The main differences between folk and scientificknowledge is that:

Folk knowledge is local, with no pretence to de-scribing the world in universal terms

Folk taxonomies do not usually fill each of the 6taxonomic levels; many are left blank

Folk knowledge is (usually) stored mentally, whichconstrains memory. An entomologist can havemany more names for insects because they can bestored in writing

Similarities between folk and scientific knowledge,they both:

Have names for things (e.g. organisms) in the realworld

Use binomial labels, for some things

Organise categories into taxonomies

Sometimes there is a 1:1 correspondence between folkand scientific categories, but often there is not. Forexample, the concept of hielo is applied to 30-40 dif-

19 See Sillitoe (1998) for a similar idea.

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ferent bean diseases in Honduras. It is a concept ofreal world phenomena, but does not have any simpleanalogue in scientific terms.The structure of folk taxonomies is heavily influencedby whether the organisms that are being classified areeasily observed and culturally important (see Bentley& Rodríguez 2001).

Eliciting frames (for fieldworkers) include a fewsimple questions like:

What are the kinds of X?

What are the parts of X?

What is the difference between X and Y?

OTHERFORMALPROPERTIESOFFOLKKNOWLEDGE

Emic and Etic. These are two concepts borrowed byanthropologists from the linguistic notions of phone-mic and phonetic. Roughly, emic is local knowledgeand etic is scientific knowledge. An emic conceptcannot simply be described in terms of a scientificname.This is especially true of folk entomology. It isa poor definition to say that “cogollero (fall army-worm) is Spodoptera frugiperda).

Emic and etic descriptions can also be given forbehaviour. For example, when a Honduran campesinouses magical rites to control grassloopers, an ento-mologist may give one (etic) analysis of why the magi-cal rites seem to control the insects, while an anthro-pologist may provide another (etic) analysis of howthe rite functions.

MEANINGANDKNOWLEDGE

Scientific categories are based on semantic premisesof necessary and sufficient conditions: an insect ei-ther is or is not a Coleoptera. It cannot be partiallyColeoptera. As the above fall armyworm examplesuggests, folk definitions often make use of proto-typical semantics. Categories are often defined interms of best examples. E.g. in English folk biology,a robin is a good example of the category “bird”, whilea penguin is a poor example.

Lore. Defining a set of folk categories is a good startto describing folk knowledge, but traditional peoplehave a deeper understanding for each of those con-cepts, which we also need to know if we are going towork with traditional people as colleagues in research.

The sociology of knowledge may be rather complex,with different people (women, elders, ritual special-ists) knowing certain things. Games and drawingscan be used to elicit some of these differences (seeNazarea-Sandoval 1995). However, much of folkknowledge is shared by the entire group of people(see Hayes 1983).

Memory load. There is some suggestion that peoplecan hold about 500 names in their head. 500 personalnames of people. 500 names for plants. 500 placenames etc. This has obvious implications for folkentomology.

Chronologies. Some folk knowledge is organised intochronologies, e.g. the folk phenology of maize inHonduras.

Alternative classifications. Povinelli (1990) claimsthat the Emiyenggal and Batjemal peoples of Austra-lia classify animals in 4 different kinds of taxonomy(habitat, morphology, function, food criteria) depend-ing on context. In fact, agricultural scientists do thesame thing, with alternate classifications by phylog-eny (e.g. horse is a kind of equine) or by function(horse is a kind of livestock). IPM experts routinelyclassify diverse organisms into special categories like“pests of maize” or “pests of coffee” which are not atall phylogenetic.

EMICLABEL

Cogollero

ETIC DEFINITION

The larva of Spodoptera frugiperda (Lepidoptera, Noctuidae), especiallyin later instars, especially when in thewhorl of the maize plant.

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Regional synonyms. Unlike scientific classifications,folk taxonomies may use different labels for similarcategories, from one place to the next.

SHORT QUESTIONNAIRES

After a team has elicited farmer knowledge throughinterviews, if the research calls for quantified answers,these can be elicited through short questionnaires.

The short questionnaire is like a semi-structured in-terview, only with a larger sample:

There are 4-7 pre-defined questions, setaround a hypothesisThe sample of respondents should be cho-sen randomlyIf this is not possible, try to minimise bias(do not just interview the wealthy malefarmers near the highway)

Example, a study of maize ear rots in Honduras usedshort questionnaires to show that farmer knowledgewas comparable to scientific knowledge, with littleemphasis on magical or supernatural explanation. Theonly key idea the campesinos were missing was thenotion of a fungus causal agent (Bentley 1990).

COUNTRY

Ecuador

Honduras

Guatemala

Mexico

FARMER EXPERIMENTS AND INVENTIONS

Aprons of various mixes of organic fertiliser to improve soil fertility, control weeds and avoidmechanical damage to coffee trees.A fertilisation experiment with Schizolobium trees.

A new metal tool for harvesting cacao.

First fruits: early hand picking of broca-damaged coffee berries.

Fallen coffee fruit as a proxy for hot spots (with insecticide applied only on hot spots).

Rapid identification of individual coffee trees with high levels of CBB infestation, and immediateapplication of insecticide, but only on those trees.

No experiments documented, although in several communities the whole coffee system is so new itcould be considered experimental.

Application of 0.25 litres of endosulfan to one cuerda of coffee, to see if it is effective.

Varietal trial of caturra.

FARMER EXPERIMENTS

Farmers constantly experiment, but we often do notpay enough attention to them. Noticing farmer experi-ments is important for deciding how we can work withfarmers as colleagues (Table 7).

SUMMARY

We have seen that traditional farmers have knowl-edge, and it is organised in ways that are not as strangeas they seem. Farmers also conduct experiments. Inother words, (many) farmers are knowledgeable andcreative, which is something researchers look for inchoosing colleagues. However, farmer experimentsare organised in remarkably different ways from thoseof formal research (Table 8).

Farmers potentially have a lot to offer researchers,but their different styles make actual collaborationdifficult.

Farmers participate more in research depending onwhether they contribute:

1. Land and labour;2. Ideas for research and validation;

Table 7 Farmer participations by country

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CHARACTERISTIC

ShapeSizeRepetitionsNumbers (quantification)PlanningSerendipityWho is it for?ReplicabilityCapital cost

SCIENTIST

Square or rectangularThe same for each treatmentA mustImportantAbsolutely essentialLess oftenOthersAlways importantMore

FARMER

IrregularDifferent for each treatmentNot usedVisual analysis, with few numbersSometimes usedMore oftenFor that farmerNot alwaysLess

3. Research methods, or if-4. They actually conduct the research.

How and where to involve farmers depends on thenature of the research topic. Biggs has finally cometo conclude that there has been too much emphasison method, that the quality of the research staff andtheir work conditions are probably more importantthan method in determining the success of participa-tory research (Biggs & Smith 1998).

Researchers will have to design their own participa-tory methods, but some inspiration can be taken fromthe following:

Participatory plant breeding uses a kind of openhouse, allowing farmers to see advanced linesof breeding material that are still not released.Farmers comment on the material and some-times take some home to plant. The methodallows researchers to see what characteristicsfarmers select for, and to save several years ofbreeding effort (Sperling & Scheidegger 1995).Most farmers can be encouraged to do varietaltrials with the gift of some seed. Paul Richards(1985) gave rice seed to 50 farmers in SierraLeone, and they all planted the seed and ex-perimented with it.The Zamorano method.Back and Forth (Ir y Venir).Farmer-experimenter workshops.

SUGGESTED READINGS (ESPECIALLY IN SPANISH)

1. Bellon (1992) a case study of applied ethnoscience. Maize farm-ers in Chiapas have a detailed taxonomy for soil types andmaize varieties. Farmers use these taxonomies productivelyin making decisions to retain certain native varieties, evenafter adopting high-yielding varieties.

2. Bentley, Rodríguez & González (1994), an idea for trainingcourses for farmers that build on local knowledge to en-courage farmer experiments.

3. Ramírez (1989), a review in Spanish of the classic literature inEnglish on FPR.

4. Sims & Bentley (1999), a discussion of a soil conservationproject in Bolivia which started with FPR rhetoric. Re-searchers were allowed leeway in defining their own work,and the project developed 3 participatory styles, plus on-station research, all of which were functional.

5. Sims, Walle & Ellis-Jones (1999), original title: Guidelines forResearch on Hillside Farms: Participatory TechnologyDevelopment of Soil and Water Conservation Technolo-gies. Based on fieldwork in various countries, especiallyHonduras and Bolivia, this publication has detailed “how-to” sections.

6. Oltrogge (1975), an ethnoscience paper on wasps among a nativegroup of Honduras. The early date on the paper reinforcesthe idea that ethnoscience has been around for a while: itis not a fad.

7. Bentley (1992), a model for explaining how traditional peoples(Honduran smallholders, in this case) classify pests andother organisms.

Table 8 Comparison of characteristics of experiments by farmers and scientists

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REFERENCES CITED

Bellon, Mauricio 1992 “Conocimiento Tradicional, CambioTecnológico y Manejo de Recursos: Saberes y PrácticasProductivas de los Campesinos en el Cultivo de Variedadesde Maíz en un Ejido del Estado de Chiapas, México.” Pp.297-327 in Enrique Leff & Julia Carabias (eds.) Cultura yManejo Sustentable de los Recursos Naturales Vol II.Mexico DF: Grupo Editorial Miguel Angel Porrúa.

Bentley, Jeffery W. 1990 “Conocimiento y ExperimentosEspontáneos de Campesinos Hondureños Sobre el MaízMuerto.” Manejo Integrado de Plagas 17:16-26.

Bentley, Jeffery W. 1992 “El Rol de los Agricultores en el MIP.”Ceiba 33(1):357-367.

Bentley, Jeffery W. & Gonzalo Rodríguez 2001 “Honduran FolkEntomology.” Current Anthropology 42(2):285-301.

Bentley, Jeffery W., Gonzalo Rodríguez & Ana González 1994“Science and People: Honduran Campesinos and NaturalPest Control Inventions.” Agriculture and Human Values11(2&3):178-182.

Berlin, Brent 1992 Ethnobiological Classification: Principles ofCategorization of Plants and Animals in Traditional Soci-eties. Princeton: Princeton University Press.

Biggs, S. 1988 Resource-Poor Farmer Participation in Research:A Synthesis of Experiences from Nine National Agricul-tural Research Systems. Comparative Study No. 3. OFCORProjects. The Hague: ISNAR.

Brown, Cecil H. 1984 Language and Living Things: Uniformi-ties in Folk Classification and Naming. New Brunswick,New Jersey: Rutgers University Press.

Oltrogge, David F. 1975 “La Etnoentomología de AlgunasCategorías de la Orden Himenóptera entre los Jicaques.”In Ponencias de los Miembros del Instituto Lingüí stico deVerano, A.C. en la XIV Reunión de Mesa Redonda de laSociedad Mexicana de Antropología y la I Reunión deAntropólogos e Historiadores de Centroamérica y México.Tegucigalpa.

Povinelli, Elizabeth 1990 “Emiyenggal and Batjemal Folk Clas-sifications, Cox Peninsula, Northern Territory: ‘Figuring’Continuity and Contingency.” Australian Aboriginal Stud-ies 2:53-59.

Ramírez, Ricardo 1989 La Participación del Agricultor en laInvestigación: Alternativas para Responder a lasNecesidades Campesinas. Netherlands: INTER PARES-CELATER. 37 pp.

Richards, Paul 1985 Indigenous Agricultural Revolution: Ecol-ogy and Food Production in West Africa. Boulder, Colo-rado: Westview Press.

Sillitoe, Paul 1998 “The Development of Indigenous Knowledge:A New Applied Anthropology.” Current Anthropology39(2):223-252.

Sims, Brian & Jeffery W. Bentley 1999 “InvestigaciónParticipativa: Un Juego de Herramientas, pero no la Clavedel Universo.” ProCampo 85:16-21.

Sims, Brian, Robert Walle & Jim Ellis-Jones 1999 Guía para laInvestigación en Predios de Laderas: DesarrolloParticipativo de Tecnologías de Conservación de Suelo yAgua. London: DFID. 52 pp.

Sperling, Louise & Urs Scheidegger 1995 Participatory Selec-tion of Beans in Rwanda: Results, Methods and Institu-tional Issues. London: IIED Gatekeeper Series No. 51.

95

20Unless otherwise indicated, all information in this study is from Aristizábal & Salazar (2001).

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1. INTRODUCTION

The Colombian Project was housed at a research cen-tre, Cenicafé, which is owned by the Colombian Cof-fee Growers’ Federation. Cenicafé’s entomology de-partment began participatory research in 1998 in 9villages in the departments of Caldas, Quindío andRisaralda with 113 farmers, to develop technologiesfor integrated berry borer management under farm-ers’ real conditions, taking into account the naturaland human conditions of each community. Research-ers took farmers’, extensionists’ and scientists’ knowl-edge into account, to generate, validate, adapt, de-velop and transfer technology.

2. THE TEAM

Preparing the team for the FPR project. Beforestarting fieldwork, the Cenicafé team received train-ing in all aspects of coffee growing, especially in berryborer IPM. Most have many years of university andon the job training. Training exercises also includedthe opportunity to get to know participatory research

ROLE

Agricultural engineers,department of entomology,Cenicafé, in charge ofplanning and carrying outthe project.

Collaborators from the de-partment of entomology,who supported the wholeprocess, in the field and inthe office.

Voluntarily responded tothe invitation to work onthe Project. 113 farmers inthe 3 areas.

Invited to support thetraining events and to ac-company the Project, inthe areas where it wassited in their jurisdiction.

NAME

Luis Fdo. AristizábalHugo M. Salazar

Carlos Gonzalo MejíaMauricio JiménezGermán TabaresArturo GómezAndrés TrujilloJulio Cesar PatiñoCarlos Alberto Marín

Coffee growers of the De-partments of Caldas,Quindío and Risaralda(Colombia’s Central CoffeeBelt)

Extensionists from the Cof-fee Growers’ Committees ineach of the work areas.

in Central America: Honduras (The Pan-American Ag-ricultural School at Zamorano), and Nicaragua(CATIE’s IPM/NORAD Programme), among others.

3. SELECTING COMMUNITIES

The team took the following criteria into account whenchoosing areas to work:

� Villages where CBB is a problem.� Communities of smallholders (less than 5

hectares of coffee, each), living and working ontheir own land.

� Groups of growers interested in working to findalternative pest management.

The extension service helped locate nine villages in:

Caldas: Viterbo, Belalcázar, Riosucio.Quindío: Montenegro, Quimbaya, Buenavista.Risaralda: Balboa, Santa Rosa de Cabal, Santuario.

The team invited farmers to a presentation, where theydescribed the Project, its objectives, and to gaugefarmers’ interest in participating; 113 farmers in 9 vil-lages volunteered to collaborate with the Project.

4. PARTICIPATORY SURVEY

Describing the farmers

85% of the farmers linked to the Project are men.15% are women, heads of household, who managetheir own coffee farm.96% of the farmers are over 30 years of age.98% can read and write.78% of the households have four members or more.

Identifying farmers’ problems

41% said their main problem in producing coffee wasthe economic situation.30% said it was the CBB.12% said it was other plant health problems.9% thought other problems were more important (suchas law & order, environment) but an optimistic 8%said they didn’t have any problems.In the nine work groups (one per village), the team

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carried out participatory surveys with the farmers, es-tablishing their specific problems with CBB manage-ment, and seeking possible solutions:

The coffee growers met in work groups (they gavetheir groups up-beat names like: Los Pilosos (TheEnergetic Ones), Los Terribles (The Rascals), LosPatarroyos (possibly named after Prof. ManualPatarroyo, Colombian scientist and world expert onartificial vaccines for malaria), Los Amigos Biológicos(The Biological Friends), a play on the terms naturalenemies and biological control. They used drawingto express their problems and to suggest solutions(Figure 3).

Filling in the gaps in farmer knowledge21 . As theylearned what farmers knew and did not know, the teambegan to fill in the gaps in farmer knowledge (seeTable 9). The Cenicafé team worked with Federation

21 Much of the rest of Section 4 is adapted from Bentley (2000).

Table 9 Method and topics that Cenicafé taught smallholder farmers

Figure 3. Drawing by Los Terribles of Santa Rosa,Risaralda, made during the survey. It shows a CBB

and a farmer drinking coffee together. The CBB

says “I am happy when I am with you” and thefarmer replies “Let’s learn to be friends.” The group

wanted to show the need to learn to live with the

insect (instead of hoping they could make it disap-pear).

TOPIC

� Cultural control (e.g. Re-Re)

� Evaluating harvest quality

� Home made entomopathogenic fungus

� Applying fungus

� Low-water coffee processing ( Beneficio ecológico)

� Building seedbeds

� Renewing coffee

� Weed management, selecting the “noble” weeds, which conserve soil and do not com-pete with coffee

� Broca control in groves that have been stumped ( zoqueado)

� Biology and rearing parasitoids

� Producing fungus

� Rearing earthworms

� Insect zoo: importance of natural enemies

� Coffee varieties

� Aspects of integrated broca management

� Control in post-harvest (plastic cover on the tolva and on the pit; marquesina [a plastic& wood structure, shaped like a small Quonset hut, for trapping broca]).

� Making and using alcohol traps

� Sampling (EBEL)

� Techniques for releasing parasitoids (exclusion chambers)

� Evaluating trap trees

TEACHING METHOD

Demonstrations

Tours: groups of farmersvisited the main Cenicafécampus in Chinchiná andCenicafé’s experimentalsub-station at LaCatalina.

Talks

Participatory evaluations

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extensionists; relations were usually cordial, occasion-ally tense, especially when the Cenicafé staff begantraining farmers. The extensionists may have per-ceived the training events as a kind of territorial threat,as a suggestion that the extensionists had not donetheir job well. The Cenicafé team tried to explain thatthey were not trying to do the extension agent’s job,but that they were “nivelizando conocimientos”, cre-ating a level playing field. Since the Cenicafé teamhad learned what the farmers knew, the team wouldthen teach the farmers what the scientists knew, sothat they could work together as colleagues.

Starting research trials with farmers. From the com-munity diagnoses, the team learned that the commu-nities’ priority problems (with CBB) were:

1. Coffee groves are too old and not producing well.2. Even if one controls the CBB, one’s neighbour does

not (and CBB travel)3. The communities are disorganised4. Control measures are expensive (but farmers do

not know exactly how much they cost)5. Too many coffee berries are left in the grove

(recolecciones ineficientes)6. Labour shortage7. Generalised pesticide applicationsS

After March 1999, the farmers and scientists plannedresearch trials on CBB control techniques to solvethe above problems. Actually, some problems are morefeasible to study than others, and the research de-scribed below deals with problems 1,4, 5 and indi-rectly 3. The research with sampling touches on num-ber 7.

The techniques were overwhelmingly designed byscientists, especially Cenicafé researchers. This wasbecause the farmers expected a toolkit from Cenicafé,a set of solutions they could try out and apply. Butalso because the scientists were comfortable with theirrole as experts. This is not necessarily wrong, but theProject anthropologist was concerned that farmerscould have contributed more technical solutions.

Researchers, extensionists and farmers then prioritisedthe following list of research topics:� Costs and efficiency of cultural control

(Re-Re).� Study of berry borer populations on farms.

� Follow-up studies of the fungusBeauveria bassiana on farms

� Monitor berry borer populations usingalcohol-baited traps

� Effect of trapping on CBB populations� Community workshops to evaluate B.

bassiana� Study of the positional dynamics of the

berry borer� Releasing parasitic wasps Cephalonomia

stephanoderis & Prorops nasuta in thefield.

� Inventory of insects (besides berry borer)captured in the alcohol trap

� Evaluation of marquesinas for dryingcoffee with defects (pasillas) for CBBcontrol

� Control of CBB during processing� Evaluation of collection containers to

prevent escape of borers� Participatory evaluation of the EBEL

sampling format (devised by Cenicaféstatistician Esther Cecilia Montoya) withfarmers

� Changes in the adoption of IPM compo-nents

5. CONDUCTING THE RESEARCH CONTROLLING THE CBB DURING

PROCES SING.

Researchers and farmers evaluated 45 greased coversfor coffee collection bins, which represents 72% of

Figure 4 . Farmer’s drawing of the plastic cover

9999

Figure 5. Farmer evaluating the capture of CBB

on the greased lid of the cherry coffee bin

the farms that have bins for holding cherry coffee.The average area of the lids was 3 m2. Farmers con-ducted 903 evaluations, capturing (and counting) al-most a million borers (949,723) with an average of7,714 borers per square meter. The costs of makingeach cover, including materials and labour was anaverage of $ 10,269 (Colombian pesos, about $5 US).The group of farmers reconfirmed the importance ofthe greased covers during coffee harvesting. As onefarmer said: “The plastic covers are very useful fortrapping borers; they are very cheap and they preventthe CBB from returning to the coffee grove.” (“Lastapas plásticas son muy útiles para atrapar broca;son muy baratas y evitan el regreso de la broca alcafetal”).

Collection containers to prevent the escape of bor-

ers. The farmers adapted a plastic drum with a plasticlid, smeared with grease to trap borers during the har-vest (Figure 5).

This tool was invented by farmers, once they had ob-served the results of the greased covers (described inthe previous section). The purpose is to minimise theescape of borers during harvest. Researchers helpedfarmers design three treatments to compare differentkinds of linings for the greased drum:

� The drum with the greased lid captured 4,208adult borers in 2,306 kg. of cherry coffee(1.8 insects / kg of coffee)

� Using plastic bags, farmers captured 8,993borers in 2,760 kg of cherry coffee (3 in-sects / kg)

� And in the control container (a fibre bag,tied shut, but with a greased plastic bag in-side it—also a farmer invention) 5,839adults were captured in 2.620 kg. of coffee(2 borers / kg.)

These groves had low rates of CBB infestation, lessthan 3%. Some of the farmers’ comments:

“It is not enough to tie the bags shut in the grove; theCBB keeps getting out.” (“No basta con amarrar lasbolsas en el lote, la broca sigue saliendo”).

“The barrel and the plastic bag placed inside the tra-ditional container are economical and simple solu-tions to keep the CBB from escaping.” (La caneca yla bolsa plástica ubicada dentro del empaquetradicional son soluciones económicas y sencillas parano dejar escapar la broca).

“At first it was a bit complicated to find the little bor-ers, because there were so many and they are so tiny,besides taking data almost every day, while harvest-ing, is a lot of work, but since we wanted to show thatit worked, there was no other way.” (Al principio fueun poquito complicado contar las broquitas, porqueeran muchas y muy pequeñitas, además estar tomandodatos casi diario y en cosecha es más trabajo, perocomo queríamos demostrar que funcionaba, no habíaotro camino).

Managing CBB in groves that have been stumped.Farmers in Quindío evaluated the efficiency of traptrees and of applying the fungus Beauveria bassianato the soil in groves that had been stumped (Figure6).

Figure 6. Drum with plastic cover, smeared with grease,for holding and carrying harvested coffee from the field,to prevent the insect from escaping. Walker Cano

(Viterbo – Caldas, age 68), inventor of the idea

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Figure 7. Renewing a coffee grove by

stumping it

On the farms Villa Holguín and La Palmita, the rateof CBB in trap trees was 51 and 16% in the controlgroups, compared with 34.5 and 10% in the lots wherefungus had been applied. Neighbouring groves hadaverage rates of less than 2.3%.

B. bassiana was found on the trap trees in the groves,with at a rate of 1.5 to 35%. The farmers confirmedthe usefulness of trap trees as a physical barrier toprevent the spread of CBB to neighbouring groves.Some comments were:

“The trap trees are a good control measure for CBBin the groves renewed by stumping.” (Los árbolestrampa son una buena medida de control de broca enlos lotes renovados por zoca).“One sees a lot of CBB in the trap trees.” (“Es muchala broca que se ve en los árboles trampa”).

“Each time one chops down a coffee grove, one shouldleave some trap rows standing.” (“Cada vez que setumbe un lote del cafetal hay que dejar los surcostrampas”).

“The fungus helps to kill the CBB that comes out ofthe berries on the ground.” (“El hongo ayuda a matarla broca que sale de los frutos del suelo”).

The “EBEL”22 sampling plan for borers. 32 farm-ers participated, of whom 28% did more than five CBBevaluations in their groves, using the EBEL plan (Fig-ure 8). In Risaralda, some farmers did 14 evaluations.

Farmers conducted 151 evaluations; in 123 (81.4%)they included data on percentage of the coffee beanswhich were damaged. 71% of the cases were belowthe upper limit for coffee bean infestation establishedby the EBEL plan. Farmers found the plan time-con-suming and unhelpful, commenting:

“(The plan) requires technified23 groves, which makeit easier to move about and apply the plan.” (“Serequiere tener lotes tecnificados, lo cual facilita elrecorrido y aplicación del plan”).

“One does not need to count to know how much ofone’s coffee is sold with CBB (damage).” (“No senecesita hacer cuentas para saber con cuanta brocavendemos el café”).

“The CBB hot spots are easily identified (withoutsampling).” (“Se identifican fácilmente los focos debroca”).

“The table has too many columns; this makes you getconfused.” (“La tabla tiene muchas columnas, estohace que uno se confunda”).

“Doing the evaluation wastes a lot of time and is tir-ing.” (“Se gasta mucho tiempo y se cansa muchohaciendo la evaluación”).

This is an example of how participatory research cansave time and money. The work on which the EBELplan was based began more than five years previouslyand involved very detailed sampling of a plot, labori-ous entry of thousands of lines of data and months ofcomputer analysis and report writing.

22 EBEL stands for the initials of the Cenicafé scientists who invented the method, a clear example that researchers identify with their inventionspersonally. This is one reason researchers develop an irrational attachment to their technologies, and become frustrated when farmers do notadopt them, and may place unreasonable demands on extensionists to force adoption.

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Figure 8. Diagram drawn by farmers to present

their results of their test of the sampling plan

A preliminary exercise with farmers and extensionists,using a range of sample schemes, based on a simpleand quickly-gathered data set, would have revealedthe practical problems of sampling. This in turn mighthave occasioned a rethink which could have producedsomething more practical.

Biology of Phymastichus coffea, parasitoid of the

coffee berry borer. Researchers in various countriesare studying African parasitoids for the berry borer.The study presented here was designed to evaluatethe lifecycle and levels of parasitism of Phymastichuscoffea (Hymenoptera: Eulophidae) on three farms atdifferent altitudes. Researchers conducted the evalu-ation on borers which were released and parasitizedinside of insect sleeves. Farmers and extensionists col-laborated in planning, conducting and discussing theresults in each of the three areas (Figure 9).

The life cycles were as follows:

At 19.3oC (elevation 1800 metres in Santa Rosa deCabal, Risaralda): 60.0 days (egg: 11.9; larva: 16.6,pupa: 31.5)

At 21.5oC (elevation 1400 metres in Quimbaya,Quindío): 37.3 days (egg: 5.5, larva: 17.7, pupa: 19.6)

At 22.8oC (elevation 1200 metres in Viterbo, Caldas):34.5 days (egg: 6.8, larva: 10.8, pupa: 16.9).

The average rates of parasitism were 96% for SantaRosa, 67% for Quimbaya and 62% for Viterbo.Theresults show that P. coffea can complete its lifecyclein coffee between 1200 and 1800 metres above sealevel. Mass release of P. coffea would probably re-duce parasitism as much as by 50% when not done ininsect sleeves. Even so, the percentages are greaterthan those achieved by other parasitoids released pre-viously. P. coffea could be a viable control option.

Integrated management of the coffee berry borer,

with emphasis on parasitoids . Farmers in Quindíoshowed interest in using the parasitoids Cephalonomiastephanoderis and Prorops nasuta (Hymenoptera:Bethylidae) on their farms. Researchers and farmersselected 36 groves in different agroecological areas,on 30 farms in Buenavista, Montenegro andQuimbaya. Borer control was based on frequent har-vest of coffee and release of parasitoids. For two years,they studied the infestation rate of borers in the grovesand in parchment coffee. The results were analysedas case studies, using descriptive statistics.

Borer infestation rates were low (Table 10).

83% of the farmers sold their coffee at rates of lessthan 2% CBB damage. All (100%) of the farmers saidthey observed parasitoids in their groves. The farm-ers concluded that frequent harvesting of coffee andreleases of wasps could be used to control CBB.

Discussion. The Project anthropologist finds this aconfusing study. It has a veneer of science, but it hasno control group, and mixes two treatments at once.Be careful not to confuse farmers with spurious data.

Biological and economic analysis of cultural con-

trol of the coffee berry borer. The purpose of thisstudy was to evaluate the efficiency of cultural con-trol of the CBB, and determine the quality of dryparchment coffee obtained during one year on threefarms in Caldas, Quindío and Risaralda. During theyear 2000, collaborating farmers wrote down the num-ber of kilos of coffee harvested, and the costs of har-vest, processing and of hauling the coffee to sale. They

23That is, plots on which farmers have applied all the cutting-edge technology, as recommended by researchers.

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Figure 9. Drawing of the experiment, by one of the children. The researchers thought this drawing “emphasised

the participation of the family”. Actually, if you look carefully, each of the 4 human figures is labelled with

a person’s name and “Cenicafé”. The child titled the drawing “Experiment by Cenicafé, CBB and wasps”.

The family seems not to have felt ownership of the experiment, although they were probably proud to be

associated with researchers. Note the large amount of space devoted to the car and the road.

also evaluated the level of infestation of the CBB inthe field, the effectiveness of harvester labour and thelevel of infestation of the CBB in dry parchment cof-fee.

The results showed that in the three groves studied,the harvest labour was efficient, and that frequent,well-done harvests control CBB in the field, obtain-ing Federation grade parchment coffee. On all threefarms, the cost of cultural control (Re-Re) was re-couped in 98% of the cases by the coffee harvestedduring 2000. It was profitable for the growers to har-vest ripe coffee every 15 to 22 days.

Farmer-experimenter workshop to evaluate

Beauveria bassiana for the control of CBB.

Beauveria bassiana is the natural enemy which causesthe most mortality in CBB populations. Some farm-ers have produced it, and seen it in the field as a whitedot on adult borers. The big question is, how many

borers does Bb kill? Humidity favours the fungus,which may be one reason that farmers underestimateits role in CBB control. Project staff held a demon-stration workshop with farmers from three villagesRiosucio (Caldas), Balboa and Santa Rosa de Cabal(Risaralda) to evaluate the natural effect of the fun-gus in the field (i.e. the fungus naturally present inthe field with no additional spraying). The team col-lected fruit with borers, at random, drew the borer’sposition and dissected the berries. Live and dead bor-ers were isolated and placed in vials in a humiditychamber for 15 days. The farmers kept written recordsof the: number of holes, live and dead borers (withand without the fungus), absent borers and the posi-tion of the insect in the berry. The farmers detectedthe presence of B. bassiana on their farms after ob-serving it during the evaluations. Live and dead bor-ers without signs of fungus often developed it afterbeing placed in the humidity chamber.

MUNICIPALITY

BuenavistaMontenegroQuimbaya

BORER INFESTA-

TION IN GROVE

2.0 ± 1.8 %3.5 ± 1.9 %1.9 ± 1.7 %

INFESTATION IN

PARCHMENT COFFEE

1.7 ± 0.5 %2.5 ± 1.3 %

1.3 ± 1 %

ESTABLISHMENT RATE

OF WASPS

28 %90 %82 %

Table 10 Borer infestation in three communities

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Discussion. The case of Bb is interesting because pre-vious extension campaigns to transfer the use of thistechnology, failed. Additionally, the results of manyfield tests, in a previous project (Baker 1999) and onein this project, failed to show that the method causessufficient mortality to be useful to farmers. But thefarmers still wanted to try it. And even after they hadtried it, they still made favourable comments about it,even though it was not effective. Were they pickingup on a research agenda and giving the response theyfelt was required? Or did they genuinely think thatthe method still has some use? The results of the sur-veys (see below) suggest that the farmers did not knowabout Bb. But should the researchers simply have toldthem that this method needed further improvementbefore more field-trials? An interesting study mighthave been to determine what farmers use as criteriafor a successful pest control method and then subse-quently to get them to rank each method tried.

Study of borer population with traps. Cenicafé hasstudied alcohol traps to capture borer for some time.The participatory study was carried out in Caldas,Quindío and Risaralda. The objectives were:

1- Observe the degree of adoption of the technol-ogy,

2- Document the periods of most emergence of theborer

3- Study the borer population to help make deci-sions about IPM.

39 farmers participated in Riosucio and Viterbo(Caldas), Buenavista, Montenegro and Quimbaya(Quindío) and Balboa (Risaralda). They made thetraps using material found on farm, and adapted thedesign.

The bait was medicinal alcohol, 90°, mixed withinstant coffee. They placed 5 traps in each grove.Farmers and researchers made 551 counts of borer,an average of 14 per collaborating farmer.

Number of borers captured weekly: between 0 and300 per trap,Most captures: April 2000 (11.5(3.5).Number of evaluations: 369, an average of nine perfarmer.Rate of infestations, between 0.2 and 15%,(2.9(2.2%).

No correlation was detected between number ofborers captured, rate of infestation and rainfall.

Cost of materials: $1,185 (about 60 US cents) pertrap and $625 (US 30 cents) for labour.

Cost of weekly evaluations: $250 (12 US cents) pertrap.Only two farmers (5.1%) continued the evaluationsall year.

Discussion. The traps did allow researchers to con-duct basic research on time of year when the mostCBB emerge, although the experience apparentlybored the farmers because nearly all gave up beforethe end of the study. The anthropologist wonders ifthe fact that each farmer designed his own traps dam-aged the replicability of the experiment.

Other studies, included a researcher-led study on onefarm to determine the effect of trapping on CBB popu-lation, apparently there is little effect. There was alsoan esoteric study of the degree of penetration of bor-ers in coffee berries in three municipalities.

Adoption. Researchers conducted another survey inthe first half of 2000, to learn about technical changein the first 18 months of the Project.

� Re–Re was the item most adopted, 95%of farmers did it in 1998 and 99% in 2000,and they were doing it more thoroughly

� Insecticides. In 1998, 80% of the farmersmade blanket applications, but by the year2000, 58% of the farmers claimed not to useinsecticides and the other 42% applied onlyon hot spots, and after evaluating theinfestation in the grove

� Knowledge of biological control (fungusand parasitoids) went from 8% to 81%

� Control in post harvest and in processingwas adopted by 82% of the group members,up from 7% in 1998

� Records, 47 % of the farmers keptrecords at first, vs. 72% by 2000

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� Field evaluations, 15% did fieldevaluations in 1998, and 80% by 2000

Participating in research is linked with adoption. Farm-ers learn by doing, learn the reasons behind the tech-nologies, increase their self-esteem, and generate newideas of their own (Figure 10).

When researchers asked farmers about the problems,the story had changed. By the year 2000:

� For 34% of the farmers, their main problem incoffee was the economic situation

� Only 2% said it was coffee berry borer� 10% said other plant health problems� 25% said other things (like law & order, envi-

ronment)� And 29% said they did not have any problems

with coffee

Compared with their answers in 1998, the farmersshowed a lot more confidence in dealing with CBB(Figure 11)24 .

6. VILLAGE EXCHANGES

The farmers of Riosucio visited the municipalities ofViterbo and Belalcázar; people from Balboa visited

24Farmers are experts in telling survey-takers what they want to hear. While these numbers may be of some value, what is more important is thatthe researchers sense that the farmers are more optimistic and self-assured after their experience with the Project.

Montenegro and Quimbaya; those from Santa Rosade Cabal and Santuario went to Balboa; growers fromthe village of Mesa Baja in Quimbaya visited the vil-lage of Morelia Alta, also in Quimbaya. Through theexchanges, farmers shared experiences and got toknow the work of other collaborating farmers (Figure11).

7. FARMER WORKSHOPS

The Project sponsored three workshops for farmer-experimenters (one per year), on the campuses ofCenicafé and the Manuel Mejía Foundation inChinchiná, Caldas (Figure 12). A total of 72 farmersattended the three events. They were all chosen bytheir communities, in meetings, to represent theirneighbours at the workshop. Nine extensionists, fouragronomists from the Foundation and eight research-ers also attended.

The attending farmers:

� Gave a general presentation on each villageand the field trials they conducted.

� Reviewed the different IPM techniques.� Made commitments as farmer-experiment-

ers.� Evaluated the participatory research.

Figure 10. Use of IPM technologies by farmers who collaborated

with the Project. Change from 1998 to 2000.

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Figure 11. Change in the problems collaborating farmers reported in coffee

growing, before and during the project.

Figure 12. Closing of the First Farmer-Experimenter Work-

shop held at Cenicafé, at the La Catalina experimental sta-

tion, 3 November 1999.

�

The farmers who attended organised themselves intovillage committees for preparing their visual aids, theresults of their research, and conclusions, which weresubmitted to a group discussion of achievements andweaknesses.

8. THE WAY FORWARD

The project staff have developed an original modelfor farmer-scientist collaboration. In summary, theirmethod consists of:

1. First encounters: for the first four months they vis-ited the areas with local extension agents, getting toknow the areas, and gaining farmers’ trust.

2. Individual visits with farmers, to learn what theyknow and the gaps in their knowledge. They conductedindividual diagnoses of 113 farmers, to learn the farm-ers’ concerns and knowledge. The method: the re-searchers had a written format to fill in, but did notadminister it like a questionnaire.

They visited the farm household, walked with themover their land, chatted informally, and filled in theform later. They led Participatory Rural Appraisal di-

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agnostic sessions in each of 9 communities, to iden-tify problems, solutions and to brainstorm CBB con-trol ideas to research. These formal, quantitative meth-ods allowed them to assess farmer knowledge.

3. Training farmers, involving extension agents to fill-ing in the gaps in farmers’ knowledge thus creating alevel playing field for collaboration. Evaluation oftraining is also carried out.

4. Establishing and carrying out tests on things thatare likely to work. From the above steps things areagreed upon for further action. Some are farmer in-ventions, but most are scientist inventions. Farmersmodify some of the techniques during the tests.

5. Farmers present results of the research in a farmer-scientist workshop. Three well-attended and compre-hensive events were held.

6. Evaluate the cost-effectiveness of the process. Afull economic analysis with an agricultural economist,e.g for CBB cultural control.

7. (Future step) train extension agents, using practi-cal demonstrations (hammer and nails, not talk andchalk) of the most promising technologies. This mightinclude the entry-level “most-likely-to-enthuse-farm-ers” technique (perhaps the sticky covers because theyare cheap, easy to install and give quick visual re-sults) and a series of subsequent steps leading up tomore difficult concepts. There would also be some“don’t-even-think-about-it” advice and ways to moni-tor achievement and encourage farmers (the regionalevents, prizes, etc.). Even this would be a pilot exten-

sion project, preferably with researchers monitoringit, followed by a full-scale roll out at a regional levelof the validated techniques.

Step 7 is the most crucial because it is the link to afollowing project. Too many projects finish and noone takes them up because they do not have owner-ship of the original. This may well happen in thepresent case because the funding is finished andproject staff will be laid off or reassigned.

Conclusions.The above project is not a panacea butis a useful attempt to assay new ideas in frequentlytesting circumstances. A general feeling we have isthat top-down extension is nearing the end of its use-fulness. It is not uncommon to find researchers whofeel that extensionists are not making a good enoughattempt to pass on their innovations, and likewise weencounter extensionists who accuse researchers ofbeing arrogant and out of touch with farmers. Coffeeproducing countries simply cannot afford this stateof affairs to continue.

REFERENCES CITED

Aristizábal A., Luis Fernando & Hugo Mauricio Salazar E.2001 Investigación Participativa en el Manejo Integradode la Broca del Café, con Pequeños Caficultores.Report. Chinchiná, Colombia: Cenicafé.

Baker PS, 1999. The Coffee Berry Borer in Colombia. Finalreport of the DFID-Cenicafé-CABI Bioscience IPM forcoffee project. ISBN 958-96554-1-6.

Bentley, Jeffery W. 2000 The CFC Coffee Berry Borer IPMProject: Colombia. Report submitted to CABI, Egham,UK. 21 pp.

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1. INFLUENCES

The Ecuadorian project is not housed in a nationalcoffee institute, but in the headquarters of a NationalCoffee Exporters’ Association (Anecafé); this givesthe Ecuadorians a certain pragmatic perspective. Forexample, at the Project meeting in Colombia in May1999, the Ecuadorians were the most willing to con-sider changing their research programme. WhenBentley visited them in May 2000, Project leader25

Alberto Larco frankly admitted that at the beginningof the Project they had confused participatory researchwith extension. Most of the others had also made thesame mistake, but were not as ready to make a clearbreak with it. The Ecuadorian team rapidly got en-thusiastic about involving farmers in research.

2. DOING PARTICIPATORY RESEARCH WITHOUT REALISING IT

One encouraging development was when Bentley andLarco realised that Project extensionist Evaristo Callehad already conducted a practical field trial with acommunity. Although it had not been appreciated asparticipatory research - it was.

Trial design. Mr Calle designed the trial to judge thevalue of four styles of planting coffee seedlings.

1) Direct planting in a raised bed.2) Planted directly into a black plastic bag, filled withsoil.

3) Planted first in a seedbed, and transplanted to araised bed.4) Planted first in a seedbed, and transplanted to ablack plastic bag, filled with soil.

Data on plant growth suggested that the first treat-ment, which happened to be the farmers’ traditionalpractice, was the most successful. The research wascarried out from June to December 1999, with fourcollaborating farmers in the community of 10 deAgosto, in the canton 24 de Mayo, Manabí. Calleshared the results in a community meeting. While notearth-shattering research, farmers did participate, andit validated a traditional practice (Figure 13).

3. RESEARCH PLANNED FOR THE YEAR 2000

With Anecafé researchers, Alberto Larco and Will-iam Chilán, plus Project extensionists José Molina,Jorge Delgado, Evaristo Calle, Carlos García and theProject anthropologist (Bentley) we planned five stud-ies in May 2000. The topics were:

� Varieties of coffee with supposed resistanceto the coffee berry borer

� Alcohol-baited traps for capturing coffeeberry borer

� The use of organic fertilisers: “Biol” andcompost

� The relationship between harvest systemsand coffee berries left in groves

25 The head of Project for Ecuador is Pablo Delgado, who is the managing executive of Anecafé. While Mr Delgado provides active leadership to theproject, most daily supervision is handled by Alberto Larco, an agricultural engineer.

Figure 13. Average heights of coffee plantlets with their

statistical significance for the four experimental treatments

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�A case study of coffee processing machinery.The team stayed with these topics, although each oneevolved in its own way.

Varieties of coffee and coffee berry borer

This topic evolved quite a bit. Originally it was de-signed to test an observation farmers had made to re-searchers that the variety yellow caturra was resistantto berry borer. However, communication with re-searchers at Cenicafé and Peter Baker convinced usthat the Colombians had already studied the topic ex-haustively and that there was no varietal resistance toberry borer. But then, farmers in Pedro Pablo Gómez,Jipijapa, Manabí told the extensionist José Molina thatthey knew that (red) caturra yielded more than typica,but they were afraid to plant it, because they thoughtit was susceptible to CBB.

Ecuadorian researchers realised that this was an im-plicit demand for research, and helped the commu-nity set it up. They worked with a committee of farm-ers representing two organised groups (four farmersin the group Bajo Grande, and one in Santa Cruz).

Figure 14. Percentage of CBB infestation on the tree- first evaluation

Figure 15. Percentage of CBB infestation on the tree- second evaluation

Source: Molina & Chilán 2001

The selected farmers each had some caturra trees andsome typica trees. The agronomists went with thefarmers to the groves, where they collected the data.They showed that caturra is higher yielding, but is nomore susceptible to CBB than typica is.

In June 2001, Bentley went with Ecuadorian research-ers and extensionists to Pedro Pablo Gómez. It wasone the most enthusiastic meetings he ever saw. Thecommunity was waiting for them in the small, brickhouse of the group leader. She opened the meetingand called on the extensionist to give a talk. JoséMolina spoke on one of the parasitic wasps. Then thecommunity members explained the results of the ex-periment, how they had gone on the rounds from farmto farm, collecting the data from 10 caturra plants and10 typica plants on each farm. And they saw that theincidence of CBB was about the same. “Sometimesthere were seven in one and nothing in the other. Therewere only three little beans damaged in all three clus-ters that we evaluated at the end. And those three beanswere typica ”26. The farmers clearly caught the ideathat caturra yields more and is not especially suscep-

26 A veces era siete en uno, nada en el otro. Solo habían tres pepitas dañadas en todas las 30 gavillas que evaluamos al final. Y los tres granos erantypica.

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tible to berry borer. In other words, the local peopleowned the data.

This may not be groundbreaking research agronomi-cally, but it responds to an implicit community de-mand. It’s probably an extension experience, becausethe farmers learned much more than the researchers,who already knew that Caturra was not more suscep-tible to CBB. But the experience can easily be used tobenefit many others, by bringing farmers from othercommunities with the same concern, to visit P.P.Gómez, where local farmers will be able to explainthe research, in the local vernacular, in no uncertainterms. An extension agency could even make a radioshow, interviewing farmers from P.P. Gómez, and play-ing their remarks on the air, for the benefit of otherswho may also be asking themselves if they shouldplant caturra or typica.

Alcohol-baited traps for coffee berry borer. Thegoal of this study was to design a better CBB trap, soresearchers could monitor CBB populations. WilliamChilán had already started testing three trap designsin farmers’ fields by early 2000. As the farmers wentwith Chilán, they learned which traps caught the mostCBB. In May 2000, Bentley cautioned that this mightbe counter-productive, if farmers began to make ex-tra efforts to control CBB around the traps with themost captured insects, it might skew the data. Bentley(2000) suggested that there were several ways to ap-proach the study of traps, as a:

� Conventional, on-farm agronomic trial(participatory level 1)

� Qualitative experience, with farmers suggest-ing some changes to make the traps cheaperor easier to make. For example, farmers werealready suggesting using bamboo (locallyabundant) instead of purchased wire, as theframe for the trap (participatory level 3/4)

� Study of local knowledge, to see if the trapscould reconfirm what farmers were saying,that they already knew where the hot spotswere in their groves (participatory level 4)

Ecuadorian researchers organised the study as a setof on-farm trials, with collaborating farmers, and acommunity evaluation. In June 2000, researchers took

three trap designs to the communities of Entrada deGuarumo and Los Angeles, both in 24 de Mayo,Manabí. Chilán made the traps with local people. Thethree models of traps were made from:

1) A string of five plastic drinking cups2) A string of five funnels, each funnel cut from thetop of a large, plastic soft-drink bottle, and painted asilver colour3) A large plastic soft-drink bottle, hung upside-down,with windows cut into it

Each model has two small, disposable plastic platesas a roof, a plastic film can filled with alcohol (a mixof ethanol and methanol) as bait for the CBB, and

The trap made from a soft-drink bottle

The funnel style trap

Photo courtesy of Anecafé

Photo courtesy of Anecafé

111111

Johnny Sánchez hangs a trap made

from 5 disposable drinking cups.Photo courtesy of Anecaféé

another film can filled with water, to capture the bor-ers.

Chilán and collaborating farmers replenished the al-cohol and collected data every 10 days, which Chilán

Figure 16. Capture of adult CBB by 3 kinds of traps in La Entrada de

Guarumo, Portoviejo

Figure 17. Capture of adult CBB by 3 kinds of traps in Los Angeles,

24 de Mayo

analysed. Each community had a replicate of the 3treatments, with 6 of each style of trap. The dataclearly showed that the trap made from cups caughtmore borers. However, it also showed that far moreborers were caught just after harvest, which suggestedthat if researchers were working on traps as a controldevice, they might concentrate on that time of year.

On 21 June 2001, Bentley attended a communityevaluation, in Entrada de Guarumo, attended byProject researchers and extensionists, about 25 farm-ers and five extensionists from a collaborating NGO(OFIS). Chatting with farmers before the meeting, andagain during the meeting, it became clear to us thatthe community members thought that the traps werecontrolling the CBB, not just on the participatingfarms, but in the whole community. This was a fan-tastic misperception.

Farmers said that the year before they had had 40%incidence of CBB, and that now there was much less.Alberto Larco led a long and sometimes noisy dis-

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cussion, with community members providing muchof the data. The logic of it went something like this:

� The traps killed a total of about 32,000borers.

� A coffee tree can have about 900 berries.� 2,500 plants per hectare would have

2,250,000 berries.� 40% of which is 900,000.� So if the traps killed 32,000, there are still

868,000 borers unaccounted for.

Larco then asked how many traps it would take to kill900,000 borers.

We calculated 500 traps (though through the law ofdiminishing returns, it is most unlikely that this num-ber would kill all the borers). The cost in labour ofvisiting these 500 would be $288 and the cost of ma-terials would be $413 , without taking into accountthe cost of getting the materials or of building the traps.It was courageous of Larco to take the time to clearup such a misunderstanding, especially in front of thesurprised extensionists from the NGO. The farmersgot very discouraged. It was clear that the local peoplehad not realised that they were participating in re-search. One outspoken farmer, Johnny Sánchez, saidthat the researchers should bring things that wereready, and not things like this that they did not knowwould work or not.

Discussion. The experience was a shock at the time,but it shows how important it is to be clear with acommunity about the goals of research. We also seeby the final meeting that the farmers had misunder-stood what was going on, and formed some seriouslywrong conclusions, that the traps were for control-ling the CBB. The farmers’ implicit demand was fora trap to control CBB, not just to monitor it (whichwas the researchers’ idea). Perhaps Anecafé’s busi-ness orientation led them to be so brutally honest withfarmers’ regarding the cost ineffectiveness of the traps.Certain other programmes tend to encourage farmersto adopt an innovation without bothering to count thecosts.

Still, everyone learned something. The researcherslearned when to trap and which model works best.The farmers learned how to make the traps, and how

to count CBB. They got an idea of how many mil-lions of borers they probably have in their groves. Inother words, for all its flaws, it was participatory re-search, because farmers and researchers learned newinformation (see Box 3, Part I).

Compost. Project extensionist Evaristo Calle andother team members have been interested in organicfertiliser since at least 1999, specifically, in two typesof organic fertiliser, both of which they learned fromNicaraguan NGOs.

Biol: a slurry of water, cow manure, cane syrup, milkand lime, fermented in a plastic barrel.Bokashi: a Japanese-style potting soil, made of ma-nure and half a dozen other ingredients, mixed 25times and fermented indoors.

Bentley’s first impression of these tedious technolo-gies is that they were conceptually, as well as liter-ally, bullshit. They use too much labour, too muchpurchased material and generate little organicfertiliser. The nutrient value of organic fertiliser islow, and to be very useful, a farmer or gardener mustapply a lot of it.

But the Ecuadorians countered that Ecuadorian cof-fee farmers also usually had cattle, so the cost of themanure would be lower than in some other countries.They also observed that in previous experiences, theyhad noticed that Biol helped to control disease oncoffee plants. That made Biol worth trying.

From July 2000 and for the next year, the extensionistsEvaristo Calle, Jorge Delgado and Pedro Tulio Gómeztried Biol and compost in three villages. They onlyreport on results of Biol, not on results of compost(Delgado et al. 2001). Their trials showed that mal dehilacha (Koleroga) was significantly lower on coffeethat had been sprayed with Biol.

This was basically level 1 participatory research, on-farm. It remains to be seen if it is cost-effective or iffarmers will adopt it, but the initial results are inter-esting and suggest that Biol can be adapted as a fun-gicide, which could make it much more profitable thanif it is used as a fertiliser.

Harvest systems. In May 2000, Ecuadorian research-ers told Bentley they wanted to study the effects of

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Figure 18. Incidence of mal de hilachas (Pellicularia koleroga) in

Caña Brava, 24 de Mayo

Figure 19. Incidence of mal de hilachas (Pellicularia koleroga) in

Los Colorados, Portoviejo

Figure 20. Incidence of mal de hilachas (Pellicularia koleroga) in La

Ladera, 24 de Mayo

different, traditional harvest systems on the amountof coffee berries spilled on the ground (and provid-ing CBB habitat)(Table 11). Some pickers harvestberries into baskets. Others spread a large sheet onthe ground (made from 2 fertiliser sacks sewn to-gether, somewhat like the picking mat in India). We

agreed that it was an important topic and agreed to doit by visiting different places, measuring the size ofthe grove, the number of workers, documenting theharvest technology (e.g. basket, mat etc.) and samplingthe number of berries left on the tree or dropped to theground.

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PLACE

10 de Agosto

Los Angeles

La Cruz

HARVEST SYSTEM

Men, women and youths picking ripe berries into a bucket.

Women and youths, stripping berries off the branches onto a canvas sheet.

Hand picking onto a canvas sheet.

Table 11 Researchers studied three harvest systems in three different communities, with no repetitions

However, this was more or less conventional, socialor even ergonomic research. It was almost physicalanthropology, with little room for farmer participa-tion. The Ecuadorian researchers, who had done suchother good studies, never got comfortable with themethod for this one.

Researchers conducted the study by measuring thetime it took pickers to harvest 20 plants. They alsocounted the number of berries on the tree and on theground, both before and after harvesting. They alsocounted how many volunteer coffee plants hadsprouted below each tree.

Just by doing this small study the researchers realisedthat harvesting is much more difficult on hills, wherethe pickers had to tie the sheet to the ground withstakes, so that the stake would be higher on the lowend, to keep the berries from rolling off. This tookmore time. The researchers also began chatting withfarmers about why they stripped the berries all at once,instead of hand-picking the ripe ones. The farmerssaid they realised that they were damaging next year’sharvest, but that when coffee prices are low, they don’tbother to pick properly.

The pickers were very fast, taking only two to fourminutes per plant, if they stripped the fruit. Pickingripe berries took five to seven minutes. Since strip-ping is done once, and careful picking twice or moretimes, stripping is much faster, but it damages the plantand the quality of the harvested coffee is much lower.Farmers usually pay pickers by the day, not by theamount picked, if they are more concerned about qual-ity. After the harvest, the owners pick the coffee fromthe ground, so there is little fallen fruit.

Discussion. In spite of certain methodological prob-lems, something was salvaged from the research. Ifnothing else, we have a better idea of how people

pick coffee in Ecuador and that at least some peopleare careful not to leave a lot of berries on the ground.But the Ecuadorian researchers were uncomfortablewith the study, and eventually discarded it from theirfinal report.

Case study: beneficio húmedo. This study was to befrankly qualitative, and the Ecuadorians had a sig-nificant experience with it, but failed to write up theresults.

On 22 June 2001, Larco and Bentley visited a groupof farmers in Las Juntas, Moraspungo, department ofCotopaxi. This was supposed to be a case study ofbeneficio ecológico (low water coffee pulping, usingstate-of-the-art Colombian machinery). The notionwas that farmers take a low price, because they sellcoffee in cherry, because they often do not haveenough water to wash coffee. The Colombian pulperthat uses less than two litres of water per kg of coffeeseemed like a promising solution. Anecafé had loanedthis group a machine. We found them on a large ce-ment patio, where one member of the group buys cof-fee. Eight or ten men gathered around while theextensionist, P. T. Gómez adjusted the machine. Wetalked with the farmers and with Wenceslao Beltránof Anecafé.

The people in Moraspungo sell their coffee in cherry.

They harvest a mix of ripe and unripe berries, whichlowers labour costs. The price of coffee is low, $4-5per hundredweight of cherry. Although they are onlypaid $4 a day (plus meals), a labourer cannot harvesta hundred pounds of coffee a day, so many people arenot hiring harvesters. Many men who have coffee oftheir own are working as labourers instead of harvest-ing their coffee. People remember fondly when cof-fee was worth $40 to $50 per hundredweight, as re-cently as 1996.

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The coffee flowered many times that year, and therewas a great mix of ripe and unripe coffee on the plants,which made it just that much more difficult to harvestonly ripe berries. People were just stripping thebranches, instead of bothering to pick only ripe ber-ries.

The Colombian beneficio ecológico machine was de-signed to be fed only ripe coffee. It choked up severaltimes on the hard, unripe berries. Wenceslao had tobring a bag of ripe coffee, that he picked himself, justso people could watch the demonstration of the ma-chine. The extensionist got the machine running beau-tifully on the hand-picked ripe coffee, but the farmerswho gathered around to watch it lost interest whenthey saw that it did not handle unripe berries. Theyhelped us load the (surprisingly heavy) machine ontothe pick-up truck, and we took it to Los Colorados,but by this time the extensionists had a harder timeconveying much enthusiasm about the machine to theirfarmer friends. It is likely, if prices had been at 1996levels, that farmers would have been willing to selec-tively harvest ripe berries to feed the machine. In thiscase it could have earned them even more than byquickly stripping the pulp and allowing them to pro-duce high quality parchment. As such this is an inter-esting case of how low prices can lead to a downwardspiral in earnings from which it is difficult to recover.

Lesson learned. Beneficio ecológico demands a har-vest quality that many Ecuadorian communities can-not match. It would be a difficult technology to adoptin Ecuador, unless it was re-tooled, though this wouldbe a major undertaking. Perhaps the staff at Anecaféfound this conclusion too qualitative, or too negative.At any rate, they opted not to write about their expe-rience with beneficio ecológico.

Discussion. The researchers were more comfortablewith, and did a better job with research designs thatresembled an agronomic trial on a research station.This is no doubt one reason agronomists are accept-ing the CIAL method with little trouble. But with top-ics that demand a different design, e.g. a one-off er-gonomic study of harvesting, or a qualitative, casestudy of a new tool, agronomists are reluctant to writetheir results. The beneficio ecológico study could be

done in the Back-&-Forth format, if the team has amechanical engineer with the time to take the ma-chine apart and put it back together again.

People who are going to write an account of an expe-rience in a community would do well to take a coursein journalism, and write the account like a plain,simple newspaper story.

In a country like Ecuador with weak scientific insti-tutions, it was probably expecting too much of thisProject’s staff to develop the methods and the topicsof participatory research, besides carrying out theirother duties. They did well, given the circumstances,but if we are to develop FPR as a proper discipline,we need to think hard about where and how to firstapply it and the minimum conditions required for itto flourish.

REFERENCES CITED

Bentley, Jeffery W. 2000 The CFC Coffee Berry Borer IPMProject: Ecuador. Report submitted to CABI, Egham, UK.34 pp.

Calle S., Evaristo & William Chilán V. 2001 Comparación de dossistemas de crianza de plántulas de café arábigo (Coffeaarábica L.), en el Cantón 24 de Mayo, Manabí. Manta:CFC- CABI-OIC-ANECAFÉ, Proyecto Manejo Integradode la Broca del Café. 8 pp.

Chilán V., William, Jorge Elicio Delgado, Evaristo Calle S. 2001El uso del trampas en la captura de adultos de broca delcafé en las comunidades de Entrada de Guarumo y LosAngeles, Manabí. Manta: CFC- CABI-OIC-ANECAFÉ,Proyecto Manejo Integrado de la Broca del Café. 12 pp.

Delgado, Jorge Elicio, Evaristo Calle S., Pedro Tulio Gómez,William Chilán V. 2001 El biol y compost; alternativasorgánicas y su incidencia en las enfermedades fungosasdel cultivo de café con caficultores de Manabí, Ecuador:CFC- CABI-OIC-ANECAFÉ, Proyecto Manejo Integradode la Broca del Café. Anecafé. 5 pp.

Molina M., José & William Chilán V. 2001 Relación del ataquede broca del café Hypothenemus hampei Ferrari, en lasvariedades arábigas Typica y Caturra en Pedro PabloGómez, Jipijapa, Ecuador. Manta: CFC- CABI-OIC-ANECAFÉ, Proyecto Manejo Integrado de la Broca delCafé. 12pp.

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1. INFLUENCES

Like most of our other Latin American Projects, thestaff of the Honduran Project had a long associationwith other related projects. For example, in about1991, Raúl Muñoz, Project leader for Honduras, hadpreviously worked on a project that taught farmers torear wasp parasitoids, in collaboration with Dr JuanBarrera and other colleagues from our MexicanProject. Muñoz and others at IHCAFE (the Hondu-ran Coffee Institute) had worked on extension withfarmers since the mid 1980s.

Another major influence was the CATIE/NORADprogram in Nicaragua. CATIE is an international ag-ricultural research and education centre, based inCosta Rica, but with offices in the other Central Ameri-can countries. CATIE has a long experience with cof-fee and with IPM. CATIE emphasised teaching farm-ers to make a lengthy, formal count of insect pestsand diseases. The idea was that farmers would learnto fill out the sampling forms, and use the informa-tion to make agroecologically sophisticated decisionsabout pest management.

The CATIE training materials for farmers also in-cluded solid lessons on the biology and ecology of avery large range of topics, weeds, diseases, nematodes,the coffee borer and others (Muñoz & Paz 2000).IHCAFE researchers hoped that farmers who attendedtraining events would be more likely to adopt newtechnology. These extension experiences were calledparticipatory research, although the emphasis wasmore on encouraging farmers to adopt researcher in-novations, with little emphasis on inventing technol-ogy (Muñoz & Paz 2000, especially pages 2-3).

2. STARTING

The participatory research was set up in response tothese early influences. As early as 1998, at the verystart of this project, Raúl Muñoz and colleagues atIHCAFE set up four participatory research plots, infarmers’ groves, to compare IPM with farmers’ prac-tices. This was consistent with the researchers’ pre-vious efforts to train farmers in IPM (the communi-ties also received training events, and the IPM plotswere implicitly a kind of demonstration plot). The

“IPM treatment” included cultural controls (gleaningberries from the ground, pepena, and picking berriesleft on trees after harvest, repela) and biocontrol (re-lease of parasitic Hymenoptera). In this sense the treat-ment reflected the researchers’ interest in finding al-ternatives to insecticides (Muñoz studied entomologywith the renowned Fausto Cisneros at La Molina, inPeru). The Honduran researchers sensibly kept the trialdesigns simple: just an IPM treatment and a farmercontrol per each replicate. There were four replicates,in remarkably different locations.

Trial geography. Muñoz was based at the researchstation at La Fe, Ilama, Department of Cortés in north,central Honduras. He found two study sites near thestation:

� El Tigre , a nearby community ofsmallholders who had received land aspart of the agrarian reform of the mid1970s. The community was formallyorganised, but all farming was individual.They took little collective action otherthan living near each other and assertinga united block to prevent encroachmenton their land.

� Babilonia, a large, commercial estate ofover 100 hectares.

Muñoz found two other sites, many hours’ drive fromthe station, in the western highlands of Santa BárbaraDepartment:

� El Corozal, a traditional community ofsmall and medium coffee growers, alsoin the western highlands.

� Agua de la Piedra, a smallholder com-munity. Like El Tigre, Agua de la Pie-dra also benefited from the AgrarianReform, but kept an unusually tight lo-cal organisation. They managed a fewplots of coffee collectively (althoughmost of their coffee was farmed indi-vidually). For about ten years they hadattracted the support of a US-based do-nor (Foster Parents Plan) who hadhelped them first get into coffee, in 1986.

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3. RESEARCH WITHOUT REPLICATES

The researchers carefully set out the plots in equalsizes of one manzana (7,000 m2) per treatment, andbegan to establish the same IPM treatment in eachone. However, even with a great deal of participationby the scientists, by 2001, after three years, they wereforced to admit that the experiment had no replicates(Muñoz, Trejo & Paz 2001). Each research site had aunique set of treatments. This was because of modifi-cations made either by farmers, or by researchers inresponse to different conditions.

Researchers lost replication, in spite of the fact thatthis was not even a highly participatory trial; it waslevel 1, on-farm research largely controlled by theresearcher. However, with a highly commercial, pe-rennial crop, over 3 years, farmers are bound to even-tually introduce enough changes into the crop man-agement to eliminate strict experimental replication.

Farming systems determine pest incidence more

than control tactic. The researchers collected a greatdeal of data. They also paid community members totake data (more on this later). This carefulness allowedthem to salvage at least one very important conclu-sion from the research.

Besides the high annual variation, observe (Table 11)how there is little difference between control (farmer)and IPM plots. There is however, wide variation be-tween farms. By far the place with the most CBB dam-age is the large estate, Babilonia. The smallholdersachieve reasonably good control in every year. Thebest control of all is achieved in El Corozal, the tradi-tional coffee farming community.

Large estates have more berry borer incidence becausethey are large. The owner is often absente, and leavesmanagement to a hired professional. No matter howconscientious the owner and manager are, they can-not invest the amount of time per hectare that a small-holder can. During a visit, the manager complainedto one of the senior authors that the quality of hiredhands was poor and that he had to compete for labourwith a maquiladora factory.

Large estate managers must hire overseers to super-vise workers, who are paid by the amount harvested,so workers do not bother to pick up spilled berries,

and may skip some trees entirely if they are poorlyladen with fruit. This provides ample CBB habitat forfollowing years.

More coffee left in groves on large estates. Directevidence of the above idea comes from data on theamount of coffee that researchers paid to have gleanedfrom the IPM treatments in each of the 4 “replicates.”(They did not glean coffee from the control plots,which were managed by farmers.)

Here we see clearly that there is far more coffee lefton the ground and after harvest on a large estate thanon the small farms (Table 13).

Farmer experiments. The Project anthropologist(Bentley) visited Honduras twice in 2000 to work withMuñoz and other Honduran researchers. The first visitwas a tour of research sites (5-11 June 2000) and thesecond was to lead a workshop in ethnoscience andparticipatory research with the Honduran, Mexicanand Guatemalan staff (21-24 August 2000). Althoughthese were short visits, they helped spark an interestin farmer experiments. By the end of the Project,Honduran researchers documented at least two ex-periments by farmers themselves (Muñoz, Trejo &Paz 2001).

Stump & spray a strip. This technique was inventedby the management of the Babilonia estate after threeyears of interaction with Project staff. The estate haddivided its holdings into five plots of 30 manzanas(21 hectares) each; they stumped one every year.Based on researcher’s observation that the berry bor-ers abandoned the newly stumped groves, to fly toneighbouring ones, the owner, José Angel Saavedra,began directing his workers to spray insecticide instrips, on the edge of groves next to the stumped one.Muñoz, Trejo & Paz (2001) report that this lowersCBB incidence by 4%, compared with plots that arenot sprayed.

Dry fruits. Jorge Villanueva of El Tigre has inventeda control combining the picking of dried coffee ber-ries from the trees in March, followed by insecticideapplications (Muñoz, Trejo & Paz 2001). This is in-teresting because it is at the height of dry season, notimmediately after harvest. By waiting, the farmer isable to pick the berries during the agricultural “downseason,” when there are fewer tasks competing for

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his time. There is also probably less foliage on thetrees, and the berries are easier to see and reach. Thepractice makes sense if the farmer can do it beforeany significant rains, which would stimulate emer-gence, since the adult borers tend to wait inside theberry until they become fully moistened by rain.

Experiments. Both of these experiments involve in-secticides. They are both influenced by new bioeco-logical information they received from the Projectregarding CBB movement and habitat. They wereclearly not copied from Project recommendations,since the Honduran staff was quite reluctant to rec-ommend insecticides. Muñoz also notes that the farm-ers who have worked with the Project are harvestingmore thoroughly, so that on the smaller farms there ishardly any coffee left to glean.

Hot-spots. The Honduran staff and CATIE edited amanual on extension material for coffee farmers(Muñoz & Paz 2000). It stresses IPM, including theclassic notion that chemical insecticides may be usedas a last resort, but only after sampling the pest popu-lation to determine that it has reached the thresholdlevel of economic damage. It does not specificallymention the idea of applying insecticide only on CBBhot-spots. However, it is possible that the Honduranstaff told farmers something about it.

Counting. For one thing, by the end of the Project,researchers were downplaying the idea of pest scout-ing. The farmers could do the counts, which involvedfilling in some 500 or 600 little boxes, an effort thattakes three hours or more. But farmers were unwill-ing to take the time. The Project paid a farmer at eachsite to count the pests in the experimental plots, andgive the completed sheets to the researchers. It seemsthat no farmers adopted the practice spontaneously.

Surveys . The Honduran researchers began and endedtheir work with a formal survey. The 52 questions mayhave taken two hours to administer. The first surveywas given to 74 farmers in three areas of Honduras(La Libertad, Comayagua and the Lake Yojoa area,Cortés & Santa Bárbara) in April 1998 (Muñoz, Paz& Trejo 2000). The second survey in 2001 was ad-ministered to 66 farmers in two communities wherethe test plots are located (El Tigre, Cortés and Aguade la Piedra, Santa Bárbara) and on some farms near

the research station at La Fe (Muñoz 2001). In otherwords, the two surveys had a lot of overlap, but thesecond survey was more biased in favour of farmerswho were more likely to have had contact with theProject. Both surveys report many farmers sprayinginsecticide only on hot-spots. The practice does notappear to have increased or decreased as a result ofthe Project. This was certainly an opportunity wasted:we still do not know how farmers identify hot-spots,or how effective their hot spot spraying is for CBBcontrol, nor do we know how natural enemy popula-tions respond to it. The Project should have validatedthis farmer practice.

4. EXTENSION

The Honduran researchers hoped that participatoryresearch would help extend IPM technologies. In theirfinal report, Muñoz et al. report that farmers learnedfrom the test plots and adopted the techniques (Muñoz,Trejo & Paz 2001). This seems questionable. For onething, we have seen above that the IPM technologieswere not significant in reducing pest populations.Secondly, in the final survey, carried out only in thecommunities where the experimental plots were sited,only half of the farmers surveyed had even heard ofthe test plots. Over half of those who did know theplots existed had no idea what the research was about(Muñoz 2001).

5. VALIDATION

Collecting the first fruits (i.e. some weeks or monthsbefore the main harvest they selectively remove in-fested berries of early minor flowerings, see Table 12is a farmer invention, practiced on some plots in Aguade la Piedra. An important part of FPR is validatingsuch innovations. The Honduran researchers collectedsome basic cost data, concluding that first fruits couldbe collected at a cost of $7 per hectare. Table 13 showsthat Agua de la Piedra has very low berry borer inci-dence. It is possible that this practice is cost effectivefor very poor farmers, although more research maybe necessary. (Bentley noticed that many people inthe community did not use the technique on their in-dividual plots, even though helped carry it out on thecollective plot. This lack of adoption suggests that

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PLACE

El Tigre

Babilonia

El Corozal

Agua de la Piedra

UNUSUAL THINGS ABOUT THE IPM PLOT

Is the only trial where the IPM plot and the controlare separated by several (3) km.

The estate workers spray endosulfan.Was near a recently stumped grove in 1999.Very light shade (other farms are in moderate todense shade).

The farmer stumped half of the plot.

The community hand pick the first fruits, i.e. theyremove the coffee berries that are infested with thecoffee berry borer.

Researchers did not release parasitic wasps.

UNUSUAL THINGS ABOUT

THE CONTROL PLOT

Separated from the IPM plot. (Atthe other sites the IPM and farmerplot are contiguous).

Endosulfan is used.Is near a recently stumped grove.Very light shade.

All of the control was stumped.

No wasps are released.

Table 12 Why there are no replicates

Source: Adapted from Bentley 2000

PLACE

El TigreBabilonia (Estate)El CorozalAgua de la Piedra

1998 1999 2000 1998 1999 2000

11.0% 2.3% 7.5% 10.0% 7.9% 15.3%35.6% 6.2% 25.2% 32.0% 10.0% 49.2%0.1% 0.5% 0.3% 0.3% 0.5% 0.3%2.0% 3.3% 0.8% 2.1% 2.7% 0.8%

CBB INCIDENCE IN IPM PLOT CBB INCIDENCE IN FARMERS’ PLOT

Source: Adapted from Muñoz, Trejo & Paz 2001

Table 13 Coffee berry borer (CBB) incidence by location

there may be a reason for not adopting it, such as lackof labour at that time of year).

Fallen fruits. In another study, the Honduran research-ers calculated that of the berries that fall to the ground,58% of them either rot or sprout, and thus are nothabitat for the coffee berry borer. This modest studywas a nice touch, one of many formal studies done bythe hard working Honduran scientists. It is a kind of across between a natural history study and a validationof farmer practice (harvesters drop some grains, butmost are not CBB habitat).

Farmers from the 1991 project abandoned rearing ofparasitoids. In 2000, Bentley asked Muñoz what hadhappened to the farmers who had received training inrearing parasitoids. Muñoz reports that these farmershave now all abandoned rearing wasps, because oflow coffee prices (Muñoz, Trejo & Paz 2001). Moreinformation on this case would be interesting. As aresult of this intensive, probably high-quality train-ing, did farmers adapt the concept of rearing wasps?Did they innovate any other technologies based onit?

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6. SYNOPSIS

The Honduran researchers made a concerted effort toinclude a wide range of farm types from the largest tothe most humble. They achieved a good rapport withfarmers, but were beset by methodological problems.They were insufficiently analytical of things that didnot work and through inexperience in FPR they didnot fully appreciate some of the potentially interest-ing things that farmers did. They responded well toon-the-job training.

We now realise how difficult it is to change estab-lished research practices and that workshop-style train-ing may not be the best use of resources for this sub-ject. The fact that researchers were receptive to thenew ideas they encountered during inter-disciplinaryfield work and practical, field-training makes us opti-mistic that change in attitude is possible and that alonger term project, well structured, could yield sig-nificant sustainable improvements.

After nearly 20 years work on coffee, Raúl Muñozhas now left to do other things.

PLACE COST OF AMOUNT COST OF AMOUNT

GLEANING 1999 GLEANED 1999 GLEANING 2000 GLEANED 2000

El Tigre $16 46 lb $29 46 lbBabilonia estate $136 1,000 lb $128 717 lbEl Corozal $9 19 lb $4 7 lbAgua la Piedra $6 9 lb $3 2 lb

Table 14 Amounts and costs of coffee gleaned in IPM treatment, 1999 and 2000

Source: Adapted from Muñoz, Trejo & Paz 2001

REFERENCES CITED

Bentley, Jeffery W. 2000 The CFC Coffee Berry Borer IPMProject: Honduras. Report submitted to CABI, Egham, UK.16 pp.

Muñoz Hernández, Raúl Isaías 2001 Resultados de Encuesta, SanLuis, El Tigre y La Fe. MS. 6 pp.

Muñoz Hernández, Raúl Isaías, & Hugo Henry Paz Paz (eds.)2000 Información Preparada para Productores y Técnicosque Participaron en Cursos-Talleres sobre “ManejoIntegrado de las Plagas en Caficultura” con Énfasis enInvestigación Participativa. IHCAFE: La Fe, Ilama, SantaBárbara, Honduras. 222 pp.

Muñoz Hernández, Raúl Isaías, Hugo Henry Paz Paz & ÁngelRafael Trejo Sosa 2000 “Resultados de Encuesta sobreCaficultura Efectuada en Tres Zonas Cafetaleras de Hon-duras,” pp. 1-23. In R. Muñoz, H. Paz & A. Trejo (eds.)Informes Técnicos de Investigaciones Realizadas en Hon-duras 1998 – 2000. IHCAFE: La Fe, Ilama, Santa Bárbara,Honduras. 104 pp.

Muñoz Hernández, Raúl Isaías, Ángel Rafael Trejo Sosa & HugoHenry Paz Paz 2001 Informe Final de ActividadesDesarrolladas en Honduras (Marzo 1998—Noviembre2001) IHCAFE: La Fe, Ilama, Santa Bárbara, Honduras.21 pp.

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BACKGROUND

The leader of the Mexico project, entomologist JuanBarrera, had a long history of research and extensionwith parasitic wasps. Besides classic biocontrol, inthe early 1990s, Dr Barrera designed and implementeda project to train farmers to produce parasitic Hy-menoptera in rural rearing centres, and to use Bb tocontrol the berry borer. (Bb is Beauveria bassiana, afungus which attacks and kills certain insects.) Thisinnovative effort even included writing a comic bookas an aid to teach farmers in an enjoyable format(Barrera & Castillo 1996). For reasons still not fullyunderstood, in spite of these best efforts, farmers ei-ther did not adopt the techniques (Damon 2000), oras in the Honduran case, adopted rural centres for rear-ing wasps, only to abandon them after project staffstopped visiting the field. This previous experiencehad a profound effect on this current project. DrBarrera hypothesised that biological control was aneffective tool for control of the berry borer, and thatfarmers would adopt biocontrol if it was properlytaught to them.

The current Mexico project was housed at ECOSUR(El Colegio de la Frontera Sur), which is a universitywith campuses in Tapachula and other southern cit-ies. This was a departure from our other countryprojects; most were housed at national coffee insti-tutes. The university setting may have given the Mexi-can Project more of an academic framework. It cer-tainly had a solid scientific foundation.

Barrera enlisted a Ph.D. candidate, Ramón Jarquín,to implement much of the Project, and to write histhesis on it. Jarquín designed his research as an ex-tension experiment: to test the hypothesis that par-ticipatory extension was more effective than institu-tional extension. Thus, unlike most of the other coun-tries, the Mexico project was based on two clear, cross-cutting research objectives:

1) To prove that proper extension would convincefarmers to adopt parasitic wasps and Bb.

2) To compare participatory extension with non-par-ticipatory (Table 15a y b).

The Mexican staff had a sophisticated notion of par-ticipation. They also understood that participatoryextension was not research.

1. STUDY NUMBER ONEParticipatory vs. Traditional Extension

Selecting the communities

Unlike the Honduran and Guatemalan cases, inMexico, the Project staff did not simply chose com-munities where they had previous, agreeable relation-ships with farmers. The Mexican Project started witha large survey of communities. In 1998 ECOSURcontacted the Unión de Ejidos Lázaro Cárdenas27 ,near Tapachula, Chiapas. Unión leaders said that farm-ers were interested in controlling berry borer. Projectstaff held meetings in 33 communities in 1998. In 18of the communities, the local people walked out whenthey realised that the Project was not going to donatematerials. Project staff conducted farmer surveys andpromoted sampling in the other 15 ejidos. We havenoted elsewhere in this manual that smallholders donot like quantitative pest sampling. Of the 15 com-munities in Chiapas that showed interest in berryborer, people were only willing to do sampling inseven communities. The project selected four com-munities to work with, the four that showed the mostinterest. In other words, the collaborating communi-ties were selected to:

� Have coffee berry borer� To show concern about it� And to be willing to sample.

In 1999, the Project started the extension experiment,with the following two treatments:

In each of the four communities, Project staff helpedestablish two berry borer trials. Each trial had twoplots of 0.5 ha each: an IPM plot and a control plot.The Project staff helped farmers gather data on rain-fall, temperature and soil. In each half-hectare plot,the Project took samples on 10 sites, five trees persite, and 20 berries per tree.

27An umbrella organisation linked to the PRI. It provides technical assistance and other services to ejidos in Chiapas. Itused to distribute fertiliser and credit.

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TREATMENT A: PARTICIPATORY B: INSTITUTIONAL

Interactions with farmers Collective IndividualDecision-making Horizontal VerticalData-taking Collective Project staffTeaching style FFS Demonstration plotsDiffusion Workshops for analysing results Written flyers and field daysTraining Field and workshops Talks and practical demonstrationsDesign Farmer suggestions are incorporated A program is established and followedEvaluation of results With community By technical staff

Table 15a Description of the treatments in the extension experiment

COMMUNITY MUNICIPALITY ALTITUDE IN METERS MODEL

Piedra Partida Motozintla 1000 ParticipatorySanta Rosalía Tapachula 960 InstitutionalTiro Seguro Tapachula 608 ParticipatoryMixcum Cacahoatán 585 Institutional

Table 15b The four communities in the extension experiment

The IPM treatment included

�cultural control (collecting perforated berries,pepena and repela)� releasing parasitoids�Bb

As in the Honduran case, the control group was man-aged by the farmers.

Project implementation

Monthly visits. The team visited each community aboutonce a month, as inspired by the FFS model. The per-sonable Mr Jarquín handled most of the communityrelations, but was accompanied by extensionists whodid most of the teaching. One extensionist stayed withthe Project for three years, and taught the villagers inthe participatory treatments. Although it was not partof the experimental design, there was a high turnoverof extensionists on the institutional treatment (as fre-quently happens with public institutions). A succes-sion of three extensionists worked in the communi-ties of the “institutional” treatment.

Little difference between treatments. By 2000, theProject staff recognised that in practice, there was littledifference between the two treatments. Both allowedfor community input. For example, the trial plots inall communities were placed on land selected by farm-ers. Even in the “institutional” ejidos, the local farm-ers helped conduct the sampling, just as in the “par-

ticipatory” ones. In fact during our visit in June 2000,more farmers participated in helping researcherssample for pests in the “institutional” than in the “par-ticipatory” villages; this was due to individual deci-sions by the farmers. Project staff concluded that therewas little difference in results: that both participatoryand institutional styles “worked.”

In his presentation at the final Project meeting in CostaRica, in October 2001, Jarquín returned to the idea ofthe extension treatments, saying that there was a sig-nificant difference between the two. Bentley ques-tioned him about it, and he said after looking at itagain carefully, the differences had emerged.

Observations on Study 1

Sampling is cumbersome. In June 2000, Bentley ob-served researchers and farmers in Mixcum, samplingberry borer on two plots of half a hectare each. Sam-pling is inherently time-consuming, and even thoughthe Project staff and farmers were experienced withthe plots and with the method, it took them most ofthe morning to sample the two plots. Such numericalsampling methods are too complicated and time-con-suming to be adopted by most smallholders.

Adoption was low. The Project recommended thatfarmers glean coffee berries. The farmers that Bentleyinterviewed in June 2000 said that the traditional prac-tice was to allow poor neighbours to enter the grovesafter harvest, to glean. The trend among commercial

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farmers was to stop allowing gleaning, because somegleaners broke trees, trying to reach the berries lefton top branches. As a result of the Project, at leastsome farmers were aware that gleaning helped man-age the CBB, and were allowing their neighbours tostill come into the groves.

Those same farmers also knew about Bb, as a resultof Project extension, but they found it difficult andexpensive to use. There was little or no adoption.

Parasitic Hymenoptera were still important to Projectstaff, who monitored them closely and told farmerswhere the wasps were (e.g. that by 2000 the waspswere being found in the control plot, not just in theIPM plot). Farmers seem interested in this, and ob-served staff members releasing wasps from jars. How-ever, as part of this Project, the staff did not try toteach farmers to rear parasitoids themselves.

Human experiments. Entomologists may have a dis-ciplinary tendency to divide human subjects intogroups, and to test different extension strategies for-mally. Keith Andrews inspired a large set of these inHonduras in the late 1980s, early 1990s. Like theMexican case, those experiments were also frustrat-ing, in part because it was difficult to keep the treat-ments separate. It feels insincere to treat one commu-nity one way and another in a different way. It seemsmore natural to be consistent with all of them, and tolet each relationship evolve on its own course (delRío et al. 1990, Bentley & Andrews 1991, Bentley &Melara 1991).

Bentley suggested that Jarquín write the experiencequalitatively, instead of describing it as a compara-tive study of two treatments.

2. STUDY NUMBER TWOAn Experiment Arising from

Listening to Farmers

Hot-spots

In June, 2000, farmers said that they knew which partsof the grove had more berry borer. Barrera and Jarquínagreed that other farmers claimed to know where CBB

hot-spots occurred. For example, at the beginning ofthe Project, collaborating farmers helped the Projectto site the IPM test plots. Although the staff did notknow it at the time, farmers always put the IPM plotsover large hot-spots.

Barrera, Jarquín & Bentley designed the followingsampling experiment:

Background

� Farmers find numerical sampling difficultand tedious.

� Sampling of berry borer is time-consumingeven for specialists.

� Berry borer occur in hot-spots of severalcontiguous trees.

� Sampling attempts to create a model of thosehot-spots.

� The model is flawed, because of the geo-metrical (checkerboard) sampling design.

� At best, sampling creates a simplistic math-ematical model of a more complex reality. Sam-pling is based on the premise that some plantsrepresent others. A number of plants are sampledin a “site,” which is rectangular and arbitrarilydefined.

� To counteract this problem, statisticians havedeveloped “adaptive” sampling where the sam-pler has the option to change his plan based onwhat has been observed during the course ofthe sample (Thompson, 1992). Perhaps farm-ers intuitively do something similar when theylocate hotspots.

� Researchers’ knowledge of sampling is outof date and this may also apply to statisticiansadvising them.

� Sampling is difficult and even experts get itwrong. At worst, sampling is an artefact.

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Hypothesis

H1: Farmers know where the berry borer hot-spots arein their coffee groves. Farmers know the size andboundaries of the hot-spots.

Research protocol

1. Interview farmers. Ask them if they can identifyplaces in their groves where there are more berryborers.

2. Ask the farmers to take the researchers to thosespots.

3. Ask the farmers if they can identify the boundariesof the hot spot. If they say yes, mark the bound-aries (e.g. with plastic tape tied to trees).

4. Do an entomologically sophisticated sampling ofthe grove to determine where the hot-spots are. Thisshould be done with the farmer’s permission, butthe farmer does not need to take part in the actualsampling. This sampling is being done for scien-tific purposes, and is not intended to be somethingthat a commercial grower would find useful. Thesampling can take up to several hours. The mainpoint is accuracy, not developing a farmer-friendlysampling method.

5. At first, it may be a good idea to hone the method,by working with farmers already well-known byProject staff. Later, researchers can work withfriends of those farmers, and later with farmers whohave had little or no contact with the Project.

6. Researchers will repeat the method—a) interview,b) mark hypothetical hot spot boundaries, c)sample—with many farmers, until the scientists canconfirm or reject the idea that farmers know wheretheir berry borer hot-spots are.

In fact, when the research was actually conducted (seeSection 3, below) not all of these points were cov-ered. For example, it seems that researchers did notask farmers to mark the boundaries of the hot-spots,

but merely point out the spots. However, in all fair-ness, carrying out all six of the above points wouldtake a long time. Section 3 reports on a preliminaryeffort, and while it may not prove that farmers canidentify hot-spots, does suggest that they can.

Applications of experiment results

Berry borer control technologies tend to be expen-sive. If coffee growers could apply them only to hot-spots, farmers would lower IPM costs, whilemaximising the benefits. This may help some tech-nologies or farming systems become profitable. Forexample, Bb or hand-picking may not be profitable ifapplied to a whole grove, but it may be, if applied to asingle hot spot.

Confirmation of the notion that farmers

can identify hot-spots

Jarquín later wrote a paper on hot-spots. It was a shortstudy of two farmers, but it did suggest that farmerscould accurately identify the hot-spots in their owngroves (Jarquín, Montes & Barrera 2001).

In November 2001, Ramón Jarquín sent us a draftpaper that suggests that farmers can identify hot-spots.Farmers’ notions of the factors associated with hot-spots (e.g. sun, shade, humidity) are not unlike thoseof researchers. Farmers also suggested some novelideas, e.g. that hot-spots were near paths, which re-searchers had not noticed, but which were validatedby Jarquín and his colleagues. See Section 3 for atranslated and slightly abbreviated version of Jarquín(2001).

3. VALIDATING FARMER KNOWLEDGE

OF HOT-SPOTS IN CHIAPAS28

Entomologists have reported that the coffee berryborer has a patchy distribution, forming “hot-spots”(Decazy et al. 1989, Barrera 1994). Hot-spots havebeen shown to be related to coffee grown in shade(Baker 1984, Baker et al. 1989, Barrera & Covarrubias1984). However, studies in Honduras (Muñoz et al.1986) and Nicaragua (Monterrey 1994) did not ob-

28This section was written by Ramón Jarquín (ECOSUR, Tapachula, Chiapas, Mexico), edited and translated by Jeffery Bentley. Javier Valle Morahelped with the statistical analysis, and project extensionists Manuel Figueroa & Román Montes assisted with the fieldwork.

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serve a relationship between shaded coffee and CBBincidence. Other authors (Bustillo et al. 1990) con-sider that high relative humidity (90 & 98.5%), con-sistent with shady groves, favours the CBB.

Intercropping of Arabica coffee (Coffea arabica) withrobusta coffee (Coffea canephora) may favour berryborer, since robusta bears fruit over a longer periodand so provides alternate habitat for CBB (Leach1998).Until now, the method most often recommended togrowers to identify hot-spots has been systematic sam-pling. It supposedly allows farmers to identify hot-spots and then apply a control measure only to thoseareas that require it. Nevertheless, few farmers haveadopted quantitative sampling (Guharay 1997, Jarquínet al. 1999, Jiménez 1999, Jarquín et al. 2001).

Recent fieldwork in Chiapas, as part of the CFC-spon-sored Coffee Berry Borer Project suggests that farm-ers can identify hot-spots without quantitative sam-pling. To further test this hypothesis, and to validatefarmer knowledge, we studied farmers’ perceptionsof CBB hot-spots (which farmers call focos ormanchones) and compared this with scientific knowl-edge of hot-spots.

Context

The research was conducted with coffee growers inthe Soconusco and Sierra regions of Chiapas, Mexico,in the communities of Santa Rosalía and Tiro Seguroof the municipality of Tapachula, Mixcum of themunicipality of Cacahoatán and Piedra Partida of themunicipality of Motozintla. The research team took arepresentative sample of each community. In eacharea, some farmers had been trained by staff of theCFC Coffee Berry Borer Project.Step one. In June-July 2001 the team administered171 short questionnaires on berry borer to farmers.The basic question was, did they think that the berryborer had a uniform distribution within the grove ornot. Of the 171 farmers, 108 (63%) said that the dis-tribution is not uniform; 85.1% mentioned at least onereason, in order of frequency:

� Coffee is exposed to sun (37.9%)� To shade (19.4%)� The spot is near a road or path (11.1%)� Arabica coffee is intercropped with robusta

(10.1%)� Lack of integrated pest control (3.7%)� Humidity (2.7%)

Figure 21. What causes hot-spots? Responses from farmers surveyed

in January-April (1st step n = 171) and August-October (2nd step

n =25) 2001 in Soconusco and the Sierra of Chiapas, Mexico

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The rest of the respondents (14.8%) said they did notknow the reason for hot-spots (Figure 21).

Step two. From August to October 2001 the teamworked more closely with a smaller group of 25, farm-ers selected at random from those in the first set whohad said that CBB is not distributed uniform. The teamgave them another questionnaire to flesh out theirearlier answers and did field verifications of the ex-istence of hot-spots.

First, farmers identified a hot spot. Next, researchersconfirmed that the area had a high level of berry borerdamage. The research team documented intercroppingwith robusta, shade density, proximity to a road andto neighbouring plots. Shade was quantified with aspherical densometer, using the methodology ofLemmon (1956). Researchers and farmers collabo-rated in carrying out a systematic sampling of berryborer in each plot.

In the second survey, 36% of the farmers claimed thatthe lack of integrated pest management was the maincause of the hot spot. This was probably what theythought the research team wanted to hear. The lack ofshade was mentioned in 16% of the cases, and thepresence of robusta and excess shade were each men-tioned 12% of the time. Another 12% said they didn’tknow. Proximity to a neighbour’s grove or to a roador path were only mentioned 4% and 8% respectively(Figure 21). In both questionnaires, farmers explainedhot-spots by either shade, sun, being near a path, or tointercropping with robusta.

Validation

Of the hot-spots farmers showed us, 64% had arabica-robusta mixes, and 36% were pure stands of Arabica.The difference was not statistically significant (c21=1.96, P=0.1615).

68% of the hot-spots indicated by farmers were withinfive metres of a road or path, while proximity to thegrove of a neighbour who does not control pests, orto a permanent body of water, were found in 17.4%and 8.6% respectively. Being near a path was statisti-cally significant (c22= 14.16, P=0.000083).

23 of the 25 hotspots were in shade of over 64%, whichwas highly significant statistically (c21= 20.16,P=0.0000007).

Discussion

Most farmers claim that berry borer hot-spots are cor-related with some environmental factor, but farmersdo not attribute clusters of CBB to any one cause.Some farmers consider shade to contribute to CBBhot-spots, and by far, most of the hot-spots that farm-ers showed us were in dense shade.

During the first questionnaire, most farmers attrib-uted CBB hot-spots to an excess of sun, consistentwith studies from Colombia (Cárdenas & Posada,2001), which report that spots of light attract the CBB.The team did not find intercropping with robusta cof-fee to be significant, in contrast to an earlier model-ling study by Leach, (1998), using data from theSoconusco region. Many hot-spots are found close topaths and roads, which could be due to exposure tocontamination from people passing by with harvestedcoffee berries. Only a few farmers blamed hot-spotson roads.

External change agents should take local knowledgeand experiments into account in order to find solu-tions that are consistent with local economic and eco-logical conditions (Bentley 1992). Our study supportsthe hypothesis that farmers can accurately identify hot-spots of CBB without quantitative sampling. Thisstudy of local knowledge has created an opportunityto identify berry borer hot-spots quicker, and muchmore efficiently than by using systematic sampling.

Conclusions to Section 3

Hot-spots are linked to a complex of biotic and abi-otic factors, which farmers recognise. We did not con-firm the accuracy of all of the farmers’ explanationsfor hot-spots, but more research on this is needed.For example farmers linked hot-spots mainly with sun,but researchers found that the spots were almost allin dense shade. However, research in Colombia hasfound an association between canopy holes and hot-spots.

This study is a first step to developing a method, whichcan be used in follow-up studies to monitor the causesof hot-spots, relating the information closely with thelocal knowledge of farmers. The confirmation thatfarmers can accurately identify coffee berry borer hot-spots, without doing difficult and time-consumingnumerical sampling opens a door to more farmer-friendly sampling programmes.

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4. SYNOPSIS OF MEXICO CASE STUDY

The Mexican team tried to develop a rigorous andscientific approach to evaluating participatory exten-sion vs. traditional extension. While there are someindications that there were differences between thetwo treatments, at least one team member (Bentley)remains sceptical. The epistemological problem withsuch a study is that the researchers carrying it out in-variably have a bias, and may sub-consciously eitherfavour one treatment, or on the other hand, they maytreat all of the communities in a similar manner, blur-ring the difference between the treatments. Thus it isdifficult for the researchers to modify their behavioursystematically and arbitrarily within communities ofdifferent experimental treatments. The extension studywas certainly a heroic effort, and we await the dis-cussion of it in Ramón Jarquín’s Ph.D. dissertation.

The hotspot study was a good initial attempt to ac-cess farmers’ knowledge and present it in a conciseand scientific way. Further work is needed to deter-mine how the farmer comes to recognise the hotspot,and whether he takes the optimal amount of effort tocontrol these. The work throws up some interestingquestions:

� What is the definition of a hotspot, and do farm-ers concur in this definition?

� Do we have sufficient scientific knowledge to beable to predict the effect of controlling only hotspotsor to be able to tell farmers how much extra time andmoney to spend on them?

� Could our understanding of hotspots help to im-prove control measures by encouraging or discourag-ing their formation?

This is an example of how work with farmers caninform researchers’ ideas and help to steer the researchagenda towards solving their problems.

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