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The Lithuanian Dairy Farms Project
Concept for farming systems researchTroels Kristensen & John E. Hermansen, DIAS
IntroductionFor more than 20 years the research group 'Farming Systems Unit' at DIAS has worked with live-stock farming research based on studies on commercial farms as a key element. The focus of theresearch has changed over the years from investigating mainly how to increase productivity ondairy farms to investigating, at present, how to develop efficient and environmentally sound live-stock production systems in general. This development is reflecting the expectations of the society,which puts a pressure on farmers to make them produce at competitive prices and at the same timeto include environmental concern and aspects of animal health and welfare. The aims have been todescribe production and environmental impact in different farming systems, to test ideas for theimprovement and to develop decision tools for farmers and advisors. The approach is based on arespect for the individual farmer and his possibilities and motivation. Researching with farmers on
issues that were identified as important through a participative process, in contrast to performingresearch on the farm that the researcher considers important and which the researcher happens toconduct on the farm.
Concept for research
The complexity of the farming system makes an interdisciplinary approach necessary. Case studieson private farms are in this respect a useful method giving all researchers the understanding of theactual way of farming. The elements used and the relation between them are illustrated in figure 1.The actual emphasis on the different elements may vary dependent on the character of the project,
but studies on private farms as cases are the key element.
The double arrow in figure 1 illustrates the researcher-farmer interaction, and some of the elementsin the approach. Recordings takes place and a feedback is given as an immediate response based onthe individual records or when farmers and their advisors are presented for more 'analysed' or inter-
preted results. This feedback serves several purposes. The researchers are getting wiser as regardsreal obstacles for improving the authentic system considered, the data are challenged/scrutinisedsoon after recording, a fact that minimises the risk of registration mistakes. The farmers get wiser,too, meaning that, to a higher degree, the production plan is actually considered in the light of avail-able knowledge rather than being coincidental. A combination of case studies, models and experi-ments are elements in the process from farm results to general scientific biological knowledge, toolsto farm management advise and decision aids.
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C a s e -
s t u d i e r
E p i d e m i o -
l o g i s k e
s t u d i e r
U d v i k l in g a f
s t y r i n g s r e d -
s k a b e r
F o r s g
P r i v a t e f a r m s R e s e a r c h s t a t i o n s
C a s e -
s t u d i e s
D e c i s i o n a i d s
E x p e r i m e n t s
M o d e ls
( r e s o u r c e u s e
a n d p r o d u c t i o n )
S c i e n t if ic r e s u lt s : N e w k n o w le d g e , t o o l s
Figure 1. Approach for farming systems research.
The farm as a system
The systems approach basically consists of accepting the irreducible complexity of the system un-der study, of striving to understand the overall operation of the system and not only the mechanismswhich are brought into play within it. It also involves identifying and obtaining the knowledge mostuseful for the manager (Beranger & Vissac, 1992).
Production system
soil crops animal
Buildings/machinery/workforce
products
Managementsystem
measurementadjustment
Uncontrolablefactors
Controlablefactors
Figure 2. A farm as a cybernetic system (Srensen & Kristensen, 1992).
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Srensen & Kristensen (1992) have illustrated the livestock farm as a cybernetic system, as shownin figur 2. The farm consists of a production system and a management system. The different enter-
prises in the production system can be further divided into subsystem, typical organised in a hierar-chy system. The production system can be modelled either as a farmsystem or as part of the farm.
The production is controlled by a management system, meaning that the farm also can be seen as ahuman activity system, in line with the soft system approach (Bawden, 1991). The managementsystem can be organised at different level, strategic long term planning and operative short term
planning and control. Management in this context can be seen as running adjustment in the produc-tion system due to variation in uncontrollable factors. Some of the uncontrollable factors will notinfluence the production system directly, like climate, but indirectly, as change in regulations foragricultural production, new subsidies etc. This means that management often is a choice betweendifferent opportunities and not a definite solution.
The interaction between the human activities (management) and the production system is essential
in the farming system research. Looking at and understanding of production results is only mean-ingful, when both the actual production system and the management of the system are known. Fig-ure 2 can be further developed by including different groups in the society, which are supposed tohave interest and influence in the development of agriculture and the farming system. Kristensen &Halberg (1997) illustrated this as shown in figure 3.
Figure 3. A model of the farmer reflecting on the farms sustainability in light of the value systems
and discourses in society (Kristensen & Halberg, 1997).
The farmer does not develop his ways of farming and his production system isolated from the soci-ety surrounding the farm. Farmers reflect and react to changes both in surroundings and in the pro-duction systems in different way. Research using farming styles concept has demonstrated that the
Public
authoritiesEnvironmen-
talists
Advisors
Scientists
Conventional
colleagues
Organic
colleagues
Market
Production
System
Farmer
Decision System
products
externalitites
controllable factors
uncontrollable factors
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farmers, though different, tend to group around certain value orientations (Noe, 1997). This way ofunderstanding farming can be usefull in development of decision aids and set up of relevant produc-tion research.
To give an idea about how the systems approach can be used to develop farming system is in figure
4 given an illustration of the elements that has to be taken into consideration when working withgrassland planning and utilisation. It can not only be seen as a way of harvesting grass, but has atleast to start with type of grassland, milk production in the herd and possibilities for supplementfeeding. Also the balance between pasture used in the summer and amount of silage for the comingwinter is important. Kristensen & Kristensen (1993) has, based on farm studies and an interdiscipli-nary approach, described a system to grassland planning and management.
Type of
grassland
Grazing intensity
Cutting regimeType of
supplement
Urea in
milk
Amount
of silage
Crop rotation
Stocking
rate
Milk
production
4 Knowledge at partial level4 Tools at farmers level4 Demonstration at farm level
Figure 4. Grassland planning
Figure 5 shows, how we used the farming system approach in investigating the development possi-
bilities for organic farming in Denmark during the 90ties
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The system approach to organic farming research
Farmingpractice
Results
Knowledgecase-
studiescomparative
analysis
experiments
model
proto-
types
Figure 5. The system approach to farming research (Mogensen & Kristensen, 2000)
Some results obtained by the case studies are rather easy to generalise, through comparison withother cases and experimental data in the literature. Based on several cases of different system, likeorganic versus conventional farming, indoor versus pasture feeding, loose housing versus tied upsystems it is meaningful to make comparative analysis, in order to highlight the systems in focus.
Also, a valuable tool for the interpretation of farm results is models. Such models are used in twoways: First to calculate the expected production results, which should be obtained on the farms infocus, based on well accepted technical and biological knowledge and given the actual productionconditions. Such simulated production may facilitate comparisons between farms with different
production conditions. Secondly, a comparison of simulated results with the actual farm results willoften lead to an understanding of the fact that some preconditions in the model are wrong. Themodel can then be improved in some cases, based on the recorded farm data, or the gap in knowl-edge identified by the comparison of modelled and recorded results may lead to the carrying outexperiments directed towards the fulfilment of this gap.
Prototyping is a way of developing new systems based on case studies, models and experimentaldata. The sustainability of the new system is judged from such theoretical work and the most prom-ising is set up either at system orientated research stations or implemented on private farms. On
private farm the implementation will often only be as part of the described system. Kristensen &Kristensen (1997) have given an example of this way of working with farm results.
A particular case, where farm studies are extremely valuable is when the focus is on developingdecision aids. No matter what unique biological information a decision support tool may include thevalue of the system depends on the farmer's possibilities and motivation for using it. This can only
be evaluated in a co-operation between farmer, advisor and researcher. Srensen et al. (1985) hasdemonstrated this in developing a systematic management programme for calf rearing. Also thework by Hansen et al. (1997) in making a computer tool to planning of landuse and manure applica-
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tion has benefited from an interaction between farmer, advisor and researchers with different back-ground.
From idea to results
The idea and hypothesis for a research work makes it possible to choose the most relevant method.
Farming system research is one opportunity as illustrated. This method is relevant when the objec-tive, among others, are
- to describe and develop alternative farming systems- to understand and explain the process of farming- to develop management tools- to understand and describe interaction between different elements at farm level, as herd soil
The system approach is most relevant when one or more of the elements in system is interacting. Inmore experimental research this information is often not realised as the experiments is set up in or-der to minimise this effect (Lockeretz & Boehncke, 1999).
Setting up the most appropriate research project involves a serie of desions from idea to result.Some main elements in our tradition for on farm research are given in figure 6.
Project
Farm
Data
Results
Technician
Localadviser
Local vet.
Scientist
Computer
Litterature
Models
Areato debate
Selection offarms
Dataregistration
-who, freqandhow
Controlof dailyproduction
Data check-internal-external
Dataanalysis
Presentation- farmspecific(case)- general results
Introdu ctionto researchbased on use ofprivate farms
Figure 6. Elements in setting up on farm research and demonstration projects.
Selection of farms
Number of farms has to be seen in relation to the representation of the farms on the one hand andthe possibility to get more specific information about the individual farm. There are no exact guide-lines, but the described approach is not suitable for project that wants to work with a group of farmsrepresenting more common farming systems. As stated earlier the generalisation has to be done notonly from the farm, but also as combination of analysis of farm data and modelling. In developingof new systems a number of 10 to 20 farms will form an acceptable balance between representationand detailed information about the individual farm. If more experimental work is done, 3 to 5 farms
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representing the variation in some of the key factors are necessary. This will make it possible tomake analysis across farms, like demonstrated by Kristensen & Aaes (1999).
Type of production system
If it is possible without making reduction in the purpose of the work it is very important that the
actual production system is as simple as possible, in order to get the most exactly registration of theinternal flow and use of resources.
Type of management system and farmer
Besides being useful from the subject in question it is important that the farmer and the employed atthe farm is motivated for participating in the project. The farmer needs to have some time to partici-
pate in check of data and in the dialog about results and development.
Dataregistration and control
Data registration should as far as possible be carried out by skilled technicians, who are not in-volved in the farming practise and advise on the actual farm. The technicians has to be interdiscipli-
nary in their work, meaning that they must be cable of doing registration on all subjects within aproject, like herd feeding, live weight of animal, crop production and economic figures. Registra-tions like amount of fertiliser, time of harvest, have to be done by the farmer. For registration ofsome specifically activities the local advisor will often be very useful, like registration of veterinar-ian treatments.
SYSTEM (strategic )
Figure 2. Illustration of the basis registration on pilot farms.- level and type of r egistration.
TURNOVER (operational )
machinery herd labour
land buildings other
typesizevalue
breedquota
type
typesizevalue
economic account
FARM
FARM
technical accountImport
ConcentratesSeeds
Manure
Vet. serviceReproduction
Animal
Contractors
(labour)
Export
Crops
Manure
Milk
Meat
roughage
manure
Crops/fields
(date,amount)
-seed-manure-machine- irrigation
- yield
Groups/individualanimals
(date,amount)
- feed intake- vet.- reproduction-
- yield
land herd
acreagetype
Figure 7. Basis registration - system and turnover
Data can be divided into at least two types, system description and registration of turnover, as illus-trated in figure 7. Registration of turn over can be seen as two types, internal flow like manure from
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herd to crop, and external, like import of fertiliser. Some of the internal registration, like use of fer-tiliser to the different field, can be checked against the external flow over a period. Also true in-ternal flows, like manure application to the different field can be check against the production in theherd estimated from feed intake registrations and amount of animal products produced.
Data presentation.As a final part of the datacheck the preliminary results are presented for the farmer and other per-sons involved in the project. This will often be the first presentation.
Farm report
The result of the case study is shown in annual farm reports, where the result from the year in focusis presented and discussed. The discussion is done from an interdisciplinary view trying to under-stand results in the main enterprises together, and also trying to look at the development within thefarm by comparing the results with earlier years. In figure 8, is an example of a farm report, from a
project working with development of organic dairy production.
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Figure 8. Farm report from developing of organic dairy production systems
Farm report for H-No. 40-4Hanne og Vagn Borg
Grdevej 24, Hodde
6862 Tistrup
Systems DescriptionProduction Milk production
History Farm taken into possession 1970Change to organic farming started 1991 and the farm had fully converted as of 1992
Stables Loose housing system with slatted floor and cubicle houses for 165 cowsFemale breeding is stabled in part on deep litter beds, in part on slatted floor with cubicle
housesHerd SDM.
Winter feeding system: Grass/clover silage and whole crop silageSummer feeding system: Grazing in regulated big pens and supplemented with
fresh grass in stableMilk quota: 900,157 kg - 4.16% fatDelivers milk to ko-Mlk A/S (ecological milk company)
Labour 2 users and 2 farm-hands
Soil 155.2 ha (149.2 ha crop rotation). Soil 1, 3 and 4. App. 120 ha irrigated
Rotation principle Barley (whole crop or maturity) with undersown grass/clover lay - grass/clover 2-3 years.
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Figure 8 page2
Key figures for the latest 5 years 92/93 93/94 94/95 95/96 96/97
Milk, kg ECM per cow (control) 6.622 7,015 7,289
Crops, SFU per ha 5,110 4,969 4,504
Acreage, ha per cow 1.13 1.10 1.11Theoretical self-sufficiency, % 86 79 72
Gross margin, total, DKr 1,000 2,772 2,883 3,260
Net income, owner and finance, DKr 1,000 1,802 1,663 1,734
Annual results 1996/97 Total Per ha Per MPE Per ECM
Production (155.2 ha) (140.4 pcs)
- Milk, kg ECM, delivered 930,722 5,997 6,629 -
- Crops, SFU 698,955 4,504 4,978 0.75
Nutrition balance
- Nitrogen, kg N 18,225 117 1307 0.020
- Phosphorous, kg P 970 6 14 0.001- Energy use of herd, MJ 2,214,000 14,265 15,769 2.38
Economy
- Gross margin, DKr 2,214,000 21,005 15,769 2.38
- Net income, owner and finance, DKK 1,733,979 11,173 12,350 1.86
Mlkeproduktion
14
16
18
20
22
24
26
28 kg EKM
Ydelse, 24 u.e.k.Gennemsnit, kontroldagen
Maj Juni Juli Aug. Sep. Okt. Nov. Dec. Jan. Feb. Mar. Apr.
Foderration - ker
0
2
4
6
8
10
12
14
16
18 f.e./ko/dag
Frisk grs
Ensilage og halm
Rapskager, korn, hvedeklid og roepiller
Maj Juni Juli Aug. Sep. Okt. Nov. Dec. Jan. Feb. Mar. Apr.
Arealfordeling mellem afgrderVedv. grs
4%
Grnbyg
3%
Korn
(modenhed)
6%
Kartofler0,4%
Klvergrs
70%
Korn (helsd)
17%
Nettoudbytter
0 10 20 30 40 50 60 70 80
Vedv. grs
Klvergrs
Grnbyg
Korn (helsd)
Korn (modenhed)
Kartofler
Grdens gns.
hkg/a.e. pr. ha
182
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Figure 8 page3
Comments to the farm report 1996/97 H-No. 40-4
Last year's production level of the farm's has been similar to that of former years. The farm has arelatively high concentration of animals (1.19 animal unit per ha), so it has been necessary to buy
especially cereals to feed the animals. Another thing is that the farmer has purchased a 600 kWwindmill placed near the farm. The electricity from the windmill is considered an ordinary produc-tion branch. The influence of the windmill on the economic result is described later in the section.
Last year, a gross margin from the cash crop of DKr 361,511 was achieved. An area with vegetablescontributed with more than half of that gross margin. In 1996 it was necessary to take a greater partof the cereal crops as whole crop and, at the same time, the area with grass/clover was larger thanlast year. Consequently, the area with cereal for maturity was only 9.1 ha, which reduced the grossmargin to DKr 71,003 despite a high yield. Moreover, a high yield of whole crop was achieved,whereas the yield of grass/clover was considerably lower than that of last year, but still a little
above the average for this group of dairy farms.The extent and size of the livestock has not changed substantially last year. The heifers transportedwere small despite a relatively high age at calving, and this is partly due to a low growth on stable(441 g per day). A number of small heifers died in the course of the year. The main reason was
pneumonia because of a bad climate in the calf house.The feed ration for both cows and rearers consisted of a high share of roughage with a great part offresh grass, which was sometimes brought in by a forage harvester. The amount of supplementaryfeed was rather constant, app. 5 SFU per cow per day. The winter roughage consisted of a littlewhole crop, but particularly of grass silage. The feeding efficiency of the cows was high like lastyear, even though feeding level was raised. The feeding efficiency of the rearers during the housing
period was considerably improved compared with that of last year. The annual growth was satisfac-
tory owing to a very high growth at pasture (743 g per day). For the second year, the growth whenhoused was low (537 g per day) due to a rather weak feeding and that was particularly detrimentalto the growth of the heifers.During last year, the milk yield increased by 274 kg ECM. The yield though the year varied, de-crease in August and September and a minor decrease in January. The slightly higher milk yield hadas an effect that the income for milk per MPU increased as compared to last year. As the growthvalue of last year was maintained the total income increased. The costs of supplementary feed aswell of roughage were reduced compared to last year. This year, the purchased supplementary feedwas mainly conventional and that reduced the price. Due to lower costs to harvesting the roughagewas less expensive this year. Totally seen this meant a better gross margin of DKr 1,257 per MPU.The total gross margin of the livestock increased this year by app. DKr 157,000, but as the grossmargin of the cash crop was considerably lower than it was last year, the total gross margin fromfield and housing decreased by app. DKr 134,000. All the same, the farm's total gross margin in-creased by DKr 77,000. As already mentioned, a windmill was purchased and the income (DKK234,691) from this activity - with a linear depreciation of 15 years - is included in the farm's totalgross margin. After capacity costs and writings off the net income increased by DKr 71,000.
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Figure 8 page4
Technical-economic main results 1996/97 H-No. 40-4
Acreage Manure Irrigation Contractors Yield Sales price/ Gross marginField ha ton/ha mm DKr/ha per ha costs DKr/ha
Cash crops100
hkg+SFU
DKr/kg
Barley undersown 9.1 21 37 1,206 50 + 2 1.90 7,765
Roughage 100 SFU DKr/SFUPotatoes 0.6 0 0 4,000 45 2.36Whole crop 26.4 26 54 1,068 47 0.38Grass/clover+grass barley 113.1 25 88 531 46 0.18Permanent grass 6.0 0 0 0 17
Total cash crops 9.1 ha Gross margin: DKr 71 003 Roughage: 146.1 ha
Herd Cows Heifers
Number of livestock 140.4 131.7Average weight (start/end) 565/565 265/265
Turnover of animals Number of kg Number of kgHeifers born (no. of bull calves) - - 65 41 (72)Springing heifers (months at calving) 54 482 54 560 (28.1)Sold - for market 0 - 0 -
- slaughter 50 554 5 469- dead 3 550 6 75
Feed supplyFeed input, SFU Purchase, % Area, ha- Concentrates 441 37 7 -
- Grain and by-products 1,308 109 16 0.06- Milk etc. 42 - -- Grass pellets 19 1 0.01- Fresh grass 1,493 961 - Silage and hay 2,135 422 - 1,10- Straw 12 27
I alt 5,408 1,599 23% + 1.17 ha
Yield
- Milk, control, kg ECM / F% / P% 7,289/4.21/3.37- Growth, kg per animal 27 231- Feed efficiency, winter (SFU/kg growth) 93 (5.5)
Income- Milk, dairy (95% delivered) 21,221 (DKr3.20 /kg ECM)- Milk, house hold, calves (5%) 890- Growth 1,962
Costs- Feed
- Concentrates incl. mineral mixture 4,319 (DKr 2.18/SFU)- Roughage 1,101 (DKr 0.22/SFU)
- Veterinary, medicine 338- Miscellaneous 368
Gross margin (cow + 0.94 heifer + 1.11 ha) 17,947
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Comparative analysis
Having data from several projects in the same concepts and over a time period makes it possible tomake comparative analysis, with the aim of finding some general differences. In figure 9 is given
results showing the N surplus at farm level in relation to production type and stockingrate within thesystem (Nielsen & Christensen, 2001)
Figure 9. Level of N surplus on different types of farms and dependent on stockingrate
N surplus on private farms in Denmark
0
50
10 0
15 0
20 0
25 0
30 0
35 0
0 100 200 300
Manure, kg N per ha
N-surplus,
kg
Np
erha
crop
dairy
pig
Liner (average)
(1997-1999)
Kristensen & Kristensen (1998) have used a combination of deceptive statistic analysis and herd-modelling in order to illustrate the differences between organic and conventional herd feeding and
production.
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Litteratur
Bawden, R.J. 1991. Systems thinking and practice in agriculture . J Dairy Sci., 74, 2362-2373.
Beranger, C., Vissac, B. 1992. A Holistic Approach to Livestock Farming Systems: Theoretical and
methodological aspects. In Gibon A., Flamant J.C. (eds.): The study of livestock farmingsystems in a research and development framework. Proc. 2nd Int. Symp. on LivestockFarming Systems. Saragossa (Spain). EAAP Publ. No. 26 Wageningen. 149-196.
Hansen, J.P., Kristensen, I.S. & Jensen, C.H., 1997. A computer programme as an interactive toolfor planning manure allocation and feed supply on mixed organic dairy farms. Livestockfarming systems. More than food production. Proceedings of the Fourth international sym-
posium on livestock farming systems. EAAP publ. 89, 329-334
Kristensen, T. & Kristensen, I.S. 1993. Management of grass/clover continuosly grazed with dairycows. 2. Management tools. Proc. The white clover meeting of the FAO sub-network on
lowland pastures and foddercrops, rhus. 7 pp.
Kristensen, I.S. & Kristensen, T. 1997. Animal production and nutrient balances on organic farmingsystems. Prototypes. In: Proceedings ENOF workshop Ressource use in organic farming.Ancona, Italy, 4-5 June. 21 pp.
Kristensen, T. & Aaes, O. 1998. Suppleringsfoder til malkeker ved afgrsning i reguleret storfold.DJF Rapport Husdyrbrug, nr. 3, 39 pp.
Kristensen, T. & Aaes, O. 1999. Interaction between level of contrate supplement, season and stage oflactation on performance of dairy cows on pasture. Acta Agri Scand, Sekt A. 49, 1-11.
Kristensen, T. og Kristensen, E.S. 1998. Analysis and simulation modelling of the production in Dan-ish organic and conventional dairy herds. Livestock Prod. Sci. 54, 1 55-65.
Kristensen, E.S. & Halberg, N. 1997. A systems approach for assessing sustainability in livestockfarms. EAAP Publication no. 89. 16-29.
Lockeretz, W. & Boehncke, E. 1999. Agricultural systems research. Proc. Second NAHWOAWorkshop.
Mogensen, L. & Kristensen, T. 2000. Organic milk production in Denmark by using private farmsfor research. EAAP Publication no. 97. 96-101.
Nielsen, A. & Christensen, J.O. 2001.
Noe, E. 1997. Values and farming practices among Danish dairy farmers.
Srensen, J.T. & Kristensen, E.S. 1992. Systemic Modelling: A Research Methodology in Live-stock Farming. In: Global Appraisal of Livestock Farming Systems and Study on TheirOrganisational Levels: Concepts, Methodology and Results. CEC-Proceedings (in press).45-57.
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Srensen, J.T. & Blom, J.Y. & stergaard, V. 1985. Systematic management programme for calfrearing Development and analysis (In Danish). Beret. 583 Statens Husdyrbrugsforsg,Kbenhavn. 171 pp.