Technology development and adoption rates

Technology development and adoptkm rates

Systems approach for agricultural research and extension Thefailuretocany~tothepointoffinalapplicationunderfarm coditionsprobablyexplainsfarmoreaboutnon-acxqtawoftechnologicalchangethananyothersinglefactor.~

Per Ekhmd

This article sets out the case for national agricultural research and extension structures that emphasize on-farm research with a systems approach. Technology discovery by formal research is widely regarded as the key engine of growth in agriculture. Promotion of technical progress is a central component of most agricultural development plans. But adoption of new technology in peasant agriculture is below expectations. This reflects a specification bias in technology prescription: prescriptions are often not properly designed for the agroclimatic and socioeconomic conditions of the regions where they are to be used. Design of research and extension structures need to be reappraised and conceptualized so as to better support technology development and complement farmers’ experimentation capacity. Adaptive research for the transformation of peasant agriculture needs to be moved into environments of assured relevance and predictive ability from the farmers’ point of view. Keywords: Agricultural reseerch; On- Allocative efficiency of investment in research, extension and support fatm research; Developing countries services would then improve.

Adoptlonofnewtechnologyln peasant agrkulture mmaina lower than expectd. FalIurs to achkve expwtedletumsiras8oc~ more wfth inaMkbwk in the conductof~thnwlth external and economicfactors such as price sbucture or lack of agricumIral support sewices. This article sets out the case for national agricuttural wearch and extension structures that emphasize on-farm research with a sY-ms--

The author may ba contacted at The Ministry of Agriculture and Water The farmer’s innovation process Development, Lusaka, Zambia (mail address cl0 Swedii Embassy, PO The farmer’s own capacity and resources for innovation remain the key factor in technological change. Adaptation and experimentation are Box 30788, Lusaka, Zambia).

‘John W. MeNof, 7% Ecmmics of Agricawiell, 1966.

cuftum/ uevebpment,

%[email protected], ‘Sources of innovation in agiadtur8l techndogy’, 1991.

WOM

Dew,

0309-9192/93/020141-13$3.00

vol9,

forced on the farmer by continuous changes in his environment.2 These influence both genetic characteristics of plants and methods of cultivation. Genetic combination and mutation is influenced and conditioned by environmental stress, for instance, by variations in solar energy, rainfall and temperature. Shifts in cultivation methods are caused, for instance, by salinity and erosion of soils. Farmers purposively select plant materials and techniques which possess favourable characteristics in terms of yields and complementarity to the present cropping pattern.

0 1993 Buttelworth 8 co (Publishers) Ltd

141

Technology development and adoption rates

Solutions are generated through trials and adaptation efforts. Proven innovations are &&ioned by the farmers’ value systems and resource constraints, soils, climate, diseases as well as socioeconomic. Farmers are income-seeking risk averters, sensitive to variations in their environment, reasonably efficient in resource management, but have limited capacity for tzp~rimentation.~ Technologies will be adopted that promise significant increases in profits at acceptable levels of risk, even though cultural factors may momentarily delay their acceptance. Farming systems, often highly diversified in terms of number of crops and production patterns, animal and non-farm activities practised, reflect rational behaviour of farmers and minimized exposure to risk. For instance, Hausa farmers in the north of Nigeria select crops, varieties, planting and interplanting dates in a complex sequential probabilitybased decision process fitting their decisions with soil types and the actual date and amount of rainfall: agronomic practices are adapted every year to actual and expected environmental conditions.4 The subsistence farmers’ managerial strategy manifests itself as a sequence of adaptive choices as the season progresses, which reflect a gradually reduced uncertainty as to obtaining basic food self-sufficiency.5 In a sample of 30 households in an Indian village, 60 different systems of intercropping and patch cropping were found; this indicates an extraordinarily fine adaptation to minor soil and weather conditions.6 The drawback of the informal system is that the scope for innovation is constrained. Farmers’ experimental efforts become ineffective or time consuming where simple observation is inadequate, and where basic technical knowledge is not available about effects of different fertilizer elements on plant growth, and where scientific skills and laboratory techniques are required, as in analysing micronutrient deficiencies in soils. A limited pool of seeds and genes in the local environment, unsystematic ad hoc transfer of technology, and limited knowledge and resources for experimentation permeate low productivity in traditional farming. 7

The formal research system

3Donald L. Winkelmann, paper presented at the World Food Conference, Iowa State University,June 1976. Ti. Mead and Janet Riley, ‘A review of !3tatisticaiideas relevant to intercmpping research’, J.R. Statistica/ society, Pari 4, 1961;qXnmentbyR.W.PahnerJones. XJean Claude Baket, A&p&w of New Fatm Technc&gy by SuFatmers in Northern Nigeria, World Bank Seminar

Paper, January 1962. 6HansP. BhwqerandJemesG. Ftyen, ‘Efficiency and equity in ex +I& ahetion of research reewces’, Indian JouM of Agricultural Econcmics, Vol32, Nc 3, Jutyseptember 1977. ‘Biggs and Clay, op cit. Rei 2.

The formal research and diffusion system, created to offset the weaknesses of the informal system, is not adequate. The formal system is represented by the international centres, and national institutions for agricultural research and extension. New seeds and associated material inputs, and skills represent the dynamic force in the formal system. The genetic principle underlying hybridization has been a dominant force in producing the new seed varieties. The knowledge of established scientific theories and principles pertaining to plants, animals, soils and mechanics have been combined to produce associated material inputs. Most of the research connected with the generation of the modem varieties (MVs) of wheat and rice has been conducted at experiment stations of the international centres. Efficient plant engineering technologies were developed under controlled conditions. The research focused on particular commodities and the results were spectacular for the MVs of rice and wheat developed at IRRI and CIMMYT, respectively. More than a third of the area in developing countries under these two cereals has been sown with these varieties. The production effects have been substantial: the rice MVs typically yield up to 40% or more, and the yield of the wheat MVs may even be greater. The internal rates of FooDPoLcYMey1983

Technology development and adoptionrates

return to investment in the MVs frequently exceed 40%) and seem to be two to three times higher than those investments in other sect~rs.~ These high returns possibly suggest too little investment in research in the past. A caveat is necessary: returns to research would be artificially high, if national costs of producing researcher skills have been underestimated. But in the case of rice research, it has been shown that the economic justification for expanded programmes would remain even with a fourfold increase in costs of national programmes.9 Much of the investment in research during the l%os and the 1970s has been efficient, but a modified investment and institution building strategy with more emphasis on national systems for on-farm and farming systems research is now desirable. A report on farming systems research had already recommended such a shift in 1978.l’J There are three principal reasons for this reorientation towards national systems for research and extension. First, MVs that have already been developed have turned out to be less stable than expected. Productivity in research in the international centres has been reduced by the susceptibility of the MVs to local diseases. Second, the &option of the MVs has been lower in regions with agroclimatic conditions that differ from those for which the CIMMYT and IRRI varieties were developed. For these regions, it has been necessary to develop even newer varieties suited to different environmental World Bank AgriculturalResearch Sector conditions. Rates of return are lower for additional genetic crosses or Policy Paper, June 1981. 9R.E. Evmwn d P.M. m, ‘~1 filial varieties of the early MVs. 11Third, concurrently, the effectiveness returns to rice research’, in ~conomti of much of the investment in national agricultural research and extension CCnSwUenCSS

Of the &W

he

n3Ch-

systems

has begun

to &

&bated.

12

nology, IRRI, 1978. Technology prescription from station research is often not suitable and ‘OFarmingSystems Research at the International Agricultural Research Centers, as a consequence adoption of new technology by farmers has been lower CGIAR Technical Advisory Committee t h an expected. *J Low adoption rates reflect risk and uncertainty percep (TAC), World Bank, September 1976. ~~Roberl E. Evenson, ‘Comparative tions of farmers, and expectations with regard to availability of extension, evidence on returns to investment in physical inputs, credit, marketing services and prices. References in the

national and itiematil

research iNt&

d evelopment

literature

to differences in the economic environment, size, factor and product markets and their are common. But low adoption rates also in the formal systems for production and UtiliZdiOII of knowledge. References in the literature to the hlpOl?tUlCe of structural non-economic factors in technology prescriptions are less common. 14A large portion of research results in national centres is either not relevant or not complete. l5 Formal systems for research-extensionadoption are not producing relevant technology because of specification bias in technology prescription; and, technology development is not emphasized in system design.

tions’, in Resource A&cation and by tenure, farm Pmductivity in National and International represented Agricultural Research, University of effects on adoption behaviour Minnesota, Minneapolis,1977. reflect structural deficiencies ‘*For instance, see Peter Oram and Vihna

Bind&h, ~~~~~~ ~~a~~

b Na&&

Research; Trends in rhe 797Os, ISNAWIFPRI, WashinQton, DC, November 1981; and John W. Melbr ‘Commentary: the food policy research agenda and the CGIAR system’, lFPR/ Report, Vol4, No 3,lQ62. ‘aDonald L. Winkelmann and Edgardc

Agriculturel

Mowdi, ‘Amingaghhd

m

of

the

needs of -farine&, Devebprnerlt digest, 1981; see also BinswanQerand Ryan, op cif, Ref 6. %xceptbns can be found, for instance: Mellor, op tit, Ref 1; Per PinstnqAndersen, AgricuHural Research and DSR, Economic - Develqunent, Cooenhaoen. 197% and S~~MU Ishikawa, Agk&&i beve~t krategies in Asia: Case studies of the Philippines and Thailand, Asii DevebpmentBank, 1970; Robert Chambers, ‘A lesson for rural devekxws: the small farmer is a profe&bnal’, DevelqpmentDigest, 1981. lsWilliam K. Gamble, communication in seminar at World Bank, 16 October 1981.

FOODPOLICY

May1963

Specification bias in technology prescription Specification bias limits the effectiveness of research directed at raising productivity in peasant agriculture. It arises from: an improper methodology for experimental research design with limited focus on representative farming systems; and, location specificity of technology. Experimental methodology Experimental methodology contains flaws. Prescriptions are too often based on yield maximization, do not sufficiently consider stability and profitability of outcomes, and are too complex. Traditional experimental 143

Technology development and pdoprion rates

16Anderson, Dillon and Hafdaker, Agriculfwai Da&ion Analysis, Iowa State UniversityPress, Ames, IA, 1977. *Mead and Riley, op tit, Ref 4. lsRandoiph Barker and Robert W. Herdt, Rainkd Lowland Rica as a Raswch Priodv: An ESs View, IRRI ResearchPaperNo16,Mamh1979. %alcet. op tit, Ref 5. *O/bid.

*IRiley and Mead, op tit, Ref 4; and Jerry L. Mclntosh and Suruvatna Effendi. Indonesian Farming and Development,

Sykms Rasaarch AAM% Bogor,

J-~september1961. **Riley and Mead, op tit, Ret 4.

methodology is addressed to estimating average effects and responses and is directly applicable to only risk indifferent producers.16 Small farmers in traditional agriculture typically are averse to risk, but plant breeders have been inclined to ignore results obtained in low yielding environments or in drought years. The presumption that yields then are too low and not useful for sorting out the differences between selections is a serious error: high yielding selections under favourable conditions may show relatively greater failue under adverse conditions.17 Yield maximization is appropriate for irrigated but less so for rainfed agriculture. Breeders until recently had not emphasized the genetic characteristics required to generate a yield-stabilizng and cost reducing technology for rainfed environments. l* The farming system as a whole has not generally been emphasized in research although new technology must be implemented in the context of farmers’ particular systems. Prescribed technology too often is based on experiment station research which focuses mostly on single commodities and technology components and is conducted under sheltered or optimal conditions. Experimental conditions differ often fundamentally from those of representative median farmers: such farmers are small rather than large and they manage a complex farming system. Evidence from Nigeria indicates that adoption of fixed packages was limited to the relatively few large farmers or those that use sole cropping.lq Prescriptions are more readily acceptable if they are divisible with regard to timing and intensity of application. The farmer can then undertake the sequential adjustments which match his need of flexibility.20 Intercropping is the most common system but little work in tropical agricultural research concentrates on developing recommendations for intercropping, and the experimental methodology for this research can be improved. Intercropping is commonly practised in Africa, India and South and Central America. Agroclimatic conditions vary widely and many intercrop combinations are used. Mixed crops provide a longer cropping season than sole crops and the soil is protected from sun, rain and weeds. Attention to the interdependencies between soils, varieties and management practices may generate important benefits from moisture and nutrient conservation, and from pest and weed reduction. Comparisons with sole cropping have shown yield advantages for many mixtures, eg beans and maize, millet and sorghum, potato and barley, and sugarcane, and maize, and corn, upland rice and cassava.zl The persistence of traditional cropping systems which indicate yield advantages of mixed crops imply that improved intercropping research will benefit small farmers. A recent assessment of experimental design methodology in current intercropping research detected two flaws or biases in such research. First, over 90% of surveyed experiments had a single treatment structure with one or two treatment factors. Findings contrast with statistical experiment design theory, which predicts that experiments with more than one factor are more efficient. Second, there seems to be a strong tendency to continue asking whether mixed cropping is better than sole cropping, at the expense of investigating agronomic problems of intercropping. More advantageous would be to first survey farmers’ practices and to base intercropping research designs on the most frequent combinations rather than replicate long years of farmers’ experience.22 Socioeconomic evaluation of the farmers’ entire production system is

FcKmPoLlcYMmy1983

Technology development and adoption rates

still rare. Technology components must be integrated into a farm plan that considers the multiple demand on the farmers’ owned resources and his overall constraints. For instance, seasonal variations in the availability of inputs, labour, credit and storage may raise the farmer’s exposure to production risk and reduce adoption. Simple integrating procedures are not widely applied in farming systems research perhaps because they have not been actively promoted and were not required when research was conducted on single commodities.23 Recommendations for technology components that have not been tested within a systems framework commonly require far reaching and complex interventions in management and learning of farmers. Profitability calculations on single components, in the absence of integration and testing under farmers’ circumstances, is of limited value as a guide for future adoption. Location specificity of technology Agricultural technology is more location specific than suggested by the early successes of the rice and wheat MVs. The case for location specific on-farm research is supported by a CIMMYT study of adoption rates of maize and wheat. *4The study indicates that productivity factors reflected in agroclimatic and topographic variations, are the most consistent factors in explaining adoption behaviour: differences in adoption were explained only to a limited extent by economic factors. This means that excessive emphasis is easily placed on the importance solely of prices as predictor of supply response. Most experimental results with regard to cultivars and management methods are location specific. Their extrapolation to other sites requires testing in a number of representative sites with regard to soils, climate and management systems. Most agronomic experiments contribute little to findings that can be generalized because of the lack of representative site (soil) crop, weather and management data. With soils, it has been pointed out that an enormous number of field experiments involving fertilizers have been conducted throughout the world: these results usually apply only to the exact crop or environment in which the experiment was done and therefore provide little guidance as to how the crop would respond at other sites. *5Understandably, when such recommendations are uniformly propagated by extension systems without verification trials and modification for location specific variations, adoption cannot but be below expectations.

Technology development in system design

23Suruyatna Effendi, ‘Rainfed farming systems fisld laboratory’, mimso, AARD, Bogor, Itxbnesii. October 1982. *dWinketmann,op tit, Ref 3. “Sewn M. Miranda, ‘Land resows inventorbs in relation to farming systems research’, Paper presded at ths Asian ConferenceonAMadtudMsearchfor

Development:

-andchellenges,

IFARD/ISNAR. October 1982. 26J.K. t&De&&t, ‘Thetechdogyof technologicalinnovatiad, Paper pmsentd at Kwwtedge Utilii conference, East-WestCsnter, Homlulu, April 1982.

FooDFoLK2Ymyl983

Technology development for peasant agriculture requires an institutional structure that reflects properly the nature of the innovation process. Scientific research abstracts - it is directed towards single disciplines or type of crop or animal - whereas technology generation synthesizes. The latter is directed to combine knowledge to produce, for instance, a new seed variety, a new herbicide or a new farming system. The innovation process comprises scientific research, development, testing, adaptation, integration, diffusion and common practice. Development through integration represents the core of technology generation.f6 The integration function is initiated much earlier than the sequencing of the process suggests and it represents a continuous interaction with producers. It is closely associated with on-farm adaptive agronomic production research and knowledge of typical site characteristics. It necessitates a two-way 145

Technology development and adoption rates

27Y. Hayami and V.W. Ruttan, Agricultural An

Development: Perspective,

International

Johns Hopkins University Press, Baltimore, 1971; Y. Hayami and Akoko, ‘Organization and pmductMi of agricultural research systems in Japan’, Paper presented at the Conference on Resource Allocation and Productivii in International Agricultural Research, Aitlie House, Virginia, January 1975; V.W. Ruttan, Agricultural Research Policy, Universityof MinnesotaPress, Mineapolis, 1982 28Ardila, Trfgo and Pineiro, Human Resources

and

Agricultural

Research,

IICA, Costa Rica, September-December 1980, referred to in Oram and Bindlish,op cir, Ref 12. 290ram and Bindlish,op tit, Ref 12. 3oEvenson,op tit, Ref 11. S’Evensonand Fiores, op cit. Ref 9.

146

communication between researchers, extension specialists with knowledge of site characteristics and farmers. It represents experimentation farmers do in response to, or as a reaction to what professional researchers and extension specialists do or suggest, following their observation, analysis and interpretation of outcomes.27 The integration function is weak or not developed in most formal systems for the production and utilization of knowledge. Research generation and communications systems are centrally directed, of a command type, linear and sequential in nature and not related to the preferences and circumstances of representative users. Feedback from users is rare or ad hoc. Research becomes a succession of independent activities in the absence of a structured and directed innovation process. The knowledge for an improved production technology is not built up systematically. A recent study from South America supports the notion that professional research staff in general is not used effectively.28 The problem is widespread. An increasing number of developing countries have reached a stage in the evolution of their agricultural research system, where main constraints on their impact is not lack of money, buildings, equipment or absolute lack of trained researchers so much as in management of those resources. 29 Extension systems remain of limited use without research systems that generate relevant technology on a continuous basis. Several studies indicate that countries without an indigenous research capability have benefitted little from research in other countries.30 The proposition that technology is easily transferred only through extension activities has not been verified. Extension programmes in general do not produce much new technology, although they reduce the farmer’s costs for search and acquisition of information. 3l Innovations that originate with the farmers or within the extension system would lead to raised technical efficiency, to improved choice along a continuum of alternatives, eg to time and method of planting, seed bed preparation, fertilizer dosage, etc. Such improvements are associated with managerial choice, represent shorter term opportunities and are likely to generate only incremental productivity gains. Innovations that originate with researchers and technologists on the other hand would lead to shifts in production possibility sets, to choice of a new variety and intercropping, transition from manual to animal draught power, etc. Such shifts are associated with entrepreneurial choice, represent longer term research opportunities and may generate quantum productivity gains. Formal systems favour monocrop cultures and risk indifferent producers with sufficient resources for testing and experimentation. Formal systems have generated productivity gains for sole crops such as irrigated rice, where the need for adaptation by farmers is limited and for established cash or industrial crops, where producers possess sufficient knowledge and resources for experimentation. Formal systems presently are not appropriate for the vast majority of smaller farmers. Productivity of research and extension systems in these environments necessitate a developed integration function, an emphasis on on-farm research.

On-farm adaptive research Adaptive

agronomic

production

oriented

research

under

farmers’

FOOD POLICY May 1983

Technology development and adoption rates

3zWinkelmann,op cif, Fief3. %arker and Herdt, op cf?,Fief 16. 34R.K. Perrin, D.L. Wtnkeknann, E.R. Moscardi, I.R. Andersn, FmmAgmwnic Data to Farmer Recwmendatkms, CIMMYT, Information Bulletin 27, 1976. Discussionswith Paul Marko, Workf Bank, have been insbumentalfor my w&&anding of the CIMMYT expedenw withon-farm studies.

FooDKnKzYMay1983

circumstances, with an improved experimental methodology, would reduce specification bias in technology prescription and raise adoption rates. Extension seems to have only a slight relationship to adoption in circumstances when technology specification bias is significant. The CIMMYT study referred to above supports such a conclusion.32 Better technology prescription would improve the efficiency of investment in extension, as well as in associated inputs. The gap in knowledge and skills which must be bridged by extension advice and the farmers’ own experimentation then becomes smaller and manageable. Prescription, on the other hand, cannot be made specific to each and every farm to fit the large variation in farm agroclimatic and economic conditions. The farmer, even in the best of circumstances, will need to carry out the finer tuning of prescriptions through his own experimentation. With the extreme heterogeneity of environmental conditions, and the limited capacity of the research extension network, farmers must normally work out for themselves the most appropriate cropping pattems.33 The more binding are other constraints, represented for instance, by low, or in real terms, declining farm gate prices, the greater is the farmer’s need of more precise technology prescription. Better prescription represents a saving to farmers in terms of reduced own resources input into search, experimentation, testing and learning. Such resources input is not known to have been estimated, but it may be sizeable for typical median farmers. The farmers’ experimentation capacity needs to be far better understood and explored. In on-farm and farming systems research, base data analysis and onfarm studies complement both the farmer’s experimentation capacity and research station studies. Models for on-farm applied research have been developed, for instance, by CLAP, CIAT, CIMMYT, ICRISAT and IRRI. The CIMMYT model is relevant to our discussion and entails carefully selected interventions and support of the farmer’s informal innovation processes.34 Farmers to begin with, are classified through informal and formal surveys into agroclimatic zones with similar farming practices. Studies of the farmers’ present practices identify variables or ‘interventions’ that generate higher technical efficiency, better product characteristics or reduced risk. Such variables may be intercropping practices, cultivation methods and application of material inputs. The most promising variables, usually three or four, are selected for experimentation. Experimentation is carried out by the farmers over a three-year period. This system ensures that natural as well as socioeconomic constraints of the farmers condition recommendations for improved practices. A resident field team interacts with the farmers and monitors the experimentation. A typical team is composed of three production agronomists, of which one is an economist. It is supported by subject matter specialists and senior scientists at the experiment stations. Base data analysis aims at mapping agroclimatic zones, land and soil units and land use, ie farming and commodity systems. Information is generated about the homogeneity in agroclimatic conditions and the potential for improved technology in terms of technical efficiency (and/or desired product characteristics or reduced production risk). On-farm research conducted throughout the area where the crop is grown, should generate precise recommendations for improved technology. The goal is to derive a set of recommendations for successful improved practices for the particular zone or recommendation domain. Successful 147

Technology development and adoption rates

prescriptions should yield at least 40% rate of return per production cycle. This relatively high opportunity cost of capital would ensure a widespread adoption, and also guarantee sufficient social pay-off on the initial development cost. Successful recommendations should be tested through multilocational or large scale try-out at which point infrastructural and institutional constraints, for instance in extension, seeds, other input supply, credit and marketing are identified. The benefits of agronomic production and cropping systems research will be the higher, the larger and the more homogeneous is the recommendation domain, and the greater is the gap in yields between current and improved practices. Base data which contain such ex ante information, combined with costs of applied on-farm studies, determine the number and locations of benchmark testing sites. Information for each zone about technology gaps, or economic slack is vital for efficient resource allocation. Investment in extension and agricultural development programmes needs to be concentrated in zones which possess greatest potential for raised value added. But investments seem often to occur without satisfactory knowledge or consideration of the variations in regional growth potential.35 Evidence from India suggests that extension investment, at least in past years, has tended to be concentrated in areas which are relatively privileged in terms of use of efficient technology, and high investment levels.36 When the technology gap or economic slack is insignificant, there is little if any content message to extend to the farmer. Evidence is becoming increasingly available that investments in extension may have preceded the generation of appropriate technology from the national research systems in many countries. Evidence from Northern Nigeria also suggests an improper sequencing of investment in research and extension.37 For Thailand, it is reported that availability of extension services for farms using chemical inputs even has had mostly negative effects on profits.38 In short, investment in extension systems becomes less efficient both when the technology gap for representative farmers becomes too wide to bridge, and when the gap is narrow or negligible. The complementarities between location specific research and investment in extension systems warrant close attention. Alternative institutional arrangements for the management and organization of technology development within research and extension need to be explored to ensure an improved sequencing and higher productivity of investment. 350ngoing World Sank maearch may Preconditions for technology development generatemore knowbdge in this area; a& Surjit S. Shalla, Agriculture lnnovatkmsin The distinction between scientific research and technology development India - A District and Fam, Level Analysis has not been sufficiently emphasized. Guidance and responsibilities for of Fertilizer Use and HW Adoption, technology development within research and extension organizations Reaearch Pmmaai. March 1980; see alao have been left vague and undefined. Preconditions for technology Gershon Fe&r a&f Roger S&e, The Impact of Agricuftutal Extension:A Case development need to be explored, and it is important that clearly stated Study of the Training and Visit Methal in government priorities for type of agricultural development strategy are Haryana, India, Research f-P=4 pursued; the innovation process is institutionalized within research and January 1981. 36R.E. Evenaon and Y. Kialev,Agricu~?uralextension; there is improved skill formation in universities. Research and Pmductivity,Yale University Press, 1971. National priorities J%alcet, op tit, Fief5. 38Dean T. Jan&on and Lawrence T. Lau, Management of technology development requires clearly stated Farmer Education and Farm Efficiency, government objectives for type of agricultural development and regional World Bank/Johns Hopkins University food security strategy to be pursued. In the absence of government Press, Baftimore, 1982.

148

FooDPoLtcYMay1983

Technology development and adoption rates

39Barkerand Her&, op tit, Ref 18.

directives, formal systems of research and extension, by design or default, will remain biased in favour of irrigated agriculture and larger farmers with adequate resources and skills for undertaking experimentation and testing. The translation of government objectives into operational programmes requires that potential benefits, costs and risks be better explored before investments in research and technology development are initiated. Socioeconomic criteria for resource allocations in research are not well-developed, but they can be extended beyond simple congruence analysis, ie a test whether resource allocation in research ex-post conforms to the distribution of area or value added by major crop. More meaningful studies of the potential benefits of research investment and feasibility of alternative strategies for research investment can be undertaken. At IRRI, potential benefits were studied of reasonable research inputs directed at rainfed and irrigated rice in Asia.39 The point of departure for this study was that modem rice technology to a large degree has bypassed the rainfed areas. Over the past decade, there has been substantially heavier investment in rice research and development for irrigated than for rainfed areas (Table 1). In part, this may reflect that IRRI’s research orientation in the past has been of greater benefit to countries with a high proportion of irrigated area. The IRRI researchers suggested that Asian governments are likely to emphasize irrigation as a fairly sure, but costly means of increasing rice production and achieving price and political stability. If their estimates of the potential yield increase in rainfed rice are correct, the total benefits for the Asian economies may be greater, if more emphasis is put on research on rainfed technology. Productivity of recommendations from on-farm research for rainfed agriculture appears to compare favourably with returns to commodity research in national systems. Emerging agronomic production research with a farming systems approach and available local or improved varieties, is encouraging and suggests that benefits of such research can be sizeable. Results, for instance, from Indonesia for upland areas attest to the advantages and adoption, for instance of row planting in combination with fertilizers, compared to the traditional practice of random planting, and of growing combinations of crops rather than sole Tabki.blWSOWCh 1974.

expmdbmfofselecmdcounbiwInM,9outhmd~~

country Rainfed oriented, Southand So&-eaet Asia Bangladesh mnla Nepal Thailand vietnam lm’gationoriented,Southand So&-east Asie lndcmesia W. Malaysia Pakistan Philippines Philippines(includi~ IRRI) Ottrets India

Japan Note: aValued in 1971 U8 $. Source: Evensonend Fkms. op cir, Ref 9.

FoooFoLKtYMay1903

TaiwSUl SouthKorea

550 1460 210 500 2900

252.00 17.00 14.00 80.90

3900 46ooo 1700 250

1999.70 219.50 35.70

6.40

10.30

149

Technology

development

and adoption rates

cropping.40 Evidence from Indonesia also indicates that returns to plant breeding research on rainfed crops, for instance, for upland rice, corn and cassava are enhanced when such research is integrated with on-farm agronomic production research. Similar results are reported from Nigeria.41 Costs of on-farm research are sensitive to the time within which key variables selected for experimentation can be identified. Systematic comparisons of the costs and benefits of adaptive on-farm research are warranted. This need remains even though in the final analysis this research orientation is linked to wider concerns, to regional development, equity and food security. Institutionalizing

the innovation process

Research organizations: On-farm and farming systems methodologies have not yet been institutionalized: the complementarities to commodity research and extension within the innovation process need to be defined. Station research traditionally has been organized on a disciplinary basis, eg breeding, agronomy, plant protection, etc. Such research has begun to be reorganized into multidisciplinary commodity research teams, eg on rainfed rice, cereals, tubers, oilseed. Many countries, for instance, Indonesia and the Philippines and several countries in Eastern and Southern Africa such as Zambia are found in this group. The third step in this evolution entails defining the organizational and spatial framework for complementing commodity research with area specific on-farm research teams.4*

linkages: The complementarities between research and extension in technology development remain to be defined. Close interaction between on-farm research teams and extension organizations is necessary for the integration function to become operational but participation of the extension organization in technology development is rare. In Guatemala for instance, the agricultural research system was successfully changed towards a farming systems approach. Technology of proven relevance was generated for small farm systems. The impact of the system remained limited because the extension system was not incorporated or assigned a role in technology development.43 An excessive preoccupation in the design of extension organizations simply with diffusion or the extension agent function has led to neglect of the central integration function. The specialist function has been downplayed and been given far too little emphasis. On-farm adaptive research methodologies have as yet not been linked to, or institutionalized within extension systems. Within the on-farm and farming systems methodology, multilocational trials in the farmers’ fields follow the initial few trials to verify the replicability of selected recommendations. The case for extension with its knowledge of local site characteristics in undertaking these multilocational trials is strong. Researchers’ input would be required to ensure a proper experimental design and the multilocational trials ought to be planned jointly by research and extension, executed by extension, and analysed by research and extensi0n.M The decision on what to recommend to farmers should again be a joint one. Specialists from the extension system need to be seconded to the sites for the initial trials, to partake in, and learn from the design, execution and feed back from these trials. These specialists in turn ought to be responsible for executing and training other extension staff in undertaking multilocational trials. Research-extension

40Mclntoshami Effendi,op tit, Ref 21.

Walcet, op tit, Ref 5. 42For instance see, S.A. Kean and WM. Chibasa, ln.stitutfonelizing Farming Systems Research in Zambia, Research Branch, Department of Agriculture,Zambia, 1982. 43Guatemeia: Devebpment of the Institute of Agriculture/ Science end Technology (ETA) and its Impact on Agriculturel Research end Fam, PmductfHty, USAID, Washington, DC, February1992. 44Communicationwith Daniel Benor.

FoocBPoLlcvMlbyw83

Technology development and adoption rates

Skill formation in universities Technology

development

decidedly

will not come

about

without

improved skills in on-farm and farming systems research. The integration function requires skills which are scarce. Attempts to maximize the productivity of single technology components without considering system interactions, costs and risks will not generate efficient production improvements in line with producers’ preferences. Attention to the interdependencies between soils, varieties and management practices under the given physical and socioeconomic circumstances of representative producers requires interaction and skills different from those of typical commodity oriented research. In on-farm and farming systems research, activities are conducted by interdisciplinary teams rather than by representatives of single disciplines working in isolation. Biological and physical scientists interact, and skills in social and economic analysis are required in the identification of constraints and in proper experimental and treatment design. Analytical skills in experimental methodology and quantitative techniques of such researchers need to be considerable and may have to exceed those of commodity oriented scientists. Subject matter specialists in extension systems probably represent the most critical link in the research-technology development-diffusion chain. Skills of specialists are generally not commensurate with their central role. Skill requirements in on-farm and farming systems research are similar both for the initial few trials and for the multilocational trials which ideally should be conducted by the extension service. In reality, because of skill scarcities and logistical problems, multilocational trials will probably often be conducted and supervised by single specialists rather than by teams composed of diverse disciplines. In extension systems, subject matter specialists often have insufficient training and field experience even to perform regular training and technical backstopping for village extension workers. There is evidence that, in spite of significant training efforts, extension workers lack sufficient technical knowledge and appreciation of traditional farming systems.45 Systems research as described here does not generally fit the single disciplinary approach taught in colleges and universities, and there is reason to support on-farm applied and adaptive research by masters or other university programmes in farming systems.46 Informal training needs to be complemented by training to produce skills in on-farm and farming systems research. Formal graduate level training progmmmes to produce research integrators, qualified specialists for technology development are generally not available. Such programmes would provide advanced in-service training to specialists in research and extension and focus on the methodology of on-farm research under farmers’ circumsances. They would emphasize field application and integration between disciplines and natural and social scientists. Multidisciplinary masters programmes are being set up in Thailand; authorities in Indonesia and the Philippines have expressed interest in such programmes; and they have been recently proposed in Kenya. The positive association between university graduate programmes and agricultural productivity through more effective or relevant research and %alcet, on cif, Ref 5. extension has been documented for the USA.47 Masters programmes in 46Mclntoshand Effendi,op cif, Fief21. 4V.E. Evenson, The Cottrri~~ cf farming systems in regional universities in developing countries would Agriculfural Resesrch and Extension to provide an important measure of institutional support for the technology Agricultural Production, PhD Thesis, development function and provide professional recognition for adaptive Chicago, August 1968. FODDPOUCY

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research. With support from regional or local universities to regenerate analytical capacity, farming systems research programmes would not be viewed as mere training programmes for junior scientists and specialists, and promotion would not necessarily become equivalent with attaining positions in central research stations or in extension headquarters. Longterm viability for farming systems research and for a capacity for on-farm trials within research and extension system would be more certain.

Conclusion Adoption of new technology in peasant agriculture remains lower than expected. The failure to achieve expected returns from national research systems is associated more than previously perceived with insufficiencies in the conduct of research, than with external and economic factors such as the price structure and lack of agricultural support services. Formal systems for research and extension are not efficient in technology generation because of specification bias in technology prescription and because technology development is not emphasized in system design. Formal systems favour monocrop cultures and risk indifferent producers with sufficient resources for testing, experimentation and adaptation. They are biased against rainfed environments and thereby against the vast majority of smaller farmers. This bias will not be removed simply by putting more resources and skills into national systems. Low adoption rates are caused by a specification bias in the conduct of research. This bias is caused by improper methodology and location of research. First, experimental methodology is excessively focused on sole cropping and yield maximization rather than on representative or mixed cropping systems, and on improving stability of output. Second, prescribed technology is rarely verified across dominant variations in biological and socioeconomic circumstances of representative farmers. In these cases, technology and skill gaps arise, which can rarely be abridged through extension advice and with smaller farmers’ own resources for trial and experimentation. Specification bias in technology prescription has mostly been neglected and has not been given sufficient attention as a cause to low adoption rates. This is not to infer that specification bias is necessarily, or always the foremost adoption constraint. But the more binding are other constraints, represented, for instance, by declining or low farm gate prices, the greater is the farmer’s need for precise technology prescription from research. Improved technology prescription, verified through experimentation and testing under the conditions of representative farmers, represents a saving to farmers in terms of reduced own resources input into experimentation and testing. Neglect of the organization, management and location of technology development as a dominant cause to low adoption rates represents a basic flaw in system design and leads to improper policy prescription and resource allocation. Inadequate conceptualization of the innovation process has meant that the distinction between scientific research and technology development has not been emphasized. Scientific research is typically directed towards a single discipline or type of crop or animal and when carried to an extreme, or when activities are not focused and interlinked, research easily becomes irrelevant to the farmer’s needs. Scientists are trained and rewarded for abstracting, not for integrating. Integration comprises interaction with producers, and is associated with agronomic production research and technology development. 152

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Formal research organizations have rarely been given, or assumed responsibility for technology development. Nor have extension organizations been designed to direct technology development and execute adaptive research. The failure to create an institutional base for technology development has led to few verified recommendations and to premature and costly emphasis on diffusion systems and agricultural support services. 4a The necessity of on-farm and farming system research is being more widely recognized. The setting up of research stations in different locations is not sufficient: adaptive research must be moved into environments of assured relevance and predictive ability from the farmer’s point of view. Investment is desirable in small teams of researchers which, with an interdisciplinary approach, a minimum of equipment, and support from central facilities can interact with farmers in representative environments. Such ‘light structures’ would concentrate scarce resources on the foremost production constraints. The task of such teams would be: diagnostic research (benchmarks) of both socioeconomic and biological environments; agronomic production research; and, representative on-farm testing of genotypes and other technology components. Such networks would complement and make more effective biological-genetic and other research which because of critical mass and economies of scale is carried out in central or international institutions. Messages about actual production constraints in the field would be transmitted to research stations. Breeders can more easily shift their priorities from plant characteristics to environments. Productivity of research and extension systems, especially for rainfed agriculture, necessitates an integration of on-farm adaptive research with both commodity research and extension systems. On-farm and farming systems methodologies have not yet been institutionalized within research and extension systems. Assigned responsibilities between onfarm research teams, commodity researchers, and extension specialists is necessary in order to develop location specific recommendations for representative domains. Initial trials ought to be undertaken by on-farm research teams with support from regional and subregional research stations. Multilocational trials to verify the replicability of recommendations from the initial trials ought to be undertaken by extension organizations. With this model, multilocational trials would be planned jointly by research and extension, executed by extension and analysed by research and extension. Systems research as described here does not generally fit the single disciplinary approach taught in colleges and universities and there is reason to support on-farm applied and adaptive research by masters programmes in farming systems in regional universities. Attention in experimental design to the interdependencies between soils, varieties and management practices of representative producers requires skills different from those of traditional commodity-oriented researchers and of subject matter specialists in extension systems. Subject matter specialists probably represent the most critical and weak link in the entire research technology development chain: their skills are not commensurate with their central role. With support from regional or local universities to regenerate analytical capacity, long-term viability for farming systems research within research and extension systems would be @Evidence, for instance, fmm GU@nala, more certain. Raised adoption rates and productivity in peasant farming IncJia,NiiandThaiiatldsuppoHsthii would be more likely. COflClUSiOll.