Comparing rice production systems: A challenge for agronomic research and for the dissemination of knowledge-intensive farming practices

Agricultural Water Management 96 (2009) 1491–1501

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Agricultural Water Management journal homepage: www.elsevier.com/locate/agwat

Review

Comparing rice production systems: A challenge for agronomic research and for the dissemination of knowledge-intensive farming practices Willem A. Stoop a,*, Abdoulaye Adam b, Amir Kassam c a

STOOP Consult: R&D for Tropical Agriculture, Akkerweg 13A, 3972AA Driebergen-R., The Netherlands Statistical Capacity Building, Division Statistics, Department African Development Bank, Temporary Relocation Agency, BP 323, 1002 Tunis Belve´de`re, Tunisia c School of Agriculture, Policy and Development, The University of Reading, Earley Gate, Reading RG6 6AR, UK b

A R T I C L E I N F O

A B S T R A C T

Article history: Received 7 December 2008 Accepted 25 June 2009 Available online 30 July 2009

This article is a commentary on several research studies conducted on the prospects for aerobic rice production systems that aim at reducing the demand for irrigation water which in certain major rice producing areas of the world is becoming increasingly scarce. The research studies considered, as reported in published articles mainly under the aegis of the International Rice Research Institute (IRRI), have a narrow scope in that they test only 3 or 4 rice varieties under different soil moisture treatments obtained with controlled irrigation, but with other agronomic factors of production held as constant. Consequently, these studies do not permit an assessment of the interactions among agronomic factors that will be of critical significance to the performance of any production system. Varying the production factor of ‘‘water’’ will seriously affect also the levels of the other factors required to optimise the performance of a production system. The major weakness in the studies analysed in this article originates from not taking account of the interactions between experimental and non-experimental factors involved in the comparisons between different production systems. This applies to the experimental field design used for the research studies as well as to the subsequent statistical analyses of the results. The existence of such interactions is a serious complicating element that makes meaningful comparisons between different crop production systems difficult. Consequently, the data and conclusions drawn from such research readily become biased towards proposing standardised solutions for possible introduction to farmers through a linear technology transfer process. Yet, the variability and diversity encountered in the real-world farming environment demand more flexible solutions and approaches in the dissemination of knowledgeintensive production practices through ‘‘experiential learning’’ types of processes, such as those employed by farmer field schools. This article illustrates, based on expertise of the ‘system of rice intensification’ (SRI), that several costeffective and environment-friendly agronomic solutions to reduce the demand for irrigation water, other than the asserted need for the introduction of new cultivars, are feasible. Further, these agronomic solutions can offer immediate benefits of reduced water requirements and increased net returns that would be readily accessible to a wide range of rice producers, particularly the resource poor smallholders. ß 2009 Elsevier B.V. All rights reserved.

Keywords: Aerobic rice SRI Factorial experiments Interactions Experimental designs Extension Farmer field schools Water management

Contents 1. 2. 3.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Agronomic research in support of crop production systems for diverse agro-ecological conditions . . . . . . . . . . . Comparing rice production systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. The case of SRI: comparisons with other rice production systems. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Interactions between the technological components making up a production system: the issue of confounding between technological components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3. Agronomic field comparisons between production systems: the handling of non-experimental variables

* Corresponding author. Tel.: +31 343 516311; fax: +31 343 517126. E-mail address: [email protected] (W.A. Stoop). 0378-3774/$ – see front matter ß 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.agwat.2009.06.022

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Developing crop production systems for agronomic performance . . . . . . . . . . . . 4.1. Research into the components of production systems . . . . . . . . . . . . . . . . 4.2. Implications for conducting field experiments . . . . . . . . . . . . . . . . . . . . . . 4.3. Dissemination of knowledge-intensive production practices and systems Discussion and conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1. Introduction Over the past two decades international and national agricultural research has come under increased pressure from funding agencies and policy-makers to develop solutions to an array of complex agricultural and environmental problems. Among these problems are: the food security for the poor, and the sustainability of production systems in the face of rising cost of production, climate change, soil degradation and the various forms of environmental pollution. As a result, expectations of breakthroughs from research are raised and then reinforced by premature releases of research results and claims of achievements to the press and in popular newsletters and bulletins. Definitely, agronomic research that deals with multi-component crop production systems is conceptually and technically complex with respect to field experimental designs that would minimise the risk of reaching flawed or biased conclusions. However, because of the raised expectations and pressures to generate quick and spectacular results, some scientists appear increasingly tempted to overlook and/or bypass the experimental complexities involved. At the same time the need for basic agricultural research as a basis for subsequent applied research is often inadequately appreciated (see Lynch, 2007) by administrators and other stakeholders for reasons that are described by Van Mele (2008) as a lack of socio-technical and ecological literacy. This state of affairs leads applied research to generate and publish results in scientific journals that are too often of inadequate and inconclusive quality as elaborated in the present article. The current debates surrounding rice and certain novel rice production practices (e.g., aerobic rice system, or the system of rice intensification—SRI) are a point in case. Irrigated rice farming is generally viewed as an intensified, flooded production system that requires large quantities of increasingly scarce irrigation water. There are, however, also numerous smallholder rice producers in Asia and Africa who for generations have practiced various types of mainly rainfed rice production systems including aerobic upland rice systems. Against this background, an intensive debate has evolved in recent years among rice scientists on the potential merits of new rice production systems like SRI. As the preferred staple food for some 60% of the world’s population, rice represents huge economic and political interests which have increased even further due to recent price increases of major food staples on the world market, along with rising costs of fossil fuel. This article first elaborates on the relevance of agronomic research and the difficulties such research faces in addressing and meeting the needs of the heterogeneous rural farming communities (a majority being poor smallholders) that operate under diverse, variable and often unpredictable agro-ecological and socio-economic conditions. Next, it illustrates how the confounding of technical production factors in agronomic research, as well as the handling of non-experimental agronomic variables and their confounding with the former, readily leads to the generation of poor quality research data and to their misinterpretation. Consequently, agricultural production problems and issues are often oversimplified by those who conduct such research. This often leads to proposing standardised ‘‘silver bullet’’ or so-called ‘‘best bet’’ type solutions that bypass

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the bio-technical and socio-economic complexities associated with sustainable crop intensification and with sustainable farming in general. For instance, the analysis of yield gap and labour productivity in Africa made by Bindraban et al. (2008) argues for the ‘‘adoption of technologies on the shelf—following the strategies of the green revolution’’ in spite of their admission that African production systems are notoriously complex and diverse. Likewise, the assertions of a presumed potential of aerobic rice over other rice systems in several articles by IRRI scientists (Bouman et al., 2005, 2006, 2007; Nie et al., 2008) serve to illustrate the limited agronomic scope of that research as well as its short time horizons. As a result, the relevance of such type of research in addressing the important practical issues of long-term sustainability associated with rice farming could be questioned. Similarly, there have been several recently published critiques on SRI that were also based on short-term, simple assessments through incomplete field experiments in a single season (e.g., Sheehy et al., 2004), or on desk studies (e.g., Doberman, 2003; Sinclair and Cassman, 2004; McDonald et al., 2006) directed to support pre-conceived ideas about SRI. Subsequently, the scientific quality of the results and the credibility of the conclusions presented in these peer-reviewed papers were refuted by Stoop and Kassam (2005) and by Uphoff et al. (2008) on the grounds of serious methodological and empirical deficiencies. The shortcomings in the research work and assessments cited above have serious consequences for the relevance and quality of rice science as well as for investment decisions and future strategic directions of rice research. These concerns have led to this article in which various suggestions are elaborated for conducting more effective and innovative agronomic research whose results can be of increased relevance and value to the interests of large and small rice farmers alike, as well as to the scientific community and the society at large. The main aim of the article is to objectively highlight, in good faith, a set of concerns regarding production system research that could improve scientific rigueur and effectiveness. 2. Agronomic research in support of crop production systems for diverse agro-ecological conditions The view that much agronomic research is essentially locationspecific and thereby relevant mainly at the micro, farmer-field level is widespread among national and international agricultural scientists. Therefore, it is often considered to be an activity mostly involved in adaptive research through relatively simple, routine trials and tests on dates of planting, varietal choice, plant densities, and fertiliser and pesticide rates. Initially such trials were conducted mainly on experiment stations, but during the last two decades, they have been conducted increasingly on farmer fields through various forms of farmer participatory approaches. Yet, to capitalise on its analytical role, agronomic research should be considered as an integrative science that can clarify and explain the workings of the various biological, physical and chemical mechanisms in the crop production environment. These insights can then be exploited to increase crop yields and to optimise the associated factor productivities. The resulting knowledge and

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principles about the agro-ecological functioning of crop production processes subsequently contribute to the identification and development of new farming practices. It also provides a basis for the formulation of further agronomic research that could guide adaptation and improvements across diverse agro-ecological and socio-economic conditions. By contrast, plant breeding and genetics and various other specialisations such as plant nutrition and crop protection, being considered of a more fundamental nature, have always mustered considerably greater international significance, prestige and financial support from both public and private sources. Moreover, these disciplines have provided attractive links to the commercial sector through the sizeable markets for agricultural inputs (Ro¨ling and Jiggins, 2007). To achieve and maintain profitable market shares, production practices based on standardised and exogenous technological inputs of ‘‘improved’’ seeds, high input levels of agricultural chemicals and large-scale mechanisation (see IAC, 2004; Bindraban et al., 2008) then readily become the major elements of the so-called productive ‘‘modern’’ agriculture. As a result, the international and national agricultural research and development organisations, and the agricultural education and training institutions, tend to present this ‘‘industrialised’’ version of agriculture as the only modern option for meeting the food and agricultural needs of the growing world population, now and in the future. This form of agricultural development, in theory and in practice as well as the supporting scientific research, tends to overlook two important characteristics of the farming environment. First, the diversity and variability in agro-ecological and socio-economic conditions that are associated with farming in general, and with less favourable areas and smallholders in particular, is largely ignored. Thus, the interactions between the recommended technological components and the location-specific conditions of farming are not taken into account adequately. Consequently, the standardised ‘‘best bet’’ production technologies espoused by such an approach tend to be of limited relevance and value for many farmers because the recommended external inputs are often not attractive to them or become unattractive from economic and environmental perspectives. Second, the vast majority of farmers, certainly in most of the developing world, belong to the poor smallholder category, who cannot afford to buy expensive external inputs (assuming that these and the associated extension support would be available locally, which is often not the case). These two characteristics of the farming environment have been identified as the major technical reasons, among several others of a more political nature, for the limited impact of agricultural research on farming in most of sub-Saharan Africa (Stoop, 2002; Stoop and Hart, 2005). A similar feature has been highlighted for most rainfed farming in marginal areas of other continents, including Asia (Bouman et al., 2007). It follows that serving the interests of the large heterogeneous group of poor smallholder farmers in the developing world requires fundamentally different approaches to agronomic research, and the large scale adaptive dissemination of any new agronomic principles and practices. Instead of ignoring the relevance of the ‘‘diversity issue’’ for effective agricultural innovations and for the introduction and adaptation of new agronomic practices, research and development programmes need to take it into account and approach it in a flexible manner—certainly far more flexible than is currently the case for the major international interventions aimed at reducing rural poverty through increases in agricultural productivity and output of production systems. This flexibility particularly relates to understanding the agronomic research principles that must be respected when making experimental comparisons between production systems, as well as to understanding the role of the farmer in adapting and integrating any new principle and practice into the prevailing production system, or when replacing one production system with another.

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3. Comparing rice production systems In its efforts to present the case for a ‘‘modern’’ agriculture, formal research has attempted on several occasions in recent years to make comparisons between rice production systems. A driving concern in some of the comparisons has been to limit and to economise on the water requirement for irrigation, thus increasing water productivity, but also the productivity of labour and other external inputs. However, such comparisons are very complex to perform practically in the field (Stoop and Kassam, 2005), as well as theoretically through crop growth modelling and other desk studies (Uphoff et al., 2008). Both the modelling and field approaches deployed to compare rice production systems have relied on questionable theoretical assumptions and agronomic simplifications to overcome the lack of knowledge about some of the agro-ecological processes. Likewise the potentials of actual crop production systems, including the contributions of various interactions between production factors, as well as between these and the non-experimental variables inherent in the local conditions have received inadequate attention from scientists. In the case of crop growth models, most of these aim at simulating plant phenotypic expression and biological performance as a simple physical process bound by fixed growth cycle parameters of morphology and phenology. They are unable to take into account situations in which the quality of the growing environment changes as a result of the effects, positive or negative, of the production system itself. The crop growth models generally ignore the root systems as well as the biological aspects of the soil system and their combined role in the maintenance of soil and crop health as well as in crop photosynthesis and growth, development and biomass partitioning (see also Lynch, 2007). Moreover, many of the crop coefficients that drive crop models are derived from crop production systems that represent the status quo crop agronomy. Consequently, such crop growth models are unable to simulate crop performances for situations in which the crop agronomy and environmental quality in space and time differs fundamentally from that associated with the status quo crop agronomy. This issue is elaborated in the section below by comparing the performance of a rice crop grown under aerobic agronomy with that of flooded (anaerobic) rice produced under the ‘recommended’ modern agronomy. In addition to the difficulties involved in comparing the performance of fundamentally different rice production systems, there is the issue of the large diversity in farming conditions that is typical for smallholder situations. These two issues are extremely difficult to successfully reconcile with recommended standardised technological production packages of, for instance, the best management practices (BMP). Both these issues are elaborated in the next section by using the aerobic SRI rice production system as a contrasting illustration. 3.1. The case of SRI: comparisons with other rice production systems Over the recent years an intense debate has been going on among some scientists about the possible merits of the aerobic SRI system as compared with the recommended anaerobic (flooded) rice production systems. The SRI production concept has been defined on the basis of six major agronomic principles (the use of very young – some 10 days old – seedlings for transplanting; single transplant/hill; wide spacing of transplants; alternate wet-and-dry soil water regimes; regular weeding through a rotary hoe to also facilitate soil aeration, and liberal use of organic fertilisers). These principles were first described in detail by de Laulanie´ (1993), a Jesuit priest, who recognised that small rice farmers in Madagascar simply lacked the resources to invest in intensifying their rice cultivation practices through the recommended ‘modern’ techno-

2 rounds with rotary hoe; may use herbicides Mechanical or manual + herbicide

Combination of mechanical and manual; may use herbicide 3–4 rounds, with rotary hoe

Moist soil; intermittent wetting and drying 120

75–150

c

Balasubramanian et al. (2005). Stoop et al. (2002). Bouman et al. (2005). b

a

80–120 Aerobic rice methodsc

21

3

10  10 to 20  20; usually in rows 25  10 3–4 20–30 80–120 Conventional methodsb

4–16 25  25 to 50  50 1 8–12 5–10 SRI methodsb

Continuous flooding

Organic manures/compost + mineral fertilisers (need-based) Compost/manures + mineral fertilisers as supplement if needed and available Basal mineral fertilisers + N top-dressing Basal mineral fertilisers + N top-dressing Intermittent irrigation, saturated soil to 5 cm flooding Moist soil; intermittent wetting and drying 16–50 20  20 to 25  25 1–2 10–30 Integrated methodsa

15–21

Fertility management Water management Number of transplants/m2 Spacing of hills (cm) Number of transplants/ hill Age of seedlings (days) Seed requirement (kg/ha) Rice production system

logical package based on costly (and unavailable) external inputs and inadequate or non-existent extension support. Interestingly, de Laulanie´ paid little attention to the issue of genetically improved and input responsive modern varieties (the backbone of ‘‘modern’’ rice production and indeed of industrialised agriculture in general). Yet, by manipulating the other agronomic factors, including their interactions, he recorded spectacular yield increases for the local varieties. Tsujimoto et al. (2009) have recently reproduced and discussed this performance. In essence, SRI agronomy at the level of practice represents an ‘‘integrated’’ production system. Through integrated management of its various crop-soil-soil biota-water-nutrient-space-time components it seeks to capitalise on a number of basic agronomic principles aimed at optimising the above as well as below ground plant growth and development, and the performance of the crop as a whole. Through his approach, de Laulanie´ questioned the efficacy and relevance of some of the principles and practices of the modern agronomic package recommended for anaerobic irrigated or flooded rice production systems. Notably, these are the cultural practices associated with the optimum timing of transplanting and of plant density and spacing, as well as the need for continuous flooding. In particular, the latter creates in some situations an unhealthy environment for root growth (Yoshida, 1981) and the edaphic flora and fauna. The resulting negative effects on plant growth reflect the interferences with soil biological processes as well as root exudation that are known to affect above-ground plant growth. The micro-organisms affected include those responsible for soil organic matter transformation and mineralisation and thus for nutrient availability and storage. In Table 1 these cultural practices are illustrated as approximate ranges that permit comparisons with corresponding ones for recommended, fully irrigated, best management practices, and integrated crop management (ICM) practices. Several major obvious differences can be pinpointed. In their research, scientists critical of SRI, however, have not focused on these different technical components of the respective systems, but instead have attempted to make overall comparisons between the various multi-component systems (see: Balasubramanian et al., 2005; Sheehy et al., 2004; McDonald et al., 2006). An interesting additional case, also included in Table 1, is presented by the ‘‘aerobic rice system’’ as compared with the ‘‘irrigated flooded rice system’’ (Bouman et al., 2005, 2006, 2007). In recent years this ‘‘aerobic system’’ has been developed by IRRI in collaboration with scientists in China to reduce the requirements for increasingly scarce irrigation water. Driven by similar concerns, Senthilkumar et al. (2008) tested a modified rice cultivation system for Tamil Nadu (India) that used some of the SRI principles, notably water-saving irrigation based on an alternate wet-and-dry soil water regime, to improve water-use efficiency while maintaining production. To arrive at valid comparisons between rice production systems, as was attempted by the studies mentioned above, implicitly requires that the various technological components of each system and the interactions among them are fully known and can be adequately mastered in the field. Likewise, it assumes that the interactions between the respective components and the various location-specific environmental conditions, both bio-physical and socio-economic, can be fully controlled, which in practice is not a very realistic assumption. As our analysis in the next section will illustrate, such full control situation did not prevail for the research on aerobic rice reported by Bouman et al. (2005, 2006, 2007) or for the modified rice system reported by Senthilkumar et al. (2008), or for the published comparisons involving SRI as already cited above. The information presented in Table 1 illustrates the variations and differences for the major individual components in the respective production systems. When making formal comparisons

Weed management

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Table 1 Comparison between the major agronomic practices of rice production systems following Integrated (ICM), SRI, conventional irrigated and aerobic rice production methods.

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between these systems, it becomes impossible to pinpoint which component or combination of components has been responsible for the superiority of one system over the other. The following sections therefore will elaborate further on the origins of the biases from both bio-technical and socio-economic points of view that subsequently are introduced in the results of such comparisons as presented in many published materials. 3.2. Interactions between the technological components making up a production system: the issue of confounding between technological components A production system is made up of a set of multiple technological components that interact in space and time to determine the final outcome. These components range from land preparation, choice of variety, seed rate, plant spacing, date of seeding, water and nutrient management, soil cultivation, weed control and numerous other management interventions that are guided by location-specific conditions some of which are even of an ad hoc nature in response to unpredictable weather conditions. In optimising the crop growth conditions, not only a farmer, but also an agricultural scientist, will have to seek the optimum combination of the various components, including their adaptation to the local conditions. Given the multitude of factors/components entering into a production system this is an immense task which is further complicated by the fact that many technological components are interdependent and show positive or negative interactions, i.e., the response to one component depends in a statistically significant way on the management of another essential component of the system. The latter applies in particular to research which compares production systems that employ different soil water or irrigation treatments, and which in the case of rice may range from purely rainfed to an alternately wet-and-dry moisture regime, and to a flooded condition. A first consequence of different soil water regimes will be that (new) adapted varieties need to be identified to realise the full potential of a particular system. In addition the levels of many agronomic management variables (plant density, planting date, fertiliser regime, crop protection against weeds, insect pests and diseases) will also require adjustments to optimise the performance of a particular system. There are, however, also important interactions between agronomic management variables and environmental factors. Frequently, the latter are ignored by scientists in their formally published articles. For example, the research by Bouman et al. (2005) covered three years of field experiments comparing two rice production systems (fully irrigated anaerobic rice and aerobic rice) for their yields and water use in the Philippines during both the dry and wet seasons. The paper makes several critical omissions. First, only the rainfall and irrigation data for a single year (2001) are presented, while stating that the data for 2002 and 2003 were ‘‘quite comparable’’. In spite of this claim, the ‘‘leaf area index (LAI)’’ and ‘‘biomass’’ data presented respectively in Figures 4 and 5 of the paper show distinct differences between 2001 and those in 2002 and 2003. The reasons for this difference remain unexplained. Moreover, these figures do not show whether the recorded differences between the anaerobic flooded system and the aerobic system were statistically significant. Second, only a very limited number of varieties (three or four) of uncertain adaptation to the aerobic soil condition (see Section 4.1. below) were tested, while the levels for the other technological components of each production system (e.g., plant densities, fertiliser applications, notably nitrogen, their timing and rates, etc.) were maintained at fixed levels for all treatments. Yet, the optimum levels for many of these other agronomic components will likewise be dependent on the major treatment variable tested, namely, ‘‘soil water’’. This means that in the Bouman et al. (2005)

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experiments the various system components are confounded with the soil water regime component. While, admittedly, it is very difficult in practical implementation terms to overcome this problem through the field experimental approach chosen by Bouman et al. (2005), the implications and impact – and therefore the limitations – of the presented results should have been highlighted by the authors. Furthermore, no statistical analysis was (or could be) applied in Table 4 of Bouman et al. (2005) to show to what extent the differences between ‘‘systems’’ and between ‘‘years’’, as well as the interaction between ‘‘systems  years’’ are significant. The statistical analysis performed refers only to the differences between the four varieties that were tested, and this was done without taking into account the possible ‘‘variety  system’’ and ‘‘variety  year’’ interactions, all of which could be highly relevant. A subsequent article by Bouman et al. (2006) on aerobic rice experiments conducted in China shows very similar shortcomings. Here, just three rice varieties were compared over two seasons and at five soil moisture regimes. While extensive data are reported for weather and climatic, soil and crop parameters, the statistical analysis and presentation of the crop data is incomplete and nontransparent because the interaction effects between varieties and soil moisture regimes are not presented explicitly (see Tables 7 and 8 of Bouman et al., 2006) or analysed in any detail. The final conclusion of the paper that proper irrigation management around flowering can contribute to maintaining high harvest indices and grain yields is hardly new, as this has been reported in major crop physiology handbooks and irrigation bulletins for many years (e.g., Doorenbos and Kassam, 1979), and is now explained by molecular physiology (Kim et al., 2009). 3.3. Agronomic field comparisons between production systems: the handling of non-experimental variables It follows from the preceding section that field experimentation with crop production systems is complicated by the many factors that together constitute a production system. It is simply impossible to accommodate systematically all factors – not even all those of major importance – into a single field experiment. Consequently, it is standard practice in agronomic research to maintain most factors as constants. Moreover, there is always a wide range of location-specific factors, such as weather and soil conditions but also farming experience and professionalism that will affect the outcome of field experiments and tests. It should not be overlooked that all of these so-called non-experimental factors should be kept in mind when interpreting and/or evaluating experimental data. In their research Bouman et al. (2005, 2006) used ‘standardised cultural practices’ without adequately considering whether these are appropriate (adapted) to the respective systems. Because of the inherent confounding of experimental variables (i.e., two different soil water regimes) with non-experimental variables (e.g., plant density; fertiliser regime, etc.) that has occurred in these experiments, the interpretation of the results easily becomes biased. Firstly, the experiments covered only a limited time span of three years so that the impact of major non-experimental factors, such as variations in the annual weather conditions notably in rainfall distribution cannot be assessed adequately (see also the remarks under Section 3.2 above concerning the Bouman et al. (2005) experiments). Secondly, important crop management factors like plant density as well as the rates and timing of mineral fertiliser applications were treated as non-experimental variables. The implications become obvious when it is realised that both the flooded anaerobic rice system and the aerobic rice system used the same high plant density (a spacing of 25 cm  10 cm with three plants/hill, corresponding to 120 plants/m2). By comparison,

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a spacing of 30 cm  30 cm with a single plant/hill, commonly used in SRI, corresponds to a plant population of only 11 plants/m2 which is roughly 10 times less. Such large difference in spacing and plant population is likely to have profound effects on watersavings and on increased drought tolerance, which undoubtedly contributed to the increased grain yields that were reported for SRI (e.g., Prasad, 2006; Sato and Uphoff, 2007). Under conditions of high plant densities, which is a standard recommended practice for most modern wetland anaerobic rice production systems promoted by IRRI and most national programmes, an aerated rice system is likely to yield less (both in grain and biomass) than the fully irrigated system, and this feature will probably be recorded irrespective of the variety used. However, the high plant densities as used in the Bouman et al. (2005, 2006) experiments will affect the degree of competition between individual plants for available supplies of soil water and soil nutrients below the ground and for radiation above the ground to the detriment of the aerobic rice system. This feature is confirmed by the results shown in Figures 4 and 5, as well as Table 4 of the Bouman et al. (2005) article. However, a more comprehensive and innovative agronomic study would have revealed that adjustments in plant densities and in other practices such as the timing and optimum application rates of fertilisers, nitrogen in particular, or the partial substitution of mineral fertiliser by organic forms of fertiliser, could have counteracted this reduction in grain yields and total biomass. Yet, because all these variables in the Bouman et al. (2005, 2006) experiments were confounded with the systems/ water regime variable, the case for profitable aerobic or aerated rice systems and its long-term sustainability cannot be made convincingly. Likewise, Senthilkumar et al. (2008), while demonstrating that rice production could be maintained under greatly reduced (40–50%) rates of irrigation water, ignored the critical effect of a ‘‘G  E’’ interaction by conducting their experiments with only a single rice variety. Very similar misconceptions have conditioned the earlier studies by Sheehy et al. (2004) and McDonald et al. (2006) in their respective efforts to compare the aerated or aerobic ‘‘system of rice intensification (SRI)’’ with the recommended, anaerobic, fully irrigated system of ‘‘best management practices’’. 4. Developing crop production systems for agronomic performance In view of the experimental shortcomings explained in the previous section about the validity and relevance of the comparisons between different rice production systems, what possible alternatives can be considered? First of all, this would require a systematic recognition of all major (socio-)technological factors that affect the long-term productivity and sustainability of a production system. Performing such comprehensive field comparisons between production systems will admittedly be a daunting task. A crop production system is composed of many technological components and each component needs to be implemented on time and correctly to achieve a valid comparison. Also, any crop production system is an integral part of a larger cropping or farming system, involving rotational effects of preceding crops, including those of past and current soil tillage and crop residue management practices, as well as the interactions resulting from annual variations in the weather, in particular the rainfall distribution and extreme temperature events. All of these will affect the performance of subsequent crops. Therefore, production systems research should ideally be of a multi-year type which considerably increases the experimental complexities. For instance, in their sophisticated experiment over 13 years that compared organic with non-organic production systems in Wisconsin (USA), Posner et al. (2008) concluded that for most years both production

systems were equally productive. Yet, the ‘‘system  year’’ interaction proved to be statistically highly significant, because in some of the wetter years weed growth in the organic system interfered with the growth of the crop and reduced its yield. As mentioned earlier, the other problematic aspect of assessing different production systems is knowing how to deal with the effects of the diversity of agro-ecological and socio-economic conditions that is typical for resource-poor smallholders. Without paying attention to these factors, a comprehensive assessment is hardly possible, and any major investment in an up-scaling process would therefore be difficult to justify. The next sections will discuss, what should be the major elements on which to base large scale dissemination efforts. 4.1. Research into the components of production systems Obviously it will be impossible for research to simultaneously handle all the different factors entering into a crop production system through a single field experiment. Such experiment would simply become too large to be manageable. Scientists therefore may want to focus on a limited number of factors (2 or 3, at the most 4) which they judge to be of critical importance, and address precisely formulated issues/hypotheses, while maintaining the other factors (i.e., the non-experimental variables) at fixed levels. Moreover, instead of conducting the same experiment for several years in a row or to avoid complex and sophisticated, long-term experiments like those conducted by Posner et al. (2008), it will often be much more informative to change the combination of experimental factors in response to results obtained in the previous season and/or years. Another option would be to conduct several small factorial (two to three factors) or fractional factorial experiments simultaneously for a number of years. Such strategy would contribute greatly to improving our understanding and knowledge about how a proposed technology and/or crop production system is likely to behave under diverse farming conditions. In any case, the choice of experimental factors, their test levels, as well as the levels at which to maintain the nonexperimental variables, is by no means easy, as this will always critically affect the results. A very first requirement for establishing the superiority of one crop production system over another, in a scientifically unbiased way, is the identification of cultivars that have been proven to be optimally adapted to a particular system. This point was convincingly made in a recent study by Murphy et al. (2007) who compared 35 wheat genotypes for their responses to a non-organic farming system and an organic farming system. The end result was that the organic system proved as productive as the non-organic farming system so long as the genotype had been selected for that specific condition rather than through the usual indirect selection system. In other words, the scientists showed that for four out of five locations there were significant genotype  system interactions. This finding should not come as a surprise, since plant breeders have for many years been emphasising the selection for abiotic stress tolerant (e.g., for drought, salinity, low soil fertility, Al, Mn, or Fe toxicities, etc.) varieties to improve crop production under marginal and less favourable environmental conditions (see also Lynch, 2007), and high-yielding varieties to optimise production systems under favourable conditions. However, there is also another side to varietal testing and the introduction of new varieties at the farmer level. Plant breeding and progeny selection as well as subsequent line or varietal testing tend to take place mostly under standardised agronomic and crop growth conditions that reflect modern farming techniques. When such testing includes comparisons with local varieties (often tall and full-season materials), the modern farming practices are generally inappropriate, thereby introducing an additional bias in

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the results. Moreover, (soil) conditions in smallholder farmer fields in many areas will be distinctly different from those on experiment stations. Together these two aspects explain why the initial performance of newly introduced modern varieties is often disappointing for lack of adaptation to farmer conditions. To some extent this problem can be overcome by involving farmers in a direct selection process through ‘‘participatory variety selection’’ (PVS) trials conducted on-farm. In addition to the varietal adaptation issue to various soil moisture regimes, there have been a number of well-focused studies on several aspects of rice crop growth and production systems that help to clarify some of the crop features and practices associated with high yields. For example, it has been reemphasised that rapid crop establishment and the avoidance of transplanting shock is advantageous in raising grain yields (Pasuquin et al., 2008), and that transplanting young seedlings as single plants/hill minimises this shock and results in enhanced tiller development (San-oh et al., 2006; Mishra and Salokhe, 2008). Likewise, it appears that intermittent irrigation and the maintenance of moist, aerobic soils not only enhances tillering but also the root system development and function (Yang et al., 2004; Stoop, 2005). This is entirely in line with common knowledge that favourable environments for root growth and development – even for a wetland crop like rice – are created by avoiding anaerobic conditions when reduction produces large quantities of detrimental substances like ferrous iron and reduced organic molecules (Yoshida, 1981), and by providing enough space for each individual plant (see Section 3.3.). A logical consequence of more extensive and active root systems is increased drought tolerance, as well as greater efficiency in nutrient uptake (and in fertiliser use) from the soil. Mishra et al. (2006) postulate that in addition there are other interdependent processes between roots and leaves (especially the older leaves) that affect source-sink relationships, further contributing to grain formation and grain filling in widely spaced plants where shading and senescence of lower older leaves is delayed. Moreover, in his review paper Lynch (2007) draws attention to the different types of roots and their roles in accessing moisture and nutrients from different soil horizons, but equally the genetic variability that exists in root systems and architecture that can be exploited through modern plant breeding and selection techniques in developing varieties particularly suited to marginal soil conditions. Eventually, these features may explain why for instance the SRItype agronomic practices of single, widely-spaced, very young transplants not only develop profuse root systems and extensive tillering, but that subsequently these morphological differences translate into more and larger panicles with heavier individual grains even under relatively marginal soil conditions (see Stoop et al., 2002). A practical consequence would be that plant spacing will have to be adjusted in response to the tillering ability and maturity cycles of different rice varieties in order to determine the minimum plant density to secure the optimum number of panicles/ m2 that leads to the highest grain yield and individual factor productivities. However, it would be unrealistic to suppose that an optimum physiological performance of the crop could be achieved irrespective of the soil (nutrient) conditions. Again a set of complex interactions between various agronomic management practices (e.g., plant population/spacing and soil fertility management practices) would have to be taken into account to optimise crop development and yields as well as factor productivities and crop resilience to stresses. It seems unlikely that modelling exercises such as that attempted by Sheehy et al. (2004) could effectively handle this complexity and arrive at realistic assessments of agronomic yield potentials for crops grown under soil, water and weather conditions that are as diverse as in the case of rice.

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4.2. Implications for conducting field experiments The various studies conducted by IRRI scientists have been indicative also of another undesirable trend in agronomic field research. Over the years scientists have been employing increasingly the most simple experimental/treatment designs, i.e., a mono-factorial or at most a two-factor treatment arrangement laid out in a randomised complete block design with three or four replications (presumably to minimise the costs of field experimentation). Each block accommodates a number of randomised plots representing different treatments or treatment combinations. In cases where a factor like irrigation requires large plots, the blocks are split into main plots with that factor within which subplots are created that represent the other treatments (e.g., different varieties), a so-called split–plot design. Yet, it has become common practice to compare only rather limited numbers of treatments through such designs, which results not only in reduced over-all information, but also at best in a moderate degree of accuracy. Often the shortcomings in the field experimentation are masked by taking many different types of measurements routinely that can be graphically presented and/or are employed as inputs into theoretical crop growth models. In the Bouman et al. (2005) case, for instance, frequent soil moisture measurements were taken as presented in Figures 2 and 3 of the article. Subsequently, these data are hardly exploited for an in-depth interpretation of the effects on crop parameters, while the various interactions, including the ‘‘varieties  soil moisture regimes’’, do not feature in the statistical analysis (see also the earlier Section 3.2). Very similar observations apply to the Bouman et al. (2006) article. The somewhat more complex experiments with factorial treatment arrangements and designs like the lattices which can accommodate a large number of treatments, through which several factors at two or more levels and their interactions can be assessed with increased precision (for examples see Cochran and Cox, 1957), appear to be out of favour. Yet, these types of experiments permit scientists to distinguish systematically between main and interaction effects and to assess these for their statistical significance. In particular, the two- and three-way interactions are of utmost importance in assessing the potentials of crop production systems as was explained in the preceding section. Small and simple experiments are attractive mostly in (onfarm) adaptive research, when supervision is often limited and irregular. The scope of such trials, and consequently the collected information is limited, however, while its reliability is often difficult to guarantee. In the absence of simultaneous and more comprehensive field experimentation the basis for drawing fundamental and valid conclusions, therefore becomes exceedingly weak, as was the case in the research by Senthilkumar et al. (2008). Serious information gaps thus remain that ideally should have been resolved prior to starting dissemination campaigns. Filling these gaps and generating high quality research data would, however, require inputs from qualified biometricians in designing field experiments and analysing the results. Unfortunately, this expertise is lacking in many agricultural research institutions with the consequence, as illustrated by the preceding analysis, that the credibility of results from agronomic field research is jeopardised. 4.3. Dissemination of knowledge-intensive production practices and systems To effectively cope with the diverse agro-ecological and socioeconomic conditions of farming environments, flexible approaches to on-farm testing and dissemination are required. This is particularly so when knowledge-intensive, integrated practices involving the simultaneous management of several elements are being introduced.

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In the past and to a large extent at present, the development and dissemination of standardised technology packages has been common practice for new varieties, mineral fertilisers and pesticide applications following the linear technology transfer principles. These technologies have generally been regarded by those who promote them as being relatively non-intensive in terms of the knowledge of agronomic management required in their adoption and application. Often, however, the on-farm conditions even with respect to these standardised seed and agrochemical-based technologies have proved more diverse and varied, and therefore complex than anticipated (see Van Mele, 2008). Over the past three decades and initially in particular for pesticide applications new approaches to crop protection management have evolved through which knowledge-intensive integrated pest management (IPM) practices have been introduced. Farmers were taught the underlying principles of IPM practices through a learning and farmer discovery process, thereby empowering farmers with the capacity to manage its application independently. This successful approach followed by the FAO in Asia in the 1980s and 1990s was based on building farmer capacity to support the large scale dissemination of rice IPM practices through networks of Farmer Field Schools (FFS) that have remained firmly in place in Asia even today (Van den Berg and Jiggins, 2007). Similar IPMbased pest management practices are being replicated throughout Africa in recent years with similar success. By taking into account the levels of pest infestation and the numbers of various beneficial organisms (e.g., predators, parasitoides) that are present in the natural environment and that contribute to effective biological control, farmers have achieved important gains. Pesticide use and its expenses as well as the associated health and pollution risks have been reduced greatly as a result. Consequently, IPM practices have increasingly replaced the standard, calendar-based, recommendations for pesticide applications (see the extensive grey literature on the successful IPM experiences in Asia and Africa at http://www.fao.org/ag/AGP/AGPP/IPM/gipmf/index.htm). Other integrated practices such as conservation agriculture (CA) systems for soil health management and sustainable production intensification, or SRI (rice) agronomy for integrating and optimising the use of production inputs for sustainable rice intensification, should likewise be viewed as being knowledgeintensive types of approaches and production practices. By offering productivity, economic and environmental improvements these practices provide considerable potential benefits for large groups of farmers (see: Goddard et al., 2008; FAO, 2008a,b; and publications at http://www.fao.org/ag/ca/ for CA; and at http:// ciifad.cornell.edu/sri/ for SRI). CA production systems are based on three principles: (a) no mechanical tillage and minimal disturbance of the soil by direct seeding or planting through a soil organic cover; (b) maintenance of a permanent complete cover of the soil with plant organic materials (e.g., residues of the previous crops, cover crops); (c) the use of diversified rotations, sequences and associations which include N-fixing legumes. In a similar way, SRI systems aim at integrating six agronomic principles at the production level as described in Section 3.1. The development and dissemination of integrated practices such as IPM, CA or SRI that are each based on integrating multiple principles into production practices, however, requires flexibility both in the form in which technological information is provided and tested on-farm as well as in the approaches followed for dissemination and scaling. Once the ‘proof of concept’ has been established under field conditions for the technological production principles, farmers themselves, including smallholders, will have to gain some basic initial experience on how to translate and integrate the principles into production practices in their local farming systems. Farmers will learn by testing and developing their own location-specific adaptations

in production practices by fine-tuning these to their specific local needs and farming conditions. For instance, in a number of countries in Africa, conservation agriculture (CA) practices are being tested and adopted through Farmer Field Schools (FFS) networks and training in countries such as Ghana, Kenya, Tanzania and Uganda (see publications showing the advantages of CA in productivity, cost of production, system stability and income, posted at the FAO CA website: http:// www.fao.org/ag/ca/). Similarly, IPM practices in FFS networks operate in Asia and Africa as seen from the publications posted at http://www.fao.org.ipm. Further, in several major rice producing countries in Asia, SRI production principles and practices appear to be spreading rapidly in recent years through a combination of policy support by national and local governments, and local stakeholder initiatives working through farmer organisations, which enhance farmer-to-farmer extension, information exchange and learning in combination with FFS. Various recent reports from India (Prasad, 2006), and Indonesia (Sato and Uphoff, 2007) illustrate this process. As underscored by Mishra et al. (2006), it is this type of cooperative learning approach in the ongoing dissemination of SRI principles and practices that explains their success because it offers smallholders the possibility to exploit and optimise local conditions for production intensification without having to rely heavily on imported technologies and/or expensive exogenous inputs. Thus broadly, but well-defined, SRI production principles in combination with flexible/informal learning and dissemination approaches have increasingly encouraged even smallholders to experiment and undertake independent assessments of various practices and adapt and integrate those elements that offer tangible benefits to their respective production systems (see publications posted at http://ciifad.cornell.edu/sri/). Thus, a relatively large variation in the implementation and performance of IPM practices, CA systems or SRI agronomy in farmers’ fields is an obvious and logical consequence of this dissemination approach. After all individual farmers will have to establish new balances and equilibria over time to achieve the full benefits that such systems are expected to offer. Therefore, economic assessments and adoption studies based on aggregated results over relatively short periods of time will further contribute to biased and/or pre-mature, generalised conclusions with regards to production potentials, agronomic feasibility and future prospects. In the case of SRI, this appears to have happened for the short-term studies by Moser and Barrett (2003) in Madagascar and by Senthilkumar et al. (2008) in Tamil Nadu, as well as for the global synopsis of SRI by McDonald et al. (2006). In each of these cases, an assessment of SRI practices was attempted but the underlying principles as well as the practices were still incompletely understood by scientists, and inadequately and rather variedly implemented by farmers, as they still lacked a basic level of personal experience in putting SRI principles into practice. Ideally, clearly stated disclaimers and caveats that indicate the various assumptions and limitations of the studies should be included when presenting the ensuing results as a formal publication. 5. Discussion and conclusions Rice is a crop that is grown in the tropical, sub-tropical and warm temperate regions under very different agro-ecological conditions ranging from sea level to 2500 m altitude. Production systems vary accordingly, depending on the extent of control over water. The latter may range from rainfed uplands to wet lowlands and flood plains with annually varying levels of flooding and to sophisticated irrigation schemes where water availability can be controlled meticulously (see WARDA (1999) for the situation in West Africa). Directly related to this divers range of agro-ecological

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conditions, is also a huge genetic diversity within the rice crop. Furthermore, in rice-based cropping systems in the sub-tropics or tropics away from the equator, rice is a component that is grown as part of a rotation with other irrigated crops (often wheat, vegetables, potato, forage legumes or pulses). In the equatorial tropics, other crops in rotation with rice are vegetables, pulses or legumes. It follows that to assess the specific merits of the various rice cultivars and production systems is a complex task. Such assessments are compounded further by the numerous locationspecific natural and socio-economic factors that are encountered in any farming environment. The implications for the development and dissemination of new crop production technologies, particularly when involving new knowledge-intensive, integrated principles and practices, therefore should not be underestimated. Apart from genotype adaptation, there are obviously many other factors that together make up a crop production system whose actual performance is also greatly affected by the variables associated with local soil, water and weather conditions. However, the limited time span of much of the field crop research (being based on fixed-term projects, frequently of a rather narrow scope, repeating the same experiment for several seasons) tends to interfere with more comprehensive assessments of crop production systems prior to introducing any new system to farmers. The present article highlights the serious implications of that situation for rice agronomic research and for agronomic research in general, as well as for the dissemination of results from such research to farmers. This issue was illustrated in the preceding sections of this paper. In this regard, the research studies on aerated rice (Bouman et al., 2005, 2006) reviewed above have a limited scope (both conceptually and experimentally), by looking at just three or four improved varieties grown under different soil moisture regimes for just a few seasons. A similar criticism applies to the study by Nie et al. (2008) of ‘‘soil sickness’’ as a result of mono-cropping of aerobic rice. While the yield depressing effect of such practice is not surprising, it is not plausible that a long-term solution will be found by raising nitrogen fertiliser applications as suggested by the authors. In either case, the research was narrowly focussed and did not permit a comprehensive analysis (also in statistical terms). In light of the above, the conclusion by Bouman et al. (2005) that aerated rice systems hold promise for farmers, presumably because of the savings in irrigation water, while the yield difference could be overcome through ‘‘further breeding to develop varieties that can achieve high yields under drier soil conditions than used in their experiments’’ is rather superficial and cannot be justified in the absence of more comprehensive agronomic research. It certainly does not constitute a reliable basis for a subsequent dissemination effort of aerobic rice. A similar observation applies to studies by Senthilkumar et al. (2008) who made comparisons between a conventional and a modified (water-saving) rice system for two seasons on the basis of just one single variety prior to entering a phase of on-farm, multi-locational adaptive research trials (ART) based on some 100 tests followed by farmer surveys to identify adoption constraints. Similar criticisms can, however, also be levelled at various research efforts seeking to validate or invalidate SRI. Generally, equally inappropriate field experimental designs and statistical analyses were employed in some of these, formally published, studies on SRI production research (e.g., Ceesay et al., 2006; Lin et al., 2005; Tsujimoto et al., 2009) to complement the huge amount of grey literature on spectacular SRI yield responses in farmer fields (see: http:// ciifad.cornell.edu/sri/). In all these studies the critical shortcoming has been that important interactions were not analysed at all, or analysed inadequately. Such interactions, particularly those between soil water regimes and other agronomic factors, like varietal adapta-

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tion, seed rates, plant density/spacing, fertiliser regimes and plant protection practices are of fundamental significance. Their proper assessment would most likely have permitted the identification of important and practical cost-saving alternatives for farmers to enhance productivity and output. Another research trend has been to attribute increased weight to crop modelling, presumably to avoid the high costs of field experimentation. However, growth and production models are necessarily based on existing information and assumptions derived from status quo systems and therefore are unlikely to apply to novel systems and/or to cope effectively with a range of complex, and even unexpected interactions. In that respect modelling might have little to offer to explaining production system behaviour when the biological phenomena involved in space and time are still incompletely understood by scientists including those engaged in the modelling work. In view of the on-farm variability and diversity between farms and farmers in implementing a multi-component crop production system, discussions about adoption and non-adoption readily become non-debates simply because of the impossibility to objectively distinguish one crop production system from the other under conditions of practical farming. As a result much of the SRI debate conducted over the past ten years has been of a semantic and academic nature (see Doberman, 2003; Sinclair and Cassman, 2004; Sheehy et al., 2005; McDonald et al., 2008). After all, SRI itself is an ‘‘integrated’’ rice production system and demarcating it distinctly from other (integrated) systems (see Table 1) in the field will not always be easy, or even relevant for practical purposes. In that regard McDonald et al. (2006), in spite of their flawed methodology and therefore scientifically unsupported conclusions concerning the superiority of ‘‘best management practices (BMP)’’ over SRI, have a point when stating that there is still no conclusive scientific evidence that explains the SRI performance. It is still possible that the recorded higher yields and individual factor productivities under SRI are simply the effect of more timely and meticulous crop management by the farmers. However, the magnitude of the yield responses and of differences in factor productivities that were recorded in farmer fields for SRI, along with the large savings made in external input use, are such that a comprehensive and fundamental research effort into this alternative approach to rice farming is fully justified. As elaborated in the present article, such research will need to be more robust than that conducted in the past by Sheehy et al. (2004), Latif et al. (2005) and McDonald et al. (2006). Therefore, it is important for scientists not to become entangled in research efforts associated with a specific paradigm, be it Green Revolution or biologic/organic farming. This seems to have occurred in the case of the various IRRI studies referred to in this article, but likewise for SRI. Because of their implicit orientation and outlook, the IRRI studies simply missed various low-cost and practical agronomic alternatives of great relevance and value to any type of rice farmer. Yet, certain viable alternatives to the promoted BMP (best management practices) systems have come forward from non-conventional, farmer participatory research efforts, as highlighted by the case of SRI. In both cases, however, the desire and pressures for achieving quick results have led to ignoring major agronomic factors and their interactions. The preceding analysis highlights that several of the SRI principles are likely to be of considerable relevance for rice production in general (e.g., seedling vigour, reduced seed rates, wider spacing, aerobic soil condition, extensive healthy root system, etc.) and therefore certainly merit further research and, most likely, exploitation on a wide scale. With respect to such scaling there should be a concern that many extension programmes still tend to depart from the

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conventional, supply-driven and linear technology transfer concepts and might be preoccupied by vested commercial and political interests rather than by the needs of individual farmers and their welfare. An increased awareness of this problem has progressively led to a general recognition that fundamental and structural changes in governance and in development and delivery of agricultural knowledge are required if the multitude of the world’s smallholders are to benefit form knowledge-intensive practices (Ashby, 2007; Kiers et al., 2008). At a field implementation level this has to be complemented by practicing various participatory approaches leading to an increased emphasis on ‘‘client ownership’’ by rural communities for the introduced technologies, in other words a ‘‘demand-driven’’ innovation process. Unwittingly, the rhetoric of participatory approaches has been adopted widely by different stakeholders, thereby effectively masking their actual objectives (Stoop, 2002). Nederlof and Odonkor (2006) and Nederlof and Dangbegnon (2006) illustrate this problem well through highly relevant examples from Togo and Benin where in spite of the proclaimed participatory approaches, including FFS, various ‘‘hidden agendas’’ of other stakeholders succeeded in introducing undesirable biases, thereby contributing to the ultimate failure of interventions in terms of their impact on farmer practices. International agricultural research and development institutions have frequently emphasised that feeding a growing world population will only be possible in the future through what is called a ‘‘modern’’ agriculture and therefore systems like SRI or organic farming would have little to offer (Doberman and Dawe, 2008). It is particularly unfortunate for the world’s resource-poor farmers that the publicly funded research scientists are using such flawed arguments to exclude on a a priori basis from their research agenda a whole range of cost-saving and environment-friendly topics of great practical interest and relevance to any type of farmer and to society at large. For instance the field-based evidence on SRI has shown repeatedly that rice farmers can obtain productivity and income improvements with just a fraction of the quantity of seed normally used. In addition, based on locationspecific conditions, there will nearly always be a wide array of interesting options offered by SRI to exploit local varieties (for their desirable quality and stress tolerance characteristics) and to substitute, at least partially, the need for expensive external agricultural chemicals by locally available organic materials or in situ generated organic matter within the rice cropping system involving crops that generate high biomass. Given the fact that so much of the publicly funded agricultural research is narrowly focussed on developing new varieties/improved seeds and agricultural chemicals as the basis for a ‘‘modern’’ agriculture for smallholders in the developing world, compel us to pose the question: who is actually driving the research agenda and to what end? Equally important is the question: how an adequate level of research relevance and quality can be ensured, particularly in the publicly funded research, to avoid the common biases highlighted in the present paper? Acknowledgement The authors are grateful for the encouragements, the criticism and supportive suggestions, including the provision of the reference to Kim et al. (2009), provided by the three anonymous reviewers. References Ashby, J.A., 2007. Fostering farmer first methodological innovation: organizational learning and change in International agricultural research. On: http://www. future-agricultures.org/farmerfirst/files/D1_Ashby.pdf. Accessed 10 November 2008.

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