What farmers don't know can't help them: The strengths and weaknesses of indigenous technical knowledge in Honduras

Bentley, Jeffery W.

doi:10.1007/bf02217666

Cited by 113 publications

(47 citation statements)

References 9 publications

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“…Lack of training and awareness about diseases may be suggested as a reason leading to the relatively lowest validity, i.e., the highest degree of incorrect observations on Disease resistance. Our results concur with Bentley's (1989) reasoning that the ease of visual observation is an important determinant of the accuracy of farmers' observations and is therefore a main factor explaining the depth and level of concurrence of farmers' and formal scientific knowledge in different domains.…”

Section: Computational Resourcessupporting

confidence: 91%

“…To achieve highquality science using this citizen science approach, the level of accuracy of data collection by farmers should be clear. Farmers have heterogeneous levels of knowledge and expertise, and possess knowledge that is more developed in some domains than in others (Bentley 1989). Kremen et al (2011) show that citizen scientists can make accurate observations in certain categories, but are more prone to bias or inaccuracy in others.…”

Section: Introductionmentioning

confidence: 99%

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The accuracy of farmer-generated data in an agricultural citizen science methodology

Steinke

Etten

Zelan

2017

Agron. Sustain. Dev.

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Over the last decades, participatory approaches involving on-farm experimentation have become more prevalent in agricultural research. Nevertheless, these approaches remain difficult to scale because they usually require close attention from well-trained professionals. Novel large-N participatory trials, building on recent advances in citizen science and crowdsourcing methodologies, involve large numbers of participants and little researcher supervision. Reduced supervision may affect data quality, but the "Wisdom of Crowds" principle implies that many independent observations from a diverse group of people often lead to highly accurate results when taken together. In this study, we test whether farmergenerated data in agricultural citizen science are good enough to generate valid statements about the research topic. We experimentally assess the accuracy of farmer observations in trials of crowdsourced crop variety selection that use triadic comparisons of technologies (tricot). At five sites in Honduras, 35 farmers (women and men) participated in tricot experiments. They ranked three varieties of common bean (Phaseolus vulgaris L.) for Plant vigor, Plant architecture, Pest resistance, and Disease resistance. Furthermore, with a simulation approach using the empirical data, we did an orderof-magnitude estimation of the sample size of participants needed to produce relevant results. Reliability of farmers' experimental observations was generally low (Kendall's W 0.174 to 0.676). But aggregated observations contained information and had sufficient validity (Kendall's tau coefficient 0.33 to 0.76) to identify the correct ranking orders of varieties by fitting Mallows-Bradley-Terry models to the data. Our sample size simulation shows that low reliability can be compensated by engaging higher numbers of observers to generate statistically meaningful results, demonstrating the usefulness of the Wisdom of Crowds principle in agricultural research. In this first study on data quality from a farmer citizen science methodology, we show that realistic numbers of less than 200 participants can produce meaningful results for agricultural research by tricot-style trials.

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Section: Computational Resourcessupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

The accuracy of farmer-generated data in an agricultural citizen science methodology

Steinke

Etten

Zelan

2017

Agron. Sustain. Dev.

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“…2). At one end of the continuum, experts emphasize direct experience in immediate surroundings ), tend to be abductive (Bentley 1989) and stress continuity while acknowledging local variation (Lauer and Aswani 2010). Their knowledge can be useful for informing local observations ), providing explanations for events and processes in their immediate context (e.g., Kovacs 2000) and generating ideas for testable, causal relationships (Bart 2006).…”

Section: A Continuum Of Experts and Expertisementioning

confidence: 99%

Toward rigorous use of expert knowledge in ecological research

et al. 2013

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Abstract. Practicing ecologists who excel at their work (''experts'') hold a wealth of knowledge. This knowledge offers a wide range of opportunities for application in ecological research and natural resource decision-making. While experts are often consulted ad-hoc, their contributions are not widely acknowledged. These informal applications of expert knowledge lead to concerns about a lack of transparency and repeatability, causing distrust of this knowledge source in the scientific community. Here, we address these concerns with an exploration of the diversity of expert knowledge and of rigorous methods in its use. The effective use of expert knowledge hinges on an awareness of the spectrum of experts and their expertise, which varies by breadth of perspective and critical assessment. Also, experts express their knowledge in different forms depending on the degree of contextualization with other information. Careful matching of experts to application is therefore essential and has to go beyond a simple fitting of the expert to the knowledge domain. The standards for the collection and use of expert knowledge should be as rigorous as for empirical data. This involves knowing when it is appropriate to use expert knowledge and how to identify and select suitable experts. Further, it requires a careful plan for the collection, analysis and validation of the knowledge. The knowledge held by expert practitioners is too valuable to be ignored. But only when thorough methods are applied, can the application of expert knowledge be as valid as the use of empirical data. The responsibility for the effective and rigorous use of expert knowledge lies with the researchers.

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“…insects and the symptoms of diseases, their ability to interpret these systems often is limited due to insufficient knowledge of underlying processes (2). Late blight can be especially difficult for farmers to manage.…”

mentioning

confidence: 99%

Management of Potato Late Blight in the Peruvian Highlands: Evaluating the Benefits of Farmer Field Schools and Farmer Participatory Research

et al. 2004

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Farmer field school programs incorporating farmer participatory research (FPR-FFS) have the potential to provide important benefits to their participants and to other farmers who benefit from improved cultivars and management techniques. An FPR-FFS program in San Miguel, Cajamarca, Peru, has been in place since 1999 with an emphasis on management of potato late blight, caused by Phytophthora infestans, the most important problem facing Andean potato growers. Farmers' knowledge of late blight was surveyed to determine useful components for the FPR-FFS curriculum. The benefits to participants of FPR-FFS programs were evaluated first by measuring knowledge of late blight management of participants and nonparticipants. Studies of the Peruvian FPR-FFS program indicate that participants are more knowledgeable and that their expertise further increases after an additional year of participation. The benefits to participants can be evaluated more directly by comparing the productivity of participants' farms compared with nonparticipants' farms. For the Peruvian FPR-FFS program, participants had significantly higher average levels of productivity. The benefits of FPR-FFS programs for the development of better cultivars and management techniques can be evaluated indirectly in terms of improved estimates of performance. Estimates of the overall performance of a particular cultivar or technique become more precise as data from more sites are included in calculating the estimate. A more direct evaluation of benefits from FPR-FFS input may be based on the ability of farmers in FPR-FFS programs to eliminate undesirable genotypes and to recommend desirable genotypes based on criteria in addition to those used by breeders.

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What farmers don't know can't help them: The strengths and weaknesses of indigenous technical knowledge in Honduras

Cited by 113 publications

References 9 publications

The accuracy of farmer-generated data in an agricultural citizen science methodology

The accuracy of farmer-generated data in an agricultural citizen science methodology

Toward rigorous use of expert knowledge in ecological research

Management of Potato Late Blight in the Peruvian Highlands: Evaluating the Benefits of Farmer Field Schools and Farmer Participatory Research

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