Evidence-based Decision Making in Agricultural Development

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When you visit the doctor with a worrying symptom, or take your sick dog to the vets, you assume that the practitioner you consult is basing his diagnosis and treatment decision on the best available evidence, and not just on a quick Google search. After all, the pace of progress and change in scientific research is rapid, and it may be some years since your doctor did her training. 

Medical and veterinary practitioners (and most other professions, for that matter) also work in regulated and monitored environments, with government and non-government bodies responsible for setting policy and assessing quality. The process of setting policy for something as important as the health and well-being of a population is understandably complex and requires excellent information upon which to base those systems. Systematic reviews have revolutionised the way that policy makers in healthcare interpret the evidence base and come to conclusions about the best way to deliver cost-effective and high quality services to the general population.

In agriculture, the situation is more complex, and the evidence base for setting policy is harder to accumulate, given the lack of a significant body of Randomised Control Trials (RCTs). But what could be more important than evidence-based decision-making and policy setting in agriculture when the planet is striving to feed a rapidly growing population with dwindling natural resources, depleted soils and adaptation to climate change to contend with?

Another factor to take into account is that approximately 70% of the world’s food is grown by smallholder farmers in developing countries, where agriculture is beset by problems of pests and diseases, post-harvest losses, poor productivity and lack of good information about best practice. It is a sad fact that some 40% of crops grown are lost as a result; food which could have fed many millions of people. In many cases, the solutions to improve productivity and to reduce such losses are simple and low-tech, and would not be found in the pages of an international research journal with a high Impact Factor. But if the research relevant to the needs of the developing world is under-reported in generic bibliometric databases, then it stands to reason that the policy-makers who rely on such databases will not be basing their decisions on the best available evidence.

CAB Abstracts covers the agricultural research outputs of over 150 countries, and includes annual reports, one-off technical documents, conference presentations and book chapters alongside over 7,000 serial publications. To illustrate the benefit of this comprehensive coverage, a work in progress by researchers from France, Spain and the UK (presented at the 5th annual Global TechMining conference in Atlanta in September 2015) has uncovered massive under-representation of research relevant to rice in the main bibliometric databases when compared to CAB Abstracts, and when analysed particularly for relevance to the developing world[i]. The authors point to the potential distortion this could create in policy-making in agriculture by undervaluing domestic capabilities and a research agenda more in line with needs in the developing world.

As Systematic Reviews become more popular and understood as a way to conduct a comprehensive review of the evidence base in any given discipline while eliminating any concerns about conscious or unconscious bias, each discipline will need to identify the key resources to support this process. In agriculture, while there is no equivalent to the Cochrane Reviews, a specialist research database like CAB Abstracts can go a long way to ensuring that policy is based on a thorough assessment of all relevant knowledge.

To read more about CAB Abstracts visit:

www.cabi.org/cababstracts

or

www.ebscohost.com/academic/cab-abstracts

[i] Under-reporting research relevant to local needs in the global south. Database biases in the representation of knowledge of rice. Rafols, I., Ciarli, T., Chavarro, D.

 

 

 

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