Abstract
The potential of organic agriculture and agroecological approaches for improving food security in Africa is a controversial topic in global discussions. While there is a number of meta-analyses on the environmental, agronomic and financial performance of organic farming, most of the underlying data stems from on-station field trials from temperate regions. Data from sub-Sahara Africa in particular, as well as detailed real-farm data is scarce. How organic farming is implemented in sub-Saharan Africa and how it performs in a smallholder context remains poorly understood. We applied a novel observational two-factorial research design, which allowed to evaluate the impacts of i) interventions for introducing organic agriculture and ii) specific organic management practices on 1,645 farms from five case studies in Ghana and Kenya, which we closely monitored for 24 months. Among the farmers who have been exposed to the interventions, we found heterogeneous adoption of organic agriculture principles, depending on the intervention. Furthermore, we found rather passive than active organic management among farmers. Most yields and gross margins under organic management remained at similar levels as the conventional values in four of the case studies. In one case study, however, coffee, maize and macadamia nut yields increased by 127–308% and farm-level gross margins over all analysed crops by 292%. Pooling our data across all case studies, we found significantly higher (+144%) farm-level gross margins on organically managed farms than on conventional farms. This indicates the potential of organic and agroecological approaches if implemented well. Based on our observations, we argue for improving the implementation of organic agriculture projects in settings with smallholder farmers. Limited capacities, lack of appropriate inputs and market access are major agronomic and institutional challenges to be addressed. Furthermore, we argue for supporting a differentiated debate about which types of organic farming are really desirable by classifying approaches to organic farming according to i) their intention to work organically and ii) the degree of following the organic principles. This will support the design and implementation of targeted policy interventions for stimulating sustainability of farming systems and rural development.
Highlights
Organic agriculture (OA) is a globally-applicable environmentallyfriendly alternative to conventional farming systems, which strives for the principles of health, ecology, fairness and care (Luttikholt, 2007)
To understand how farmers practiced OA, we analysed the rate of adoption of organic practices at two levels: first, we looked at the number of farms which did not use any conventional inputs on any of their plots during any of the seasons over the two years, referred to from here on as “Passive Organic Management (POM)”
We investigated how farmers substituted these inputs by means of preventive measures and/or productivity-enhancing inputs which are permitted in OA or by agroecological practices, referred to as “Active Organic Management (AOM)”
Summary
Organic agriculture (OA) is a globally-applicable environmentallyfriendly alternative to conventional farming systems, which strives for the principles of health, ecology, fairness and care (Luttikholt, 2007). Its fundamental agronomic core characteristic is to aim at a circular system by reducing external inputs, in particular through the ban of chemical inputs such as synthetic pesticides and mineral fertilisers (Reganold and Wachter, 2016; Seufert et al, 2017). The environmental impacts are linked to the lower chemical input use and the agronomic practices that need to be implemented for compensating these inputs, such as a wider crop rotation, active nutrient management via compost, manure and nitrogen-fixing legumes and an increased use of preventive and bio logical pest management strategies. The main drawback for organic farms are the often lower yields, which partly offset these benefits when environmental benefits are evaluated from a per-output perspective (Meier et al, 2015; Seufert and Ramankutty, 2017; Tuomisto et al, 2012; van der Werf et al, 2020)
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