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To mulch or to munch? Big modelling of big data

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  • Rodriguez, D
  • de Voil, P
  • Rufino, MC
  • Odendo, M
  • van Wijk, MT

Abstract

African farmers are poorly resourced, highly diverse and aground by poverty traps making them rather impervious to change. As a consequence R4D efforts usually result in benefits but also trade-offs that constraint adoption and change. A typical case is the use of crop residues as mulches or as feedstock. Here we linked a database of household surveys with a dynamic whole farm simulation model, to quantify the diversity of trade-offs from the alternative use of crop residues. Simulating all the households in the survey (n=613) over 99 years of synthetic climate data, showed that benefits and trade-offs from “mulching or munching” differ across agro-ecologies, and within agro-ecologies across typologies of households. Even though trade-offs between household production or income and environmental outcomes could be managed; the magnitude of the simulated benefits from the sustainable intensification of maize-livestock systems were small. Our modelling framework shows the benefits from the integration of socio-economic and biophysical approaches to support the design of development programs. Our results support the argument that a greater focus is required on the development and diversification of farmers' livelihoods within the framework of an improved understanding of the interconnectedness between biophysical, socio-economic and market factors.

Suggested Citation

  • Rodriguez, D & de Voil, P & Rufino, MC & Odendo, M & van Wijk, MT, 2017. "To mulch or to munch? Big modelling of big data," Agricultural Systems, Elsevier, vol. 153(C), pages 32-42.
    • Handle: RePEc:eee:agisys:v:153:y:2017:i:c:p:32-42
    DOI: 10.1016/j.agsy.2017.01.010
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    7. Li, Lei & Lin, Jiabao & Ouyang, Ye & Luo, Xin (Robert), 2022. "Evaluating the impact of big data analytics usage on the decision-making quality of organizations," Technological Forecasting and Social Change, Elsevier, vol. 175(C).

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