Identifying sustainable farms under diverse agro-ecological conditions and livelihood strategies in southern Africa : an interdisciplinary simulation-based approach
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ArticlePublication details: Montpellier (France) : ESA ; Agropolis, 2015.Subject(s): Online resources:
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Proceedings of the 5th International Symposium for Farming Systems Design p. 143-144Summary: Agricultural systems face the challenge to feed a growing population while at the same time reducing their environmental impact in a changing world subjected to shocks, such as extreme weather and economic volatility (Godfray et al., 2010). In this global context, southern Africa appears as a particularly sensible region due to the fact that more than 60 % of the livelihoods rely on rain-fed agriculture and have low adaptation capacity (Zinyengere et al., 2014). The diversity of biophysical and socio-economic situations in this region requires prudence in the promotion of “good practices”, and a good understanding of local farming systems complexity and their current level of inefficiency. In order to identify the most efficient farms (i.e. minimizing their inputs and simultaneously maximizing their outputs), we implemented the Data Envelopment Analysis (DEA, Charnes et al. (1978)) method, which is the most commonly used non-parametric frontier efficiency approach. Using results from farm household surveys conducted in Zambia and Malawi, we modelled the efficiency frontier based on observed best practices in 2012 and identified potential progress margin of efficiency. Even if those results are themselves significant outcomes as efficiency analysis in southern Africa are very rare (Chiona et al., 2014), the originality of this research is the combination of DEA with APSIM (Agricultural Production Systems Simulator) crop model to assess the evolution of this multi-dimensional efficiency frontier. The crop growth model APSIM was used to simulate the performance of a wide range of maize-based cropping systems under different agro-ecological conditions and future climatic scenario, for several types of farming systems identified on structural data basis (cattle, adult equivalent, income, etc.). With this approach we aim to identify cropping systems and farms in southern Africa that are most efficient under future climate.
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|---|
| Conference proceedings | CIMMYT Knowledge Center: John Woolston Library | CIMMYT Staff Publications Collection | Available |
Open Access
Abstract only
Agricultural systems face the challenge to feed a growing population while at the same time reducing their environmental impact in a changing world subjected to shocks, such as extreme weather and economic volatility (Godfray et al., 2010). In this global context, southern Africa appears as a particularly sensible region due to the fact that more than 60 % of the livelihoods rely on rain-fed agriculture and have low adaptation capacity (Zinyengere et al., 2014). The diversity of biophysical and socio-economic situations in this region requires prudence in the promotion of “good practices”, and a good understanding of local farming systems complexity and their current level of inefficiency. In order to identify the most efficient farms (i.e. minimizing their inputs and simultaneously maximizing their outputs), we implemented the Data Envelopment Analysis (DEA, Charnes et al. (1978)) method, which is the most commonly used non-parametric frontier efficiency approach. Using results from farm household surveys conducted in Zambia and Malawi, we modelled the efficiency frontier based on observed best practices in 2012 and identified potential progress margin of efficiency. Even if those results are themselves significant outcomes as efficiency analysis in southern Africa are very rare (Chiona et al., 2014), the originality of this research is the combination of DEA with APSIM (Agricultural Production Systems Simulator) crop model to assess the evolution of this multi-dimensional efficiency frontier. The crop growth model APSIM was used to simulate the performance of a wide range of maize-based cropping systems under different agro-ecological conditions and future climatic scenario, for several types of farming systems identified on structural data basis (cattle, adult equivalent, income, etc.). With this approach we aim to identify cropping systems and farms in southern Africa that are most efficient under future climate.
Conservation Agriculture Program
Socioeconomics Program
Text in english
I1706386
INT3348
INT2939
INT3360
CRUL01
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