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A system analysis to assess the effect of low-cost agricultural technologies on productivity, income and GHG emissions in mixed farming systems in southern Ethiopia

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  • Berhanu, Yonas
  • Angassa, Ayana
  • Aune, Jens B.

Abstract

This study assessed the effects of various low-cost climate-smart agricultural (CSA) technologies on farm productivity, farm income and greenhouse gas (GHG) emissions in smallholder farming systems in southern Ethiopia. On-farm trials were conducted at three study sites/districts (Ziway, Halaba and Loka-Abaya) during the 2015 and 2016 cropping seasons. The experiment compared five climate smart treatments against existing recommended practice. Three farms were selected at each site. Each farm hosted one full experimental repetition, thus functioning as an experimental block. The average data of the two seasons were taken from each farm and means were calculated per site and over the study sites as well. The on-farm trails were established to identify a CSA technology that can improve yields and economic returns, while simultaneously reduce GHG emissions at the farm level. Averaged over the three sites, a combined application of seed priming with micro-dosing (0.5 g of fertilizer per pocket) was identified as the best-fit technology in terms of farm productivity and farm income. Results show that this technology increased maize grain yield by up to 45% (compared to the recommended practice). A model CSA farm was then created using this technology which was compared with the performance of the farmers' current system (conventional farm). It generated surplus production of both grain (more than three times higher) and fodder. The CSA farm produced 84% of dry matter fodder (DM) requirements and 60% of livestock crude protein (CP) needs respectively, while the conventional farm produced 30% DM and 48% of CP needs. Furthermore, the CSA farm demonstrated reduced GHG emissions compared to the conventional farm which grows maize without the use of mineral fertilizers. Our estimates indicate that due to the establishment of multipurpose trees on the CSA farm, the total on-farm C stock was about 29 Mg ha−1, that is 24% higher than the conventional farm. In conclusion, we recommend the combined application of seed priming and micro-dosing as a strategy for improving economic returns and an approach to enhance the sustainability of maize-based mixed systems in southern Ethiopia. Planting multipurpose trees will give additional benefits in terms of fodder and carbon sequestration.

Suggested Citation

  • Berhanu, Yonas & Angassa, Ayana & Aune, Jens B., 2021. "A system analysis to assess the effect of low-cost agricultural technologies on productivity, income and GHG emissions in mixed farming systems in southern Ethiopia," Agricultural Systems, Elsevier, vol. 187(C).
    • Handle: RePEc:eee:agisys:v:187:y:2021:i:c:s0308521x20308490
    DOI: 10.1016/j.agsy.2020.102988
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    References listed on IDEAS

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    1. Khatri-Chhetri, Arun & Aggarwal, P.K. & Joshi, P.K. & Vyas, S., 2017. "Farmers' prioritization of climate-smart agriculture (CSA) technologies," Agricultural Systems, Elsevier, vol. 151(C), pages 184-191.
    2. Yonas Berhanu & Lars Olav & Ajebu Nurfeta & Ayana Angassa & Jens B. Aune, 2019. "Methane Emissions from Ruminant Livestock in Ethiopia: Promising Forage Species to Reduce CH 4 Emissions," Agriculture, MDPI, vol. 9(6), pages 1-16, June.
    3. Angus Deaton, 2003. "Household Surveys, Consumption, and the Measurement of Poverty," Economic Systems Research, Taylor & Francis Journals, vol. 15(2), pages 135-159.
    4. Craig McIntosh & Alexander Sarris & Fotis Papadopoulos, 2013. "Productivity, credit, risk, and the demand for weather index insurance in smallholder agriculture in Ethiopia," Agricultural Economics, International Association of Agricultural Economists, vol. 44(4-5), pages 399-417, July.
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    Cited by:

    1. Gebeyanesh Zerssa & Debela Feyssa & Dong-Gill Kim & Bettina Eichler-Löbermann, 2021. "Challenges of Smallholder Farming in Ethiopia and Opportunities by Adopting Climate-Smart Agriculture," Agriculture, MDPI, vol. 11(3), pages 1-26, February.
    2. Eleni Yitbarek & Wondimagegn Tesfaye, 2022. "Climate-Smart Agriculture, Non-Farm Employment and Welfare: Exploring Impacts and Options for Scaling Up," Sustainability, MDPI, vol. 14(23), pages 1-22, November.
    3. Yang, Xin & Zhou, Xiaohe & Deng, Xiangzheng, 2022. "Modeling farmers’ adoption of low-carbon agricultural technology in Jianghan Plain, China: An examination of the theory of planned behavior," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    4. Xiaowen Dai & Xin Wu & Yi Chen & Yanqiu He & Fang Wang & Yuying Liu, 2022. "Real Drivers and Spatial Characteristics of CO 2 Emissions from Animal Husbandry: A Regional Empirical Study of China," Agriculture, MDPI, vol. 12(4), pages 1-18, April.

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