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Dataset Persistent ID
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doi:10.34725/DVN/KKHVOF |
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Publication Date
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2022-07-25 |
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Title
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Dataset for supporting the net agronomic assessment of yield limiting factors in maize production in Machakos county, Kenya
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Author
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Tamba, Yvonne (World Agroforestry (ICRAF))
Chacha, Robin (World Agroforestry (ICRAF))
Mboi, Damaris (World Agroforestry (ICRAF))
Aynekulu, Ermias (World Agroforestry (ICRAF)) - ORCID: 0000-0002-1955-6995
Luedeling, Eike (World Agroforestry (ICRAF)) - ORCID: 0000-0002-7316-3631
Shepherd, Keith (World Agroforestry (ICRAF)) - ORCID: 0000-0001-7144-3915
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Contact
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Use email button above to contact.
Aynekulu, Ermias (World Agroforestry (ICRAF))
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Description
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This dataset is used for a holistic analysis of the costs, benefits, and risks of on-farm soil and plant health management. The dataset was produced in 2017 by a combination of field measurements and farmer surveys. It was collected for a research study aimed at identifying and testing accurate, consistent, and cost-effective measurement tools and methodologies for evaluating the outcomes of agricultural projects. Soils data was analysed by wet spectral methods to generate estimates of the Nitrogen (N), Phosphorus (K), and Potassium (P) levels in the soils which was then used as inputs for a stochastic crop production model. The decision model consisted of two main sections targeting interactions between biotic factors (rainfall variability, availability of soil nutrients, risk of drought and temperature) and abiotic factors (farm management practices/intensity of farm management). With the two datasets, we ran a risk-return model to project the productivity of maize production and highlight yield-limiting factors. The project was funded by Bill & Melinda Gates Foundation and TechnoServe under the Innovation in Outcome Measurement (IOM) program
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Subject
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Agricultural Sciences; Earth and Environmental Sciences; Social Sciences
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Keyword
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Crop modelling (AGROVOC) http://aims.fao.org/aos/agrovoc/c_9000024
Decision analysis (NALT) http://lod.nal.usda.gov/nalt/31914
Agronomics (STW) http://zbw.eu/stw/descriptor/18318-0
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Producer
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World Agroforestry (ICRAF) https://www.worldagroforestry.org/ 
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Contributor
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Hosting Institution : World Agroforestry (ICRAF)
Research Group : CGIAR Research Program on Water, Land and Ecosystems
Funder : Bill and Melinda Gates Foundation
Funder : Technoserve- Innovations in Outcome Measurement
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Distributor
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World Agroforestry (ICRAF) https://www.worldagroforestry.org/ 
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Depositor
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Karari, Valentine
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Deposit Date
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2022-03-31
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Time Period Covered
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Start: 2017-01-01 ; End: 2017-12-31
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Kind of Data
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Biophysical and Social-economics data
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Related Material
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Bene JG, Beall HW, and Côté A. 1977. Trees, Food and People: Land Management in the Tropics. International Development Research Center: Ottawa, Canada.; Coe R, Njoloma J, and Sinclair F. 2019. Loading the dice in favour of the farmer: reducing the risk of adopting agronomic innovations. Experimental Agriculture 55(S1):67–83.; Vanlauwe B, Coe R, and Giller KE. 2019. Beyond averages: New approaches to understand heterogeneity and risk of technology success or failure in smallholder farming. Experimental Agriculture 55(S1):84–106.; Sinclair F & Coe R. 2019. The options by context approach: A paradigm shift in agronomy. Experimental Agriculture, 55(S1), 1-13. doi:10.1017/S0014479719000139; Raintree JB. 1987. The state of the art of agroforestry diagnosis and design. In Agroforestry Systems (Vol. 5). https://doi.org/10.1007/BF00119124
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