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A Bayesian Assessment of Productivity and Risks to Achieve Target Yields from Improved Chickpea and Mung Bean Varieties Using On-Farm Trials in Afghanistan
Legumes are essential to meet nutrition need of growing population in Afghanistan but have low productivity under the farmer practices. With an aim to introduce improved varieties of chickpea (Cicer arietinum) and mung ...
A Bayesian Assessment of Productivity and Risks to Achieve target Yields from Improved Chickpea and Mung Bean Varieties Using On-Farm Trials in Afghanistan
Legumes are essential to meet nutrition need of growing population in Afghanistan but have low productivity under the farmer practices. With an aim to introduce improved varieties of chickpea (Cicer arietinum) and mung ...
A Web-based Platform for Enhancing Monitoring, Evaluation and Learning (MEL) in Research for Development - Toward Achieving Development Outcomes
Achieving efficiency in large and complex research for development programs (R4D) is a significant
challenge. In 2015, as a response to the lack of a shared monitoring and evaluation system for CGIAR
Research Programs ...
A Bayesian analysis of data from on-farm trials in legumes in Afghanistan
This presentation discusses Bayesian analysis of on-farm trials on chickpea and mung bean conducted in Afghanistan in 2012 using the priors from 2009-2011. It tabulates the posterior means of mean and standard deviation ...
Monitoring, Evaluation & Learning (MEL): Envisioning an Optimal Data Flow to achieve Development Outcomes
Impact in agricultural research is strictly related to the data flow quality within research for development institutions. Achieving the Sustainable Development Goals (or Development Outcomes) is the final stage of the ...