A Bayesian method to support global out-scaling of water-efficient rice technologies from pilot project areas
This article present a Bayesian probabilistic method to support out-scaling of technologies from pilot projects. The method is applied to aerobic rice, a water-saving technology with probable global potential. The method assumes that areas similar to pilot sites are more likely to adopt than those t...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Language: | Inglés |
| Published: |
Informa UK Limited
2016
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/70261 |
| _version_ | 1855531810806562816 |
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| author | Rubiano Mejía, Jorge Eliécer Cook, Simon E. Rajasekharan, Maya Douthwaite, Boru |
| author_browse | Cook, Simon E. Douthwaite, Boru Rajasekharan, Maya Rubiano Mejía, Jorge Eliécer |
| author_facet | Rubiano Mejía, Jorge Eliécer Cook, Simon E. Rajasekharan, Maya Douthwaite, Boru |
| author_sort | Rubiano Mejía, Jorge Eliécer |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | This article present a Bayesian probabilistic method to support out-scaling of technologies from pilot projects. The method is applied to aerobic rice, a water-saving technology with probable global potential. The method assumes that areas similar to pilot sites are more likely to adopt than those that are different or unfavourable. Similarity is defined from climate, landscape and socio-economic attributes. Favourability is further evaluated by project specialists. Scaling out is not a simple linear process, so the method is proposed as a complement to learning processes. Results can support prioritization and strategic planning over specific geographic areas. |
| format | Journal Article |
| id | CGSpace70261 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2016 |
| publishDateRange | 2016 |
| publishDateSort | 2016 |
| publisher | Informa UK Limited |
| publisherStr | Informa UK Limited |
| record_format | dspace |
| spelling | CGSpace702612025-03-13T09:44:41Z A Bayesian method to support global out-scaling of water-efficient rice technologies from pilot project areas Rubiano Mejía, Jorge Eliécer Cook, Simon E. Rajasekharan, Maya Douthwaite, Boru impact assessment agricultural research bayesian theory simulation models evaluación del impacto investigación agraria teoría de bayes modelos de simulación This article present a Bayesian probabilistic method to support out-scaling of technologies from pilot projects. The method is applied to aerobic rice, a water-saving technology with probable global potential. The method assumes that areas similar to pilot sites are more likely to adopt than those that are different or unfavourable. Similarity is defined from climate, landscape and socio-economic attributes. Favourability is further evaluated by project specialists. Scaling out is not a simple linear process, so the method is proposed as a complement to learning processes. Results can support prioritization and strategic planning over specific geographic areas. 2016-02-23 2016-02-02T16:06:58Z 2016-02-02T16:06:58Z Journal Article https://hdl.handle.net/10568/70261 en Open Access Informa UK Limited Rubiano M., Jorge E.; Cook, Simon; Rajasekharan, Maya; Douthwaite, Boru. 2016. A Bayesian method to support global out-scaling of water-efficient rice technologies from pilot project areas. Water International. Routledge Taylor & Francis, 41(2): 290-307. |
| spellingShingle | impact assessment agricultural research bayesian theory simulation models evaluación del impacto investigación agraria teoría de bayes modelos de simulación Rubiano Mejía, Jorge Eliécer Cook, Simon E. Rajasekharan, Maya Douthwaite, Boru A Bayesian method to support global out-scaling of water-efficient rice technologies from pilot project areas |
| title | A Bayesian method to support global out-scaling of water-efficient rice technologies from pilot project areas |
| title_full | A Bayesian method to support global out-scaling of water-efficient rice technologies from pilot project areas |
| title_fullStr | A Bayesian method to support global out-scaling of water-efficient rice technologies from pilot project areas |
| title_full_unstemmed | A Bayesian method to support global out-scaling of water-efficient rice technologies from pilot project areas |
| title_short | A Bayesian method to support global out-scaling of water-efficient rice technologies from pilot project areas |
| title_sort | bayesian method to support global out scaling of water efficient rice technologies from pilot project areas |
| topic | impact assessment agricultural research bayesian theory simulation models evaluación del impacto investigación agraria teoría de bayes modelos de simulación |
| url | https://hdl.handle.net/10568/70261 |
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