Bigger data from landscape-scale crop assessment surveys empowers sustainability transitions
Methodological advances for use with large-n datasets hold the promise of transforming the ways that agricultural landscapes are described, understood, and managed. Nevertheless, most countries lack comprehensive characterization data for crop production systems and this constrains the application o...
| Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , |
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| Formato: | Preprint |
| Lenguaje: | Inglés |
| Publicado: |
SSRN
2023
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/138777 |
| _version_ | 1855519917247299584 |
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| author | McDonald, Andrew J. Malik, Ram K. Ajay, Anurag Craufurd, Peter Q. Dubey, Shantanu K. Gautam, Udham S. Karki, Saral Kishore, Avinash Krupnik, Timothy J. Kumar, Virender Mkondiwa, Maxwell Nayak, Hari S. Parihar, Chiter M. Paudel, Gokul Peramaiyan, Panneer Pundir, Ajay Poonia, Shishpal Samaddar, Arindam Sherpa, Sonam Balwinder-Singh Singh, Sudhanshu Urfels, Anton Veettil, Prakashan Pathak, Himanshu Singh, Ashok K. |
| author_browse | Ajay, Anurag Balwinder-Singh Craufurd, Peter Q. Dubey, Shantanu K. Gautam, Udham S. Karki, Saral Kishore, Avinash Krupnik, Timothy J. Kumar, Virender Malik, Ram K. McDonald, Andrew J. Mkondiwa, Maxwell Nayak, Hari S. Parihar, Chiter M. Pathak, Himanshu Paudel, Gokul Peramaiyan, Panneer Poonia, Shishpal Pundir, Ajay Samaddar, Arindam Sherpa, Sonam Singh, Ashok K. Singh, Sudhanshu Urfels, Anton Veettil, Prakashan |
| author_facet | McDonald, Andrew J. Malik, Ram K. Ajay, Anurag Craufurd, Peter Q. Dubey, Shantanu K. Gautam, Udham S. Karki, Saral Kishore, Avinash Krupnik, Timothy J. Kumar, Virender Mkondiwa, Maxwell Nayak, Hari S. Parihar, Chiter M. Paudel, Gokul Peramaiyan, Panneer Pundir, Ajay Poonia, Shishpal Samaddar, Arindam Sherpa, Sonam Balwinder-Singh Singh, Sudhanshu Urfels, Anton Veettil, Prakashan Pathak, Himanshu Singh, Ashok K. |
| author_sort | McDonald, Andrew J. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Methodological advances for use with large-n datasets hold the promise of transforming the ways that agricultural landscapes are described, understood, and managed. Nevertheless, most countries lack comprehensive characterization data for crop production systems and this constrains the application of emerging analytical methods. New datasets are required that are routinely collected, representative, and topically robust through surveys that are efficiently deployed at scale, especially in smallholder-dominated systems where heterogeneity is common. Here we present results from a collaboration between the Indian Council for Agricultural Research (ICAR) and the Cereal Systems Initiative for South Asia (CSISA) to address agricultural data gaps in India. With more than 39,000 fields surveyed, novel insights have been developed for closing yield gaps, reducing greenhouse gas emissions, and targeting solutions through predictive analytics. To capitalize on investments in data, methodological and institutional changes must be combined so that learning from landscapes empowers innovation and sustainability transition |
| format | Preprint |
| id | CGSpace138777 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | SSRN |
| publisherStr | SSRN |
| record_format | dspace |
| spelling | CGSpace1387772025-12-08T09:54:28Z Bigger data from landscape-scale crop assessment surveys empowers sustainability transitions McDonald, Andrew J. Malik, Ram K. Ajay, Anurag Craufurd, Peter Q. Dubey, Shantanu K. Gautam, Udham S. Karki, Saral Kishore, Avinash Krupnik, Timothy J. Kumar, Virender Mkondiwa, Maxwell Nayak, Hari S. Parihar, Chiter M. Paudel, Gokul Peramaiyan, Panneer Pundir, Ajay Poonia, Shishpal Samaddar, Arindam Sherpa, Sonam Balwinder-Singh Singh, Sudhanshu Urfels, Anton Veettil, Prakashan Pathak, Himanshu Singh, Ashok K. data crop production production systems sustainability sustainability assessment Methodological advances for use with large-n datasets hold the promise of transforming the ways that agricultural landscapes are described, understood, and managed. Nevertheless, most countries lack comprehensive characterization data for crop production systems and this constrains the application of emerging analytical methods. New datasets are required that are routinely collected, representative, and topically robust through surveys that are efficiently deployed at scale, especially in smallholder-dominated systems where heterogeneity is common. Here we present results from a collaboration between the Indian Council for Agricultural Research (ICAR) and the Cereal Systems Initiative for South Asia (CSISA) to address agricultural data gaps in India. With more than 39,000 fields surveyed, novel insights have been developed for closing yield gaps, reducing greenhouse gas emissions, and targeting solutions through predictive analytics. To capitalize on investments in data, methodological and institutional changes must be combined so that learning from landscapes empowers innovation and sustainability transition 2023-07-15 2024-02-01T17:11:38Z 2024-02-01T17:11:38Z Preprint https://hdl.handle.net/10568/138777 en Open Access SSRN McDonald, Andrew J. et al. 2023. Bigger Data from Landscape-Scale Crop Assessment Surveys Empowers Sustainability Transitions. https://doi.org/10.2139/ssrn.4511866 |
| spellingShingle | data crop production production systems sustainability sustainability assessment McDonald, Andrew J. Malik, Ram K. Ajay, Anurag Craufurd, Peter Q. Dubey, Shantanu K. Gautam, Udham S. Karki, Saral Kishore, Avinash Krupnik, Timothy J. Kumar, Virender Mkondiwa, Maxwell Nayak, Hari S. Parihar, Chiter M. Paudel, Gokul Peramaiyan, Panneer Pundir, Ajay Poonia, Shishpal Samaddar, Arindam Sherpa, Sonam Balwinder-Singh Singh, Sudhanshu Urfels, Anton Veettil, Prakashan Pathak, Himanshu Singh, Ashok K. Bigger data from landscape-scale crop assessment surveys empowers sustainability transitions |
| title | Bigger data from landscape-scale crop assessment surveys empowers sustainability transitions |
| title_full | Bigger data from landscape-scale crop assessment surveys empowers sustainability transitions |
| title_fullStr | Bigger data from landscape-scale crop assessment surveys empowers sustainability transitions |
| title_full_unstemmed | Bigger data from landscape-scale crop assessment surveys empowers sustainability transitions |
| title_short | Bigger data from landscape-scale crop assessment surveys empowers sustainability transitions |
| title_sort | bigger data from landscape scale crop assessment surveys empowers sustainability transitions |
| topic | data crop production production systems sustainability sustainability assessment |
| url | https://hdl.handle.net/10568/138777 |
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