Search Results - Open learning.

Contextual determinants of learning behaviour differentials amongst host-farmers of University-student outreach in Uganda by Kalule, S.W., Sseguya, H., Ongeng, D., Karubanga, G.A.

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Big data, small explanatory and predictive power: Lessons from random forest modeling of on-farm yield variability and implications for data-driven agronomy by Silva, ‪João Vasco, Heerwaarden, Joost van, Reidsma, Pytrik, Laborte, Alice G., Tesfaye, Kindie, Ittersum, Martin K. van

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Hybrid-AI and Model Ensembling to Exploit UAV-Based RGB Imagery: An Evaluation of Sorghum Crop’s Nitrogen Content by Hammouch, Hajar, Patil, Suchitra, Choudhary, Sunita, El-Yacoubi, A. Mounim, Masner, Jan, Kholová, Jana, Anbazhagan, Krithika, Vanek, Jirí, Qin, Huafeng, Stoces, Michal, Berbia, Hassan, Jagarlapudi, Adinarayana, Chandramouli, Magesh, Mamidi, Srinivas, Prasad, K.V.S.V., Baddam, Rekha

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Site-specific fertilizer recommendation using data driven machine learning enhanced wheat productivity and resource use efficiency by Liben, Feyera, Abera, Wuletawu, Chernet, Meklit Tariku, Ebrahim, Mohammed, Tilaye, Amsalu, Erkossa, Teklu, Degefie, Tibebe Degefie, Mponela, Powell, Kihara, Job, Tamene, Lulseged D.

“…Countries like Ethiopia are moving towards adopting site-specific fertilizer recommendations (SSFR) that are developed using machine learning (ML) and designed to enhance yields, profitability, and environmental benefits. …”
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Changes in anemia and anthropometry during adolescence predict learning outcomes: Findings from a 3-year longitudinal study in India by Nguyen, Phuong Hong, Walia, Monika, Pant, Anjali, Menon, Purnima, Scott, Samuel P.

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A review of multimodal deep learning methods for genomic-enabled prediction in plant breeding by Montesinos-Lopez, Osval A., Chavira-Flores, Moises, Kismiantini, Crespo-Herrera, Leonardo A., Saint Pierre, Carolina, Huihui Li, Fritsche-Neto, Roberto, Khalid Al-Nowibet, Montesinos-Lopez, Abelardo, Crossa, José

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Desarrollo e implementación de un sistema de apoyo para laboratorios con dispositivos móviles - pockets en el Centro Internacional de la Papa by Verano, P.E.

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Interpretable machine learning methods to explain on-farm yield variability of high productivity wheat in Northwest India by Nayak, Harisankar, Silva, ‪João Vasco, Parihar, Chiter Mal, Krupnik, Timothy J., Sena, Dipaka Ranjan, Kakraliya, S., Jat, Hanuman Sahay, Sidhu, Harminder Singh, Sharma, Parbodh Chander, Jat, Mangi Lal, Sapkota, Tek Bahadur

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Non-naivety in a long-lived ungulate : learning effects of shooting moose calves? by Graf, Lukas

“…Female moose increased nocturnal activity and increased their avoidance of open habitats. As they aged, female moose decreased their movement rates and avoided open habitats. …”

COVID-19 and rural-urban poverty in developing countries: Lessons learned, remained questions by Thurlow, James

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The influence of trust in the Nicaraguan Learning Alliance on capacity development of members and other influenced groups by Landmann, Dirk H.

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Ada’a-Liben Woreda Pilot Learning Site diagnosis, program design and atlas by International Livestock Research Institute

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National Advisory and Learning Committee (NALC) workshop report, 15-17 March 2006 by International Livestock Research Institute

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Thirty years learning to improve rainwater and land management in the Blue Nile basin of Ethiopia by International Livestock Research Institute, International Water Management Institute

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Learning from the past: Rainwater management in smallholder crop-livestock systems of the Volta basin by Douxchamps, Sabine

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Lessons learned over the course of the GAAP 2 project (2016–2018): Synthesis report by Mulema, Annet A.

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Sweetpotato seed systems community of practice – what are we learning? What are we practicing? by International Potato Center

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Key learnings about how to improve wheat/crop-livestock systems (North Africa) by CGIAR Research Program on Wheat

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Agrifood Chain Toolkit: Online value chain knowledge clearing house and learning platform by Cadilhon, Joseph J.

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Monitoring, evaluating and learning for education and extension—A framework for Index Based Livestock Insurance by St. Claire, Mallory, Banerjee, Rupsha R.

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