Resultados de búsqueda - Open learning.

Researcher-implementer partnerships for learning and impact: Lessons from IFPRI's experiences with nutrition-sensitive programming por Bliznashka, Lilia, Sproule, Katie

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

“…Replicated trials using randomized complete block design were established on farmers’ fields Farm management history, grain, straw, biomass, fertilizer and grain prices data were collected using Open Data Kit (ODK) tools and analysed using R statistical package. …”
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Assessing land suitability for leguminous crops in the okavango river basin: A multicriteria and machine learning approach por Negussie, Kaleb Gizaw, Gebrekidan, Bisrat Haile, Wyss, Daniel, Kappas, M.

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Tester selection for combining ability estimation of storage root yield and sweetpotato virus disease in sweetpotato breeding por Swanckaert, J., Santos, I.G.D., Chaves, S.F.S., Ssali, R.T., Mwanga, R.O.M., Azevedo, C.F., Mendes, T., Boeck, B. de, Eyzaguirre, R., Kitavi, M., Gemenet, D., Andrade, M.I., Grüneberg, W.J., Lindqvist-Kreuze, H., Yencho, George Craig, Campos, Hugo, Silva Pereira, G. da

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DNNGP, a deep neural network-based method for genomic prediction using multi-omics data in plants por Wang, Kelin, Abid, Muhammad Ali, Awais Rasheed, Crossa, José, Hearne, Sarah Jane, Huihui Li

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Advanced Prediction of Rice Yield Gaps Under Climate Uncertainty Using Machine Learning Techniques in Eastern India por Sahoo, Satiprasad, Singha, Chiranjit, Govind, Ajit

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Climate Governance and Agriculture in Southeast Asia: Learning From a Polycentric Approach por Fasting, Siw, Bacudo, Imelda, Damen, Beau, Dinesh, Dhanush

“…The Paris Agreement has opened up room for this type of bottom-up, polycentric governance and new attention to important issues such as agriculture. …”
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Roads & SDGs, tradeoffs and synergies: learning from Brazil’s Amazon in distinguishing frontiers por Pfaff, Alexander, Robalino, Juan, Reis, Eustaquio J., Walker, Robert, Perz, Stephen, Laurance, William, Bohrer, Claudio, Aldrich, Steven, Arima, Eugenio, Caldas, Marcellus, Kirby, Kathryn R.

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Foresight for income and employment: What can we learn for agricultural research for development por Kruseman, Gideon K., Dermawan, A., Diagne, M., Enahoro, Dolapo K., Frija, A., Gatto, M., Gbegbelegbe, Sika, Komarek, A.M., Mausch, K., Mottaleb, K., Nedumaran, S., Tesfaye, K., Valera, Harold Glenn

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Revitalizing rural China: What lessons can be learned from international experiences? por Fan, Shenggen

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What can be learned from economic transformation and agricultural transition experiences in MENA? por Nin-Pratt, Alejandro

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Learning to Implement and Scale-Up Multiple-Use Water Services at the Community Level por CGIAR Challenge Program on Water and Food

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IPMS commodity gender fact sheet, Ada’a pilot learning woreda por International Livestock Research Institute

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IPMS HIV/AIDS fact sheet, Ada’a pilot learning woreda por International Livestock Research Institute

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IPMS environmental assessment and screening report, Ada’a pilot learning woreda por Campbell, I.

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TRIPLE S: Why participatory testing and local adaptation is critical – learning from Ethiopia por International Potato Center

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Village land use planning in rangelands in Tanzania: Good practice and lessons learned por Flintan, Fiona E.

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My Learning Experience from the Norman E. Borlaug International Dialogue, Idaho por Ngurumwa, P.

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IFPRI-LCSP Newsletter, February 2007: Learning and Capacity Strengthening Program (LCSP) por International Food Policy Research Institute

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IFPRI-LCSP Newsletter, August 2006: Learning and Capacity Strengthening Program (LCSP) por International Food Policy Research Institute

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