Search Results - "learning"

From gender gaps to gender-transformative climate-smart agriculture by Huyer, Sophia, Loboguerrero Rodriguez, Ana María, Chanana, Nitya, Spellman, Olga

“…Agricultural intervention approaches have largely ignored women as agents of change [5••] as well as their capacity for — and learning in relation to — climate change adaptation, so that the root causes underpinning climate-related vulnerability persist 6, 7•, 8••. …”
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Identifying and measuring the effectiveness of socio-technical innovation bundles on empowerment and resilience in Kenya: A baseline report by Ayuya, Oscar Ingasia, Jong, Arnold Otieno, Alworah, Getrude Okutoyi, Lutomia, Cosmas Kweyu, Nchanji, Eileen Bogweh, Waswa, Boaz Shaban, Ooro, Patrick, Muriithi, Catherine, Njiru, Emerita, Ouya, Fredrick Ochieng'

“…Improved seed, farmer training, and group membership were the most used STIBs by farmers (9 farmers out of 499 STIBs adopters) across the learning labs. Majority of the STIBs were reported women (69%) and UU farmers (71%). …”
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Evidence on trends in wellbeing of rural Ethiopian households during the COVID-19 pandemic by Alderman, Harold, Gilligan, Daniel O., Hidrobo, Melissa, Leight, Jessica, Taffesse, Alemayehu Seyoum, Tambet, Heleene

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Evaluation of alternative school feeding models on nutrition, education, agriculture and other social outcomes in Ghana: Rationale, randomised design and baseline data by Gelli, Aulo, Masset, Edoardo, Folson, Gloria, Kusi, Anthony, Arhinful, Daniel K., Asante, Felix, Ayi, Irene, Bosompem, Kwabena M., Watkins, Kristie, Abdul-Rahman, Lutuf, Agble, Rosanna, Anase-Baden, Gertrude, Mumuni, Daniel, Aurino, Elisabetta, Fernandes, Meena, Drake, Lesley

“…Primary outcomes include child health and nutritional status, school participation and learning, and smallholder farmer income. Intermediate outcomes along the agriculture and nutrition pathways will also be measured. …”
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Climate Risk Management for Agricultural Extension: Processes, Experiences, And Lessons Learnt from Ethiopia by Belay, Berhanu, Amha, Yosef, Ambaw, Gebermedihin, Demissie, Teferi, Solomon, Dawit

“…Overall, the established collaboration facilitates the development of diverse learning materials, innovative teaching methods, and interdisciplinary curricula that can effectively engage trainees of all ages and backgrounds. …”
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Report on the 2023 review and 2024 activity planning workshop of the CGIAR initiative on agroecology project by Ouattara, Songdah Désiré, Orounladji, Michel, Sib, Ollo

“…It supports the application of agroecological principles in food, land and water management systems, working towards the codevelopment and implementation of agroecological innovations throughout the food system. To facilitate co-learning and co-development, the Initiative on Agroecology is establishing an international network of Agroecological Living Landscapes (ALL). …”
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Nature-based solutions for human and environmental resilience: the case of Dolo Ado and Bokolmayo districts, Somali Regional State, Ethiopia by Mekuria, Wolde, Moges, A., Girma, R., Yakob, G., Teshale, T., Haile, Alemseged Tamiru, Ruckstuhl, Sandra

“…We offered key recommendations for future actions in the areas of coordination and active participation of stakeholders, capacity building and learning, natural resources management, empowerment of local communities, enforcement of existing policies, the use of adaptive management tools and approaches, and financing mechanisms of NbS. …”
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Closing yield gaps in Ethiopia: Leveraging data-driven approaches to optimize fertilizer use and soil health by Tamene, Lulseged, Mesfin, Tewodros, Tibebe, Degefie, Abera, Wuletawu, Desta, gizaw, Liben, Feyera, Agegnehu, Getachew, Tigabie, Abiro, Legesse, Gizachew, Chernet, Meklit, Ebrahim, Mohammed, Tilaye, Asmalu, Tesfu, Daniel, Desalegne, Temesgen, Yitafferu, Birru, Gashaw, Getachew, Bekele, Hawinet, Ayele, Kebede, Endrias, Abrham

“…Leveraging advanced agricultural data, big data analytics, and machine learning, the Alliance of Bioversity and CIAT, along with ICRISAT and key partners, have developed and piloted advanced decision support tools (DSTs). …”
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The Compound Risk Framework: Assessing fragility and key drivers of food insecurity in Haiti, Mozambique and Ghana by Minoarivelo, Onivola Henintsoa, Craparo, Alessandro, Basel, Ashleigh Megan, Nguyen, Kien Tri, Ouedraogo, Yacouba, Douglas, Wesley, Melly, Brigitte, Dao, Hoa, Carneiro, Bia, Pacillo, Grazia, Laderach, Peter

“…The framework offers a holistic perspective on compound risk assessment by drawing on comprehensive data sources, FEWS NET analyses, and employing advanced techniques, such as natural language processing, digital platform monitoring and supervised machine learning algorithms. The geographic focus of this report is three fragile and conflict-prone countries: Mozambique, Haiti and Ghana.…”
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Synergistic use of Sentinel-1 and Sentinel-2 data for Fall Armyworm infestation detection and mapping in maize croplands by Dzurume, Tatenda, Darvishzadeh, Roshanak, Dube, Timothy, Amjath-Babu, T.S., Billah, Mutasim, Syed Nurul Alam, Kamal, Mustafa, Harun-Or-Rashid, Md., Biswas, Badal Chandra, Uddin, Md. Ashraf, Md. Abdul Muyeed, Rahman Shah, Md Mostafizur, Krupnik, Timothy Joseph, Nelson, Andrew

“…Synthetic Aperture Radar backscatter values, spectral reflectance profiles, and eight vegetation indices were extracted from the Sentinel data and analysed using non-parametric statistical tests to identify differences between infested and non-infested fields. Machine learning models, specifically Random Forest - and Support Vector Machine, were then used to classify infestation severity based on five model input data combinations: (i) Sentinel-1, (ii) Sentinel-2, (iii) Sentinel-2 with vegetation indices, (iv) Sentinel-1 and Sentinel-2, and (v) Sentinel-1, Sentinel-2, and vegetation indices. …”
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Workshop on applied policy research for scaling innovations in Uzbekistan’s agri-food sector by Akramov, Kamiljon T., Akhramkhanov, Akmal, Gafurov, Zafar, Egamberdieva, Dilfuza, Rajiv, Sharanya, Dosov, Botir

“…Discussions emphasized the importance of embedding dynamic Monitoring, Evaluation, Learning, and Impact Assessment (MELIA) systems into policy and program cycles to enable adaptive decision-making, accountability, and timely course correction. …”
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Community engagement through Hub model approach for local consensus building for scaling agricultural recommendations at subnational levels by Van Loon, Jelle, Fonteyne, Simon, García Santiago, Jorge Octavio, Espinosa Diaz, Anabell Guadalupe, Guera, Ouorou Ganni Mariel, Ovando, Rausel, Jiménez, Benancio, May Tzun, Vladimir Nikolai, González Regalado, Jessica, Vilchis Ramos, Rodolfo, Pérez García, Mariana, García, Ana Rosa

“…The results reinforce the core premise of the Scaling for Impact program: impact at scale is the outcome of intentionally designed and managed scaling pathways that connect science, actors and territories through continuous learning, multi-stakeholder coordination and evidence-based decision-making.…”
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Agricultura guiada por datos para maíz en Chiapas, México y altiplano occidental de Guatemala by Navarro Racines, Carlos, Jaimes, Diana, Llanos, Lizeth, Estrada, Oscar, Barrios, Camilo, Agudelo, Diego, Jimenez, Daniel, Gardeazabal, Andrea, Dorado, Hugo, Ramirez Villegas, Julian

“…This presentation introduces a data-driven agriculture approach for maize production, integrating climatic, soil, and agronomic management data through data mining and machine learning techniques. Using more than 4,500 production records from Chiapas, Mexico, and 6,500 observations from smallholder maize plots in the western highlands of Guatemala, Random Forest models were applied to identify key yield-determining factors and their interactions. …”
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Experiences with the use of participatory approaches in highly pathogenic avian influenza (HPAI) surveillance by Jost, Christine, Bloland, P., Busuulwa, M., Munstermann, S., Okuthe, S., Parmley, J., Pfeiffer, Dirk U., Pissang, C., Soumare, B., Mariner, Jeffrey C.

“…By emphasizing the importance of farmers’ knowledge and experience, participatory disease surveillance (PDS) is an approach that helps VS to address this gap. It is a process of learning and discovery that fosters better cooperation and understanding between veterinary professionals and farmers. …”
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Performance of innovation platforms in crop-livestock agro-ecosystems of the Volta basin in Burkina Faso by Ayantunde, Augustine A., Swaans, Cornelis P.M., Some, Hubert W., Pali, Pamela N., Douxchamps, Sabine, Ouattara, K.

“…The CPWF Volta Basin Development Challenge project on integrated management of rainwater in crop-livestock systems (V2) took an overarching innovation platform approach that supports learning and exchange for action research and for scaling up and out of promising best fit rainwater management strategies. …”
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Participatory groundwater management at village level in India – empowering communities with science for effective decision making by Jadeja, Y., Maheshwari, B., Packham, R., Hakimuddin, Purohit, R., Thaker, B., Goradiya, V., Oza, S., Dave, S., Soni, P., Dashora, Y., Dashora, R., Shah, Tushaar, Gorsiya, J., Katara, P., Ward, J., Kookana, R., Dillon, P.J., Prathapar, Sanmugam A., Chinnasamy, Pennan, Varua, M.

“…This approach has highlighted important learning that can be replicated in other parts of the two states and beyond. …”
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Approaches to reinforce crop productivity under rain-fed conditions in sub-humid environments in Sub-Saharan Africa by Chikowo, Regis, Zingore, Shamie, Nyamangara, Justice, Bekunda, Mateete A., Messina, Joseph, Snapp, Sieglinde S.

“…Finally, an approach that can be used for co-learning with farmers on soil fertility management principles for risk management is presented. …”
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Las instituciones públicas de ciencia y tecnología en la producción agroalimentaria argentina y la variedad no transgénica de arroz tolerante a herbicidas en Entre Ríos by Sanchez, Guillermo

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El hacer grupal como práctica agroecológica by Dussi, María Claudia, Barrionuevo, Myriam Elisabeth, Gómez, Eugenia, Flores, Liliana Beatriz, Zon, Karina Daniela

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Fruitful controversies in sustainable livestock production: beyond the intensive versus extensive livestock polarization in nonforest ecosystems by Litre, Gabriela, Lagrange, Sebastian Pablo, Arbeletche, Pedro, Champredonde, Marcelo, Bolletta, Andrea Ivana

“…Through a mix of literature review and the results of original field research in the grasslands of Argentina and Uruguay, this chapter aims at overcoming the frequently polarizing discourses generated by the “extensive versus intensive” beef production debate by learning from the analysis of fruitful controversies. …”
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