Resultados de búsqueda - "learning"

Impact of hygienic milk production training on knowledge, attitudes and practices of women farmers in the central highlands of Ethiopia por Keba, Abdi, Tola, A., Kaylegian, K.E., Kebede, M., Zewdu, A.

“…The 3-day curriculum was delivered using theoretical lecturing, video presentation, practical activities, and handouts, and learning was assessed with a questionnaire and checklist. …”
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Capacities of local maize seed enterprises in Mexico: Implications for seed systems development por Donovan, Jason, Rutsaert, Pieter, Domínguez, Ciro, Peña, Meliza

“…Overall, maize SMEs showed high levels of absorptive capacity for seed production, but limited signs of learning and innovation in terms of business organization and strategic seed marketing. …”
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Optimizing Rice Crop Manager Odisha: AI-Driven Yield Prediction to compliment Extension using legacy data por Gakhar, Shalini, Bharti, Preeti

“…To leverage legacy data effectively, machine learning algorithms have been integrated into RCM to identify key factors influencing crop outcomes and assist in estimating target yields. …”
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Nurturing care in the first 10 years of life: Results from a Vietnamese longitudinal study por Tran, Lan Mai, Stein, Aryeh D., Nguyen, Phuong Hong, Young, Melissa F., Ramakrishnan, Usha

“…This study explored five NC dimensions (health, nutrition, safety/security, learning, and relationships) using prospectively collected data from 1040 mother–child dyads in a birth cohort conducted in Vietnam from 2011 to 2023. …”
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Digital descriptors sharpen classical descriptors, for improving genebank accession management: A case study on Arachis spp. and Phaseolus spp. por Conejo-Rodriguez, Diego Felipe, Gonzalez-Guzman, Juan Jose, Ramirez-Gil, Joaquín Guillermo, Wenzl, Peter, Urban, Milan

“…High-throughput phenotyping brings new opportunities for detailed genebank accessions characterization based on image-processing techniques and data analysis using machine learning algorithms. Our work proposes to improve the characterization processes of bean and peanut accessions in the CIAT genebank through the identification of phenomic descriptors comparable to classical descriptors including methodology integration into the genebank workflow. …”
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Multi-temporal passive and active remote sensing for agricultural mapping and acreage estimation in context of small farm holds in Ethiopia por Mengesha, Tesfamariam Engida, Desta, Lulseged Tamene, Gamba, Paolo, Ayehu, Getachew Tesfaye

“…The study was conducted by integrating data from the optical and radar sensors of sentinel products. Supervised machine learning algorithms such as Support Vector Machine, Random Forest, Classification and Regression Trees, and Gradient Boost were used to classify the study area into five first-class common land use types (built-up, agriculture, vegetation, bare land, and water). …”
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Designing a contextualized food-based strategy to improve the dietary diversity of children in rural farming households in Central Uganda por Nabuuma, Deborah, Ekesa, Beatrice, Faber, Mieke, Mbhenyane, Xikombiso

“…The strategy focused on household groups for learning, demonstration, practice, and social support. …”
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Uganda: Systematic analysis of world market and domestic production shocks por Mukashov, Askar, Jones, Eleanor, Thurlow, James

“…A country-specific, economywide Computable General Equilibrium (CGE) model then simulates the impacts of these shocks on both total and sector-specific economic outcomes, deriving changes in poverty and undernourishment for each shock scenario. Finally, machine learning techniques are applied to obtain metrics for the relative im portance of different risk factors. …”
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The political economy of large-scale food fortification in West Africa: Pathways toward harmonization por Resnick, Danielle

“…At the same time, incoherent trade, tax, and macroeconomic policies in a context of multiple shocks and crises, protectionist impulses aimed at building up domestic agro-industries, lack of financial commitment to LSFF structures in the absence of donor support, and uneven financial contributions to ECOWAS and WAHO remain barriers to progress. Learning from these lessons and considering how to address LSFF from a holistic perspective that accounts for West Africa’s unique demographic, economic, and political characteristics will not only benefit extant harmonization efforts in ECOWAS but also help with broader continental alignment on fortification under the African Union’s 2025-2036 food and nutrition security strategy.…”
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Food fight: From plunder and profit to people and planet por Gillespie, Stuart

“…These case studies offer hope that, by organizing, sharing, and learning, we can build a better food future for ourselves and for our children. …”
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Remote sensing approach for detection and attribution of flood inundation, Lower Awash Basin, Ethiopia por Bekele, T. W., Negash, E. D., Asfaw, W., Haile, Alemseged Tamiru

“…We used Sentinel-1 Synthetic Aperture Radar (S-1 SAR) data to detect flood but Sentinel-2 (S-2) optical satellite data to classify land cover by applying a machine learning algorithm. We also used land cover and soil data to generate the Curve Number (CN) map of the study area from 2017 to 2023. …”
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AI-enabled UAV borne hyperspectral imaging for crop-livestock farm management por Sankararao, A.U.G., Rajalakshmi, P., Choudhary, Sunita, Kholova, Jana, Jones, Christopher S.

“…Artificial intelligence and machine learning (AI/ML) approaches can effectively analyze high-dimensional HSI data and extract meaningful insights. …”
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Agrifood system carbon emissions and reduction policy: insights from China and Africa por Li, Xia, Zhang, Yumei, Fan, Shenggen, Ouedraogo, Issa

“…China adopts multi-objective policies promoting green, lowcarbon development, whereas Africa focuses on short-term yield increases with heavy reliance on fertilizers, conflicting with low-carbon objectives. Learning from China could help Africa balance food security, income stability, and environmental sustainability, providing a pathway to achieve both food security and carbon reduction.…”
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Key Determinants Shaping Farmers’ Satisfaction with Site‑Speciϐic Fertilizer Recommendations (SSFR) in Ethiopia por Adimassu, Zenebe, Mesfin, Tewodros, Tibebe, Degefie, Tilaye, Amsalu, Ebrahim, Mohammed, Abera, Wuletawu, Tamene, Lulseged

“…Participation in cluster recommendation units fosters collective learning and enhances satisfaction, while access to affordable and timely SSF recommendation improves implementation and crop yields. …”
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A stepwise approach to facilitate adoption of climate smart practices for smallholder coffee production in Uganda por Mukasa, D., Rusinamhodzi, L., van Asten, P.J.A., Amwonya, D., Sseguya, H., Okiror, F.A., Kirungi, D., Wodada, W., Komakech, V., Margiotta, S., Jassogne, L.

“…Each site served 25–30 farmers through experiential learning. A co-design method ensured farmer involvement in the design, development, and testing for sustainability. …”
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Emboldening equitable climate adaptation: A handbook for field research leaders por Petesch, Patti, Fisher, Eleanor, Hellin, Jon, Echavez, Chona

“…While each strategy touches on the political, as well as technical, aspects of managing this action learning journey, it is the final strategy that engages most directly with upward and downward accountability for equitable outcomes. …”
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Review of CGIAR Management Response System to Independent Evaluations por Hofer, Silke, Leibovici, Didier, Molinari, Marta, Jouini, Ibtissem

“…Aligned with both accountability and learning objectives, the review assessed effectiveness and efficiency of the CGIAR MR system. …”
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Bridging gaps in groundwater: a woman leader led multistakeholder platform experience from Nepal por KC, Sumitra, Khadka, Manohara

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Women in the coffee supply chain: Identifying challenges and opportunities in San Francisco de Opalaca and La Paz, Honduras por Soto, Fernanda, Rodriguez, Rene, Gonzalez, Silvia

“…c. Initiate adaptive learning within companies to achieve sustainable supply chains in different social and productive (or business) contexts. …”
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One Health criteria to support decision-making on antimicrobial resistance interventions por Aluzaite, K., Dione, Michel M., Belay, D., Robotham, J.V., Guitian, J., Chan, Derek, Emes, E., Endalew, Y.G., White, P.J., Ramponi, F., Knight, G.M.

“…By enabling structured comparison of countries’ One Health profiles, the framework also promotes transferability and cross-learning for AMR intervention prioritisation. The authors identify three key themes that influence intervention success in a One Health perspective: i) ecosystem connectivity within and between sectors; ii) systemic societal factors, such as governance, policy and infrastructure; and iii) data availability to inform action. …”
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