Resultados de búsqueda - "learning"

Accuracy of a smartphone-based object detection model, PlantVillage Nuru, in identifying the foliar symptoms of the viral diseases of cassava-CMD and CBSD por Mrisho, L., Mbilinyi, N., Ndalahwa, M., Ramcharan, A., Kehs, A.K., McCloskey, P., Murithi, H., Hughes, D.P., Legg, James P.

“…Nuru is a deep learning object detection model for diagnosing plant diseases and pests developed as a public good by PlantVillage (Penn State University), FAO, IITA, CIMMYT, and others. …”
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Gender Outcomes Harvesting in Climate Change, Agriculture and Food Security: A meta-analysis por Verzosa, Fatima, Gonsalves, Julian Francis, Barbon, Wilson John, Monville-Oro, Emilita

“…Gender outcome harvesting shifts the focus on the changes that impact on women and men from the use of CSA technologies, practices, and social learning practices. The report presents gender outcomes and insights from 69 reports conducted in these five countries with findings validated by studies done in other CSVs elsewhere, covering a range of women’s concerns that include an analysis of their gender roles are determinants or barriers to empowerment, gendered impacts of climate change, male migration, literacy, and the COVID-19 pandemic. …”
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NIR instruments and prediction methods for rapid access to grain protein content in multiple cereals por Chadalavada, K., Anbazhagan, K., Ndour, A., Choudhary, S., Palmer, W., Flynn, J.R., Mallayee, S., Sharada, Pothu, Prasad, Kodukula V.S.V., Varijakshapanicker, Padmakumar, Jones, Christopher S., Kholová, Jana

“…We explored classical deterministic methods (via winISI, FOSS), novel machine learning (ML)-driven methods (via Hone Create, Hone), and a convolutional neural network (CNN)-based method for building the calibrations to predict grain protein out of the NIR spectra. …”
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A bibliometric analysis of solar energy forecasting studies in Africa por Zwane, N., Tazvinga, H., Botai, C., Murambadoro, M., Botai, J., Wit, J. de, Mabasa, B., Daniel, S., Mabhaudhi, Tafadzwanashe

“…Three emerging topics were identified from the thematic map analysis— namely, “solar irradiance”, “artificial intelligence” and “clear sky”, which implies that researchers are paying attention to solar irradiance, using modelling techniques that incorporate machine learning techniques. Overall, this study contributes to scientific information on the potential bankability of renewable energy projects that could assist power utilities, governments and policymakers in Africa to enforce the green economy through accelerated decarbonisation of the energy systems and building relationships with developed countries for support and better transitioning to solar energy. …”
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Ecosystem service valuation along landscape transformation in Central Ethiopia por Assefa Biratu, Abera, Bedadi, Bobe, Gebreyohannis, Solomon Gebrehiwot, Melesse, Assefa M., Hordofa Nebi, Tilahun, Abera, Wuletawu, Tamene, Lulseged D., Egeru, Anthony

“…Maximum likelihood classifier and cellular automata artificial neuron network (CA-ANN) models that integrate the module for land use change evaluation (MOLUSE) were used to classify and predict LULC. The CA-ANN model learning and validation was employed to predict LULC of 2031 and 2051. …”
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Novel insights into factors associated with yield response and nutrient use efficiency of maize and rice in sub-Saharan Africa. A review por Zingore, S., Adolwa, Ivan S., Njoroge, Samuel M., Johnson, J.M., Saito, Kazuki, Phillips, S., Kihara, Job Maguta, Mutegi, J., Murell, S., Dutta, S., Chivenge, Pauline P., Amouzou, K.A., Oberthür, Thomas, Weldesemayat, G.

“…Explorative analysis using machine learning algorithms provided further insights into the possible interaction of agroecology, soil type, and exchangeable cations on the spatial variability in yield responses to N, P, and K in maize and rice. …”
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Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms por Tramontana, Gianluca, Jung, Martin, Schwalm, Christopher R., Ichii, Kazuhito, Camps-Valls, Gustau, Ráduly, Botond, Reichstein, Markus, Arain, M. Altaf, Cescatti, Alessandro, Kiely, Gerard, Merbold, Lutz, Serrano-Ortiz, Penelope, Sickert, Sven, Wolf, Sebastian, Papale, Dario

“…In this study, we performed a cross-validation experiment for predicting carbon dioxide, latent heat, sensible heat and net radiation fluxes across different ecosystem types with 11 machine learning (ML) methods from four different classes (kernel methods, neural networks, tree methods, and regression splines). …”
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Assessing the application of gender perspectives in land restoration studies in Ethiopia using text mining por Abera, Wuletawu, Tamene, Lulseged D., Mekonnen, Dawit Kelemework, Estrada-Carmona, Natalia, Elias, Marlène, Joshi, Deepa, Aynekulu, Ermias

“…Through analyzing 314 peer-reviewed scientific articles on land restoration initiatives and studies for Ethiopia published between 1985 and 2020, we aimed to: i) develop a novel approach that would allow for the semi-automatization of analyzing gender aspects in a large set of scientific documents using machine learning techniques, ii) assessed the current evidence on gender integration in peer-reviewed studies related to RDL, and iii) identified what gender issues are discussed in RDL literature. …”
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How to succeed in implementing community-based breeding programs: Lessons from the field in Eastern and Southern Africa por Haile, Aynalem, Getachew, Tesfaye, Rekik, Mourad, Abebe, A., Abate, Z., Jimma, A., Mwacharo, Joram M., Mueller, J., Belay, B., Solomon, Dawit, Hyera, E., Nguluma, A.S., Gondwe, T., Rischkowsky, Barbara A.

“…From experiential monitoring and learning, their success depends on the following: 1) identification of the right beneficiaries; 2) clear framework for dissemination of improved genetics and an up/out scaling strategy; 3) institutional arrangements including establishment of breeders’ cooperatives to support functionality and sustainability; 4) capacity development of the different actors on animal husbandry, breeding practices, breeding value estimation and sound financial management; 5) easy to use mobile applications for data collection and management; 6) long-term technical support mainly in data management, analysis and feedback of estimated breeding values from committed and accessible technical staff; 7) complementary services including disease prevention and control, proper feeding, and market linkages for improved genotypes and non-selected counterparts; 8) a system for certification of breeding rams/bucks to ensure quality control; 9) periodic program evaluation and impact assessment; and 10) flexibility in the implementation of the programs.…”
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Exploring the potential of mapped soil properties, rhizobium inoculation, and phosphorus supplementation for predicting soybean yield in the savanna areas of Nigeria por Jemo, Martin, Devkota, Krishna, Epule Epule, Terence, Chfadi, Tarik, Moutiq, Rkia, Hafidi, Mohamed, Silatsa, Francis B T, Jibrin, Jibrin Mohamed

“…Soybean yield results from the established trials managed by farmers with four treatments (i.e., the control without inoculation and P fertilizer, Rh inoculation, P fertilizer, and Rh + P combination treatments) were predicted using mapped soil properties and weather variables in ensemble machine-learning techniques, specifically the conditional inference regression random forest (RF) model. …”
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Bundling socio-technical innovations to empower women as partners and drivers of climate change solutions por Nchanji, Eileen, Puskur, Ranjitha, Lutomia, Cosmas Kweyu, Ketema, Dessalegn Molla, Gartaula, Hom Nath, Mukhopadhyay, Prama, Mapedza, Everisto D., Johnstone, Kevin, Barrett, Sam

“…The framework will support the implementation of the learning labs in different agro-ecological and socio-cultural contexts across Africa and Asia.…”
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Information exchange patterns and technology adoption behavior of cattle farmers in the Colombian Amazon por Lienert, Anja, Lippert, Christian, Burkart, Stefan

“…There is a broad consensus that the structure and composition of social networks can affect information flows, learning processes, capabilities, preferences, and decision-making processes and that social networks can both facilitate and impede access to information. …”
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A conceptual framework of living labs for people for sustainable food systems por Habermann, Birgit, Nehring, Ryan, Zhang, Wei, Hettiarachchi, Upeksha, Leñero, Eva Marina-Valencia, Falk, Thomas, Rietveld, Anne M., Woltering, Lennart, Kumar, Praveen, Wang, Xinxin, Zhou, Yunyi, Chen, Kevin Z., Pham, Thuy Thu, Rodríguez, Luz Ángela, Venegas, Martha

“…We draw on specific cases in China, Colombia, Kenya and Vietnam as learning grounds for formulating LL4Ps through locally led innovation processes. …”
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Kenya food systems transformation book por Breisinger, Clemens, Keenan, Michael, Mbuthia, Juneweenex, Njuki, Jemimah

“…It will also spark discussions on food systems transformation among students, researchers, and policymakers to strengthen the science-policy dialogue while also serving as source of learning and inspiration for other countries. We look forward to the Ministry of Agriculture and Livestock Development’s continued collaboration with IFPRI, CGIAR, and other partners in creating research-based policy recommendations that will lead to a brighter, healthier future for all Kenyans.…”
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The evidence mapping of wasting programmes and their impact along the continuum of care for wasting in low- and middle-income countries: A rapid review protocol por Verstraeten, Roosmarijn, Touré, Mariama, Diatta, Dieynab, Huybregts, Lieven, Booth, Andrew, Becquey, Elodie

“…These included capturing, documenting, and learning from implementation experiences, and accelerating equitable program coverage of mother, infant and young child interventions at scale. …”
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Social assistance programs and birth outcomes: A systematic review and assessment of nutrition and health pathways por Leroy, Jef L., Koch, Bastien, Roy, Shalini, Gilligan, Daniel O., Ruel, Marie T.

“…Results: We included 6 evaluations of 4 different cash transfer programs and 1 evaluation of a community-based participatory learning and action program that provided food and cash transfers. …”
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Revising public agricultural support to mitigate climate change por Searchinger, Timothy D., Malins, Chris, Dumas, Patrice, Baldock, David, Glauber, Joseph W., Jayne, Thomas S., Huang, Jikun, Marenya, Paswell

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Combining approaches for systemic behaviour change in groundwater governance por Sanil, Richu, Falk, Thomas, Meinzen-Dick, Ruth S., Priyadarshini, Pratiti

“…At the local level, these include groundwater monitoring and crop water budgeting, combined with experiential learning tools such as games for demand management, and supply side interventions to support water harvesting and recharge. …”
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Ethiopia Alive & Thrive Endline Survey 2014: Health Extension Workers por International Food Policy Research Institute

“…Together, these studies generate answers to one of the major learning objectives for the overall initiative: how A&T interventions achieve their impact. …”
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Decades of building resilient food systems through demand led common bean breeding in Africa por Mukankusi, Clare, Butare, Louis, Nkhata, Wilson, Mamo, Teshale Assefa, Beebe, Stephen, Rubyogo, Jean Claude

“…PABRA’s breeding strategy for decades has been based on a pluralistic partnership model where deliverables are shared responsibilities among the Alliance of Bioversity International and CIAT, (Alliance), National Agricultural Research and Extension Systems (NARES), advanced learning institutions (Universities), consumers, farmers and other bean key stakeholders. …”
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