Resultados de búsqueda - "Artificial Intelligence"

Capacity building in livestock breeding and genetic improvement in achieving UN Sustainable Development Goals for Africa por Tiambo, Christian K., Opoola, O., Okpeku, M., Houaga, I., Touko, B.A.H., Dessie, Tadelle

“…Key capacity building intervention areas needing attention are: (1) Conservation and restoration of local animal genetic diversity, their improvement and dissemination of elite locally adapted and farmers-preferred genetics, and preservation of their natural habitat; (2) Demand-led capacity development in modern livestock breeding techniques; (3) Sustainable intensification of livestock farming practices; (4) Adaptation to extreme environmental conditions and livestock emergency guidelines and standards (LEGS); (5) Breeding for animal welfare, adaptability, and biosafety; (6) Big Data and artificial intelligence for smart farming and livestock breeding programmes; and (7) Infrastructural development and policies’ integration for technology uptake.…”
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Initial evaluation of models to predict methane production based on VIS-NIR signatures captured in the field por Gonzalez Guzman, Juan Jose, Penafiel, Jorge, Cardoso, Juan Andres, Lopez, Diana Carolina, Jones, Chris, Jauregui, Rosa, Sanchez, Miguel, Marin, Alejandra, Wenzl, Peter, Arango, Jacobo

“…The spectral data are analyzed using a Random Forest artificial intelligence model, which identifies complex patterns and determines the spectral regions that contribute most to the nutritional variability of the samples. …”
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AgWise: Modular decision support tools integrating data, models, and AI for site-specific agronomy and soil health management recommendations por Abera, Wuletawu, Mkuhlani, Siyabusa, Tibebe, Degefie, Assefa, Feben, Leroux, Louise, Seid, Jemal, Srivastava, Amit, Aguilar Ariza, Andres, Devkota Wasti, Mina, Ibrahim, Ali, Kouadio, Louis, Liben, Feyera, Llanos Herrera, Lizeth, Cherenet, Meklit, Corbeels, Marc, Kihara, Job, Vanlauwe, Bernard

“…Rather than treating artificial intelligence as a stand-alone solution, AgWise is designed as an embedded decision intelligence system that integrates agronomic science, data, models, expert knowledge, and AI within a single, coherent framework. …”
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A Protocol for a Systematic Review of CGIAR’s Research (2012-2023) on Climate-Induced Extreme Rainfall and Floods por Chikozho, C., Managa L.R., Kujinga, K., Bosire, Caroline K., Mukherji, Aditi

“…During the review and synthesis process, data will be extracted using artificial intelligence software, and a codebook will be developed to ensure consistency and reproducibility. …”
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Kan artificiell intelligens ersätta den framtida revisorn? : en studie om hur digitaliseringens effekter kan tänkas påverka revisorns roll por Krämbring, Amanda Josephine, Kähkönen, Tuulia

The global distribution and drivers of wood density and their impact on forest carbon stocks por Mo, Lidong, Crowther, Thomas W., Maynard, Daniel S., van den Hoogen, Johan, Ma, Haozhi, Bialic-Murphy, Lalasia, Liang, Jingjing, de-Miguel, Sergio, Nabuurs, Gert-Jan, Reich, Peter B., Peri, Pablo Luis, Zohner, Constantin M.

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Evaluación de modelos de aprendizaje automático para la predicción de Boro en suelos Andisoles de Nariño-Colombia por Álvarez Sánchez, David, López Estrella, Xilena, Manso Ordoñez, Eduar, López Rivera, Laura, Rodriguez Valenzuela, Jeison

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Tecnologías emergentes para el agro y su aplicación en Colombia por Ovalle Másmela, Juan Camilo, Romero Perdomo, Felipe Andrés, Uribe Galvis, Claudia Patricia

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Digital data and tools for managing agriculture: focusing on earth observation data and climate change por Ghosh, Surajit, Mallick, A., Dawn, A., De Sarkar, K., Chowdhury, A., Kour, S., Ghosh, A., Holmatov, Bunyod

“…Through various sessions, the workshop highlighted concerns about GHG emissions and their mitigation by transitioning to renewable energy, carbon capture and storage, water hyacinth mapping in urban and peri-urban wetlands, Artificial Intelligence/Machine Learning (AI/ML) applications for rice mapping, flood damage assessment, maternal, infant and young children nutrition deficit under extreme weather conditions, agricultural data collection tools and sustainable agriculture practices. …”
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Global patterns and environmental drivers of forest functional composition por Bouchard, Elise, Searle, Eric B., Drapeau, Pierre, Liang, Jingjing, Gamarra, Javier G.P., Abegg, Meinrad, Alberti, Giorgio, Almeyda Zambrano, Angélica M., Alvarez-Davila, Esteban, Alves, Luciana F., Peri, Pablo Luis, Paquette, Alain

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Adaptación y mitigación al cambio climático. Inteligencia artificial. septiembre 2023

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The Lancet One Health Commission: harnessing our interconnectedness for equitable, sustainable, and healthy socioecological systems por Winkler, A.S., Brux, C.M., Carabin, H., Neves, C.G. das, Häsler, B., Zinsstag, J., Fèvre, Eric M., Okello, A., Laing, G., Harrison, W.E., Pöntinen, A.K., Huber, A., Ruckert, A., Natterson-Horowitz, B., Abela, B., Aenishaenslin, C., Heymann, D.L., Rødland, E.K., Berthe, F.C.J., Capua, I., Sejvar, J., Lubroth, J., Corander, J., May, J., Roth, L.F., Thomas, Lian F., Blumberg, L., Lapinski, M.K., Stone, M., Agbogbatey, M.K., Xiao, N., Hassan, O.A., Dar, O., Daszak, P., Guinto, R.R., Senturk, S., Sahay, S., Samuels, T.A., Wasteson, Y., Amuasi, J.H.

“…The consensus around One Health that has been built by the One Health Quadripartite and OHHLEP, which has been reinforced by this Commission, is essential for addressing the threats to health posed by infectious diseases, AMR, NCDs, and planetary crises; harnessing data and artificial intelligence for disease surveillance and health-care delivery; forging equitable partnerships and inclusive collaborations; and generating necessary insight into socioecological interconnection. …”
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La convergencia disciplinar potencia el valor de los datos agronómicos por Tallarico, Gabriela Adriana

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Primer Boletín Sectorial : tecnologías emergentes del sector agropecuario por Ovalle Másmela, Juan Camilo, Zambrano Muñoz, Adriana Del Pilar, Gómez Contreras, Luz Mery, Salazar García, Adriana Marcela, Acevedo Silva, William Fabian, Flórez Martínez, Diego Hernando, Uribe Galvis, Claudia Patricia

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Using vis-NIRS and Machine Learning methods to diagnose sugarcane soil chemical properties por Delgadillo Durana, Diego A., Vargas García, Cesar A., Varón Ramíreza, Viviana M., Calderón, Francisco C., Montenegroa, Andrea C., Reyes Herreraa, Paula H.

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Vigilancia científica sobre procesos de gestión de información agroclimática por Cárdenas Solano, Leidy Johanna, Contreras Pedraza, Carlos Alberto

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Development of multistakeholder scenarios of secondary forest management: a multiagent system simulation approach por Purnomo, H., Priyadi, H., Yasmi, Yurdi, Yuliani, L., Prabhu, Ravi

“…MAS is a branch of artificial intelligent for creating artificial society used for social simulation. …”
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Desarrollo y escalamiento de bioplaguicidas por Díaz García, Andrés, Gómez Álvarez, Martha Isabel, Grijalba Bernal, Erika Paola, Santos Diaz, Adriana Marcela, Cruz Barrera, Fredy Mauricio, León Moreno, Diana Marcela, Alarcón Torres, Érika Andrea, Cotes Prado, Alba Marina

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