Search Results - "Machine Learning"

Global habitat suitability of Spodoptera frugiperda (JE Smith) (Lepidoptera, Noctuidae): key parasitoids considered for its biological control by Tepa-Yotto, Ghislain T., Tonnang, Henri E.Z., Goergen, Georg E., Subramanian, S., Kimathi, E.K., Abdel-Rahman, E.M., Flo, D., Thunes, K.H., Fiaboe, K., Niassy, S., Bruce, A., Mohamed, S.A., Tamo, Manuele, Ekesi, S., Saethre, M.G.

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Reference soil groups map of Ethiopia based on legacy data and machine learning technique: EthioSoilGrids 1.0 by Ali, Ashenafi, Erkossa, Teklu, Gudeta, Kiflu, Abera, Wuletawu, Mesfin, Ephrem, Mekete, Terefe, Haile, Mitiku, Haile, Wondwosen, Abegaz, Assefa, Tafesse, Demeke, Belay, Gebeyhu, Getahun, Mekonen, Beyene, Sheleme, Assen, Mohamed, Regassa, Alemayehu, Selassie, Yihenew G., Tadesse, Solomon, Abebe, Dawit, Walde, Yitbarek, Hussien, Nesru, Yirdaw, Abebe, Mera, Addisu, Admas, Tesema, Wakoya, Feyera, Legesse, Awgachew, Tessema, Nigat, Abebe, Ayele, Gebremariam, Simret, Aregaw, Yismaw, Abebaw, Bizuayehu, Bekele, Damtew, Zewdie, Eylachew, Schulz, Steffen, Tamene, Lulseged D., Elias, Eyasu

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Modeling the spatial distribution of soil organic carbon and carbon stocks in the Casanare flooded savannas of the Colombian Llanos by Martin López, Javier Mauricio, Verchot, Louis V., Martius, Christopher, Silva, Mayesse Aparecida da

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Predictive modeling of nutritional quality in Urochloa pastures from multispectral sensors and images using machine learning approaches by Camelo-Munevar, Rodrigo Andrés, Hernández, Luis Miguel, Jauregui, Rosa, Cardoso Arango, Juan Andrés

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Unveiling Drought-Resilient Pathways: Integrating High Throughput Phenotyping and Multivariate Modeling to Enhance Barley Adaptation to Climate Change by Ouahid, Safae, Backhaus, Anna Elisabeth, Jimenez, José-Antonio, Visioni, Andrea, Sanchez-Garcia, Miguel

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Working women and caste in India: A study of social disadvantage using feature attribution by Joshi, Kuhu, Joshi, Chaitanya K.

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Nowcasting food insecurity interest with google trends data by Caravaggio, Nicola, Carneiro, Bia, Resce, Giuliano

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Estimating elements susceptible to urban flooding using multisource data and machine learning by Asfaw, Wegayehu, Rientjes, T., Bekele, Tilaye Worku, Haile, Alemseged Tamiru

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Leveraging automated machine learning for environmental data-driven genetic analysis and genomic prediction in maize hybrids by He, Kunhui, Yu, Tingxi, Gao, Shang, Chen, Shoukun, Li, Liang, Zhang, Xuecai, Huang, Changling, Xu, Yunbi, Wang, Jiankang, Boddupalli, Prasanna, Hearne, Sarah, Li, Xinhai, Li, Huihui

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Estimating Leaf Area Index of Wheat Using UAV-Hyperspectral Remote Sensing and Machine Learning by Rejith, Rajan G., Sahoo, Rabi N., Ranjan, Rajeev, Kondraju, Tarun, Bhandari, Amrita, Gakhar, Shalini

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ICRISAT and Partners Launch AI-Powered Climate Advisory Initiative to Boost Farmer Resilience by Kumar, Shalander, Subbarao, AVM, Dhulipala, Ram, Kumar; Kishore G., Santanu Bal, Chandran, Sarath

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Soil nutrient maps of Sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learning by Hengl, T., Leenaars, Johan G.B., Shepherd, Keith D., Walsh, Markus G., Heuvelink, Gerard B.M., Mamo, T., Tilahun, H., Berkhout, Ezra D., Cooper, M., Fegraus, E., Wheeler, I., Kwabena, N. A.

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Can remote sensing enable a Biomass Climate Adaptation Index for agricultural systems? by Ferguson, Amy, Murray, Catherine, Tessema, Yared Mesfin, McKeown, Peter C., Reymondin, Louis, Loboguerrero Rodriguez, Ana María, Talsma, Tiffany, Allen, Brenden, Jarvis, Andy, Golden, Aaron, Spillane, Charles

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A protocol for measuring disease resistance to Cassava Bacterial Blight, using machine-learning image analysis by Pardo, Juan Manuel, Jiménez Polo, Jenyfer, Rodríguez, Rafael, Leiva Sandoval, Ana Maria, Cuéllar, Wilmer Jose

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Digitally improving the identification of aquatic macroinvertebrates for indices used in biomonitoring by Koen, R. C. J., Koen, F. J., Pattinson, N. B., Dickens, Chris W. S., Graham, P. M.

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Crop mapping in smallholder farms using unmanned aerial vehicle imagery and geospatial cloud computing infrastructure by Gokool, S., Mahomed, M., Brewer, K., Naiken, V., Clulow, A., Sibanda, M., Mabhaudhi, Tafadzwanashe

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Predicting poverty and malnutrition for targeting, mapping, monitoring, and early warning by Mcbride, Linden, Barrett, Christopher B., Browne, Christopher, Hu, Leiqiu, Liu, Yanyan, Matteson, David S., Sun, Ying, Wen, Jiaming

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Remote sensing and machine learning for food crop production data in Africa post-COVID-19 by Ly, Racine, Dia, Khadim, Diallo, Mariam A.

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Multivariate random forest prediction of poverty and malnutrition prevalence by Browne, Chris, Matteson, David S., McBride, Linden, Hu, Leiqiu, Liu, Yanyan, Sun, Ying, Wen, Jiaming, Barrett, Christopher B.

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Research-policy linkages: Empirical evidence from agroeconomic research in India by Balaji, S. J., Babu, Suresh Chandra, Pal, Suresh

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