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Highlights: AI enhances aquaculture efficiency, boosting food production sustainably. Precision aquaculture with AI optimizes resource usage for higher yields. Automated monitoring ensures...

Highlights: Determine the prevalence of malnutrition among women in Bangladesh. Identification of the risk factors of malnutrition using logistic regression. Prediction of malnutrition based on machine learning approach...

Background Most of the 10 million Kenyans lacking food security lived in the arid and semi-arid northern part of the country in a climatic condition of high temperatures and very little...

Motivated by the deterioration in global food security conditions, this paper develops a parsimonious machine learning model to derive a multi-year outlook of global severe food insecurity from macro-economic...

This paper explains the collaboration of the World Food Programme (WFP) and esteemed partners, including the University of Oxford, IGAD Climate Prediction and Applications Centre (ICPAC), Kenya Meteorological...

Highlights: A Food Security Identification (FSI) roadmap is proposed for the development of a multi-dimensional food security index. The roadmap employs a machine learning approach towards identifying regions...

Accurate and economically sound soil fertility recommendations are critical for ensuring profitable food production for smallholder farmers. However, such recommendations are lacking in many...

High crop yield variation between years—caused by extreme shocks on the food production system such as extreme weather—can have substantial effects on food production. This in turn...

Highlights: Predicting performance of hybrids prior to field evaluation is a challenging problem. We developed machine learning models to estimate performance of untested hybrids. The...

Highlights: Collection and labelling of datasets in close supervision of plant pathologist. Employing K-Means algorithm for segmentation of region of interest. Using severity scale for estimation of...