To enhance the resilience of food systems to food safety risks, it is vitally important for national authorities and international organizations to be able to identify early signals of emerging...
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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...
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...
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
Agriculture 4.0 comprises radical digital and biotechnological innovations.
Agriculture 4.0 may have pervasive effects on future agricultural and food systems.
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This paper presents the first global picture of food security at a subnational level based on the Food Insecurity Experience Scale, the indicator for the Sustainable Development Goal of “Zero Hunger”...
We use a 4-year panel (2019–2022) of 10,125 village councils in Ukraine to estimate effects of the war started by Russia on area and expected yield of winter crops aggregated...