Accurate and economically sound soil fertility recommendations are critical for ensuring profitable food production for smallholder farmers. However, such recommendations are lacking in many...
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Crop yield machine learning
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...
Highlights:
Estimating durum wheat yields in Algeria using climate records;
A forecasting process using machine learning in the presence of data scarcity;
Data augmentation by...
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...
Forecasting crop yields is important for food security, in particular to predict where crop production is likely to drop. Climate records and remotely-sensed data have become instrumental...