Machine learning (ML) and artificial intelligence (AI) will give nearly accurate predictions of crop production. Junagadh Agriculture University (JAU) is developing a model using remote sensing ...

AI has the ability to handle complex and nonlinear data effectively, using tools such as machine-learning algorithms to produce precise results for crop yield prediction.

New Michigan State University research found that incorporating in-season water deficit information into remote sensing-based crop models significantly improves corn yield predictions.

As climate change puts greater and greater stressors on crops, precision agriculture – which pursues lower inputs and higher yields – is a booming market, poised to reach nearly $13 billion by the ...

Winemaking giant Treasury Wine Estates has partnered with agtech start-up The Yield and Yamaha to better predict grape yield and improve autonomous crop spraying using robots.

Soil microbiomes provide robust, scalable predictions for crop yields beyond local contexts. A machine learning model using 26 soil bacterial genera predicts up to 37% of global vegetation ...

To reduce the variability in prediction methods will necessitate developing a method based upon the factor (s) responsible for yield reduction. Weed Technology publishes original research and ...

Variance decomposition of the yield projections showed that uncertainty in the projections caused by climate and crop models is likely to change with prediction period, and climate change uncertainty ...