The study sheds light on the widespread use of CPS in crop management, smart greenhouses, precision irrigation, livestock ...

The era of predictive modeling enhanced with machine learning and artificial intelligence (AI) to aid clinical ...

A team of researchers has turned the keen eye of AI toward agriculture, using deep learning algorithms to help detect crop disease before it spreads.

A novel genotype-by-environmental interaction machine-learning model can predict crop yield with environmental data and genetic information more efficiently and accurately than an established model.

By applying machine learning algorithms such as logistic regression, the system provides early warnings to authorities, aiming to reduce agricultural and environmental losses.

In a new breakthrough, researchers in the United States and Taiwan have developed a machine learning algorithm to more efficiently identify "genes of importance" in agriculture and medicine.

Ahmedabad: Good soil health and disease-free crops are crucial for agricultural productivity on which the economy depends as does global food security.

Machine vision is the newest weapon against crop loss Like Terminator for weeds, precision ag combines computer vision, robots, and AI to get crops right.

Using the app, the farmer snaps a photo at a specific part of the plant, and the machine learning algorithms analyze the image to determine whether the damage to the plant is from fall armyworm.