Illinois farmers are increasingly using drones for crop scouting, pest detection, and NDVI imagery to monitor plant health, while AI-driven analytics expand from agriculture to turf and lawn care.

AI technologies are increasingly being integrated into agriculture and gardening, from advanced irrigation and pest detection systems to consumer-grade smart plant care devices. Researchers and ...

A review published in Agriculture outlines how integrating these tools into farming practices could play a decisive role in ...

A new satellite-based analytical framework enables accurate estimation of crop sowing and emergence dates at the field scale. By integrating daily ...

A new satellite-based analytical framework enables accurate estimation of crop sowing and emergence dates at the field scale.

Crop Disease Detection using Machine Learning is a CNN-based system that identifies crop diseases from leaf images and provides preventive measures, helping farmers detect diseases early and reduce ...

Abstract: Precisely identifying crop diseases is a key to achieving high agricultural productivity as well as reduction of agricultural yield losses. Conventional practices in detection of crop ...

Candida auris is an emerging threat, primarily to hospital patients and residents of nursing homes. The fungus easily spreads, colonizes surfaces and objects where it can survive for weeks to months, ...

DHAKA – As a cold wave continues to grip the country, agricultural experts are warning that certain crops could face serious risks from the unusual weather, while others may benefit and thrive under ...

Abstract: Crop diseases remain a major threat to global agricultural productivity, particularly in resource-constrained regions, where early intervention is critical to ensuring food security.

A new study shows that machine-learning models can accurately predict daily crop transpiration using direct plant measurements and environmental data. By training models on seven years of ...