Rugged hardware and no-code AI empower industrial teams to deploy intelligence where operations run. JACKSONVILE, FL, UNITED STATES, January 2, 2026 /EINPresswire.com/ — Velasea ( a leading OEM system ...

Overview AI enhances farm productivity by detecting crop diseases early and optimizing resource usage efficiently.Livestock ...

By combining a custom-built optical instrument with physics-based modeling and machine learning, the study shows that leaf-level optical properties ...

By contrasting nematode infection with drought stress, the study highlights both the potential and limitations of remote sensing for separating ...

A research team has developed a new way to measure and predict how plant leaves scatter and reflect light, revealing that ...

A research team has developed a new model, PlantIF, that addresses one of the most pressing challenges in agriculture: the ...

Digital condition monitoring is transforming hydropower O&M with AI-driven diagnostics, hybrid architectures, and predictive ...

The most-visited transportation post of the year focused on the United States’s efforts to rebuild a domestic supply of neodymium-iron-boron (NdFeB) magnets—critical components for EVs, wind turbines, ...

This study shows that a blood-based metabolomic signature linked to maternal BMI predicts gestational diabetes and ...

A Hebrew University study suggests AI tools could help growers better manage water use by predicting healthy plant behavior and flagging early signs of stress.

A new Israeli study suggests that machine-learning models may soon give growers a far more precise way to predict how much water their crops use each day, while also laying the groundwork for earlier ...

Abstract: Plant diseases seriously affect worldwide crop output, threatening food security and agricultural sustainability. This study solves these issues by introducing a hybrid machine learning ...