Overview AI systems use sensors and computer vision to detect pests and diseases early, reducing crop damage and yield losses ...

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

Pests that spread as a result of climate change pose an increasing threat to fruit farming and viticulture in Germany. Fraunhofer researchers are working with partners to develop methods for the early ...

Overview: AI-driven precision farming enables real-time crop monitoring using data from sensors, satellites, and drones to ...

Abiotic stress physiology is a critical field within plant science, particularly as climate change and environmental ...

UIUC's platform, christened Stomata In-Sight, combines laser scanning confocal microscopy, gas exchange instruments and machine-learning image analysis, to simultaneously observe anatomical ...

A research team introduces a fully automated, non-destructive phenotyping platform that combines X-ray fluorescence microscopy with computer vision and machine learning.

Recent developments in machine learning techniques have been supported by the continuous increase in availability of high-performance computational resources and data. While large volumes of data are ...

EQT Foundation has invested in UK-based Biographica as part of its seed round, supporting the company’s machine learning platform for faster and more accurate crop gene discovery. Biographica’s ...

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

In this week’s edition of The Prototype, we look at building a virtual fusion power plant, a major quantum breakthrough, AI ...