Similar to humans, plants can become infected with more than one virus at a time, opening the door for more severe infections and new disease variants. But these mixed infections are often under-studied and poorly […]
New Cornell research offers alternatives to a class of insecticides that has devastating ecological impacts, especially to pollinators, beneficial insects and aquatic invertebrates. A paper published online in Crop Protection on August 5 examines a […]
Researchers at the Leibniz Institute of Vegetable and Ornamental Crops (IGZ) investigated the factors that regulate seasonal variation in the nutritional quality of red cabbage. They analyzed the influence of light and temperature on the […]
Human waste usually gets flushed away, but instead of going down the toilet, it can help the planet and solve global fertilizer shortages, according to a new study published in the journal Proceedings of the […]
Researchers at the University of Missouri have found a mix of drones and AI can help farmers measure the health of their corn more efficiently.This post was originally published on this site.
As the global population rises and environmental stressors pile up, the question of how to ensure food security for all grows increasingly pressing. A new study led by Tufts Research Technician, and incoming Ph.D. student, […]
Plants transport water and nutrients from their environment through specialized pores. Researchers at the University of Geneva (UNIGE) have shed light on a little-known but essential mechanism for proper plant function: the directionality of nutrient […]
A new method, which uses synthetic datasets and transfer learning to overcome data scarcity and variability, significantly outperforms conventional techniques in multi-year field trials.This post was originally published on this site.
By leveraging a vision foundation model called Depth Anything V2, the method can accurately segment crops across diverse environments—field, lab, and aerial—reducing both time and cost in agricultural data preparation.This post was originally published on […]
By integrating large-kernel convolutional blocks and a novel loss function, LKNet effectively addresses challenges such as overlapping targets, annotation bias, and variability in panicle structure across growth stages. Tested on UAV imagery and multiple crop […]
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