AI

In the heart of arid and remote regions, where water is a precious commodity, a groundbreaking solution is emerging to revolutionize agricultural water management. Researchers have developed an AI-driven digital twin framework that optimizes the perf

In the shadowy realm of food safety, a silent threat lurks—mycotoxins, toxic compounds produced by fungi, are a global menace to agriculture and public health. A comprehensive review published in the *Journal of Fungi* sheds light on these stealthy s

In the rapidly evolving landscape of biomedical technology, a promising intersection of artificial intelligence (AI), machine learning (ML), and hydrogel microneedles (HMNs) is emerging, offering a glimpse into the future of drug delivery, diagnostic

In a groundbreaking study published in *Applied System Innovation*, researchers have demonstrated how explainable artificial intelligence (XAI) can revolutionize genotype-to-phenotype prediction in plants, offering significant advancements for the ag

In the heart of Rostov-on-Don, Russia, a team of researchers led by Danila Donskoy from the Laboratory “Modeling and Development of Intelligent Agricultural Engineering Systems” at Don State Technical University is making waves in the agritech world.

In the face of erratic weather patterns and dwindling groundwater reserves, farmers are increasingly turning to technology to optimize water usage and boost crop yields. A recent study published in *Engineering Proceedings* offers a promising solutio

In the ever-evolving world of agriculture, technology is playing an increasingly pivotal role in enhancing production efficiency and sustainability. A recent study published in *Horticulturae* has introduced a groundbreaking photosynthetic rate predi

In the face of a burgeoning global population, the agricultural sector is under increasing pressure to enhance crop yields and ensure food security. Among the oil crops, sunflowers hold significant promise, yet their potential is often thwarted by di

In a groundbreaking study published in the journal ‘Modelling’, researchers have developed a machine learning framework that could revolutionize how we understand and predict the impact of agricultural CO2 emissions on global warming. Led by Raziyeh

In the heart of South Dakota, a team of researchers led by Swati Srivastava at South Dakota Mines is tackling a pressing global issue: the environmental and health impacts of agricultural pesticides. Their work, published in the journal ‘Pollutants’,