Satellites and Crop Models Team Up to Cut Water and Fertilizer Use in Silage Maize
A new framework coupling Sentinel-1 radar remote sensing, the DSSAT-CERES-Maize model, and multi-objective optimization cuts irrigation water use by up ...
A new framework coupling Sentinel-1 radar remote sensing, the DSSAT-CERES-Maize model, and multi-objective optimization cuts irrigation water use by up ...
A new review argues that AI could transform agriculture, healthcare, education, and finance in Africa, but only if job displacement, ...
A neural network trained on unlabeled drone imagery of lupine, maize, soybean, and sunflower taught itself to distinguish crop types ...
A new review argues that systematically measuring environmental factors, a practice called enviro-typing, can complement genotyping and phenotyping to accelerate ...
An Indian research team has built an edge-cloud irrigation system that combines ultra-low-power soil sensors, Gaussian differential privacy, and ensemble ...
A four-season study on Andalusian farms found that combining no-tillage with GPS tractor guidance cut fuel consumption by roughly 50% ...
Researchers in Spain show that the standard deviation of satellite-derived NDVI, especially during crop senescence, offers a low-cost way to ...
A systematic 264-experiment study in China found that a Wasserstein GAN augmenting just 76 soil samples improved drone-based soil organic ...
A two-stage imaging and deep learning framework detects and grades infestations of four greenhouse pests, distilling 248 spectral bands into ...
An eight-year satellite study of an Azerbaijani apple orchard shows NDVI can reliably predict yields only for individual plots of ...
© 2025 Scienmag - Science Magazine
© 2025 Scienmag - Science Magazine