Smarter crop monitoring: Multi-sensor models transform corn growth forecasting
Peer-Reviewed Publication
Updates every hour. Last Updated: 5-Nov-2025 07:11 ET (5-Nov-2025 12:11 GMT/UTC)
A research team has developed advanced methodologies for predicting the aboveground biomass (AGB) of corn by integrating unmanned aerial vehicles (UAVs), multi-sensor data, and machine learning models.
A research team has demonstrated that greenhouse tomato productivity can be significantly improved by targeting leaf-level efficiency and plant layout strategies.
Engineers and scientists, as well as artists, have long been inspired by the beauty and functionality of nature’s designs. Japan designed high-speed trains to cut through the air as smoothly as the kingfisher cuts through water, for example, but useful designs can also be found at a microscopic level. The study of biology in combination with materials science is called biomateriomics. An Italian research team sees great potential in the application of generative artificial intelligence to this already interdisciplinary field. They have described this potential, and the associated limitations and challenges, in an open access review article titled “Generative Artificial Intelligence for Advancing Discovery and Design in Biomateriomics,” published May 1 in Intelligent Computing, a Science Partner Journal.