As climate change and population growth increase pressure on global food production, regional-scale crop growth and associated process (CROP-AP) models have become essential tools for understanding and predicting agricultural productivity. A new review, published in Science China Earth Sciences, categorizes these models into four types—statistical models, crop growth models, hydrology-crop coupling models, and ecosystem models. The study explores their main functions from five aspects: crop yield prediction, crop water consumption, agricultural non-point source pollution, greenhouse gas emissions, and climate change impact and responses, and identifies key future research directions, including model validation and calibration, the ability to simulate the coupling of crop physiology and human activities, enhancing model scalability, multi-model ensembles, data and code sharing, and the integration of artificial intelligence.

Researchers used in situ pH measurements and in situ UV-Vis spectroscopy to investigate the kinetically controlled growth of Co(OH)₂. They discovered that Co polyhedra with unconventional coordination play a crucial role in the formation process of Co(OH)₂, reshaping our understanding of the formation process.