A study initiated in 2018, funded by the Fundação de Amparo à Pesquisa do Estado de Minas Gerais (Fapemig), with contributions from various academic and agricultural institutions, including The University of Georgia and UFLA, aims to revolutionize peanut harvesting by developing a precision agriculture method to predict peanut maturation using artificial intelligence, remote sensing, and neural networks. This innovation seeks to improve harvest efficiency and quality by providing a more objective and less variable method for determining peanut maturity than the traditional Hull Scrape method. By integrating climatic variables and satellite imagery, the approach promises to enhance accuracy and reduce harvest losses, marking a significant advancement in Brazilian peanut farming. The research is led by Adão, a UFLA Precision Agriculture professor, and involves international collaborations, showcasing the commitment to scientific innovation in agricultural practices.