This project aims to support sustainability in agriculture, using AI tools to reduce required fertilizers, pesticides, and water use, while maintaining crop quality and yield. Specifically, this will be achieved by improved modeling of their effects, dispersion, etc.; combined with precision application. This will result in a practical and measurable impact on society. We will consider both crops growing in soil as well as hydroponic crops. This project is paired with Part B. In Part A (this proposal) we consider the modeling and simulation needed that incorporate data from the field, including sensors and robotics. The effort includes sub model validation and will enable optimized delivery of water, pesticides, and fertilizers to the fields. Part B considers the complementary aspect of implementing hardware capable of gathering the required data in the field.