The new agricultural revolution is set to take place with the implementation of new agricultural technologies such as robotics, remote sensing, machine learning, system modeling, among others. The objective is to use agro-ecosystem models to explore how new field arrangements (patchy crops) can contribute to a more sustainable agriculture. For this project we are going to use the SIMPLACE platform to do an experiment set up for the PATCHCrop field experiment, which includes a variety of summer and winter crops arranged in patches considering soil characteristics, we are going to use the observed data, remote sensing and machine learning tools to improve, calibrate and validate our agro-ecosystem models.
We expect to develop and adapt agro-ecosystem modeling tools for diversified cropping systems (in terms of crops and field arrangements) at field and landscape scale, to gain knowledge on how these practices play a role on multifunctional agroecosystem performance, from crop growth dynamics (in terms of health, growth, and yields) to resource use efficiency of inputs and biodiversity.