Performing Department
(N/A)
Non Technical Summary
Facilitating the transition to organic farming and its sustainability in Wisconsin requires developing tailored soil health management practices (SHMPs) guidelines that can help organic farmers to improve nutrient use efficiency, increase crop yield potential, and mitigate climate change impacts like drought. In this project, we aim to leverage a comprehensive statewide soil health dataset, enhanced by new field observations, remote sensing data, and advanced machine learning models, to create a web tool offering region- and field-specific SHMPs guidelines for direct use by organic grain farmers in managing soil health and ensuring climate-resilient farming. Our specific objectives include (i) conducting state-wide sampling campaigns to assess soil health parameters, soil nitrogen mineralization rate, nitrogen use efficiency, crop climate-stress resilience, and yield under SHMPs, (ii) developing and validating farm-scale machine learning models to estimate crop yield dynamics under SHMPs, (iii) developing and validating farm-scale machine learning models to estimate changes in soil health parameters under SHMPs, and (iv) delivering SHMPs guidelines and corresponding nutrient management recommendations to organic farmers through a web tool that visualizes model outcomes and integrates existing resources. The results of this project will be disseminated to stakeholders and scientific professionals through extension activities and publications.Our interdisciplinary team, in partnership with extension specialists, soil conservation groups, and the organic farming community, is committed to providing region- and field-specific soil management guidance. This project is directly aligned with the program priorities, aiming to improve the productivity, ecosystem services, and profitability of Wisconsin's organic farms while preparing them for a changing climate.
Animal Health Component
30%
Research Effort Categories
Basic
70%
Applied
30%
Developmental
0%
Goals / Objectives
In this project, we aim to leverage a comprehensive statewide soil health dataset, enhanced by new field observations, remote sensing data, and advanced machine learning models, to create a web tool offering region- and field-specific SHMPs guidelines for direct use by organic grain farmers in managing soil health and ensuring climate-resilient farming. Our specific objectives include (i) conducting state-wide sampling campaigns to assess soil health parameters, soil nitrogen mineralization rate, nitrogen use efficiency, crop climate-stress resilience, and yield under SHMPs, (ii) developing and validating farm-scale machine learning models to estimate crop yield dynamics under SHMPs, (iii) developing and validating farm-scale machine learning models to estimate changes in soil health parameters under SHMPs, and (iv) delivering SHMPs guidelines and corresponding nutrient management recommendations to organic farmers through a web tool that visualizes model outcomes and integrates existing resources. The results of this project will be disseminated to stakeholders and scientific professionals through extension activities and publications.
Project Methods
We will leverage an extensive statewide soil health dataset, incorporating new field observations, remote sensing data, and data-driven machine learning (ML) models to develop targeted soil health management practices and corresponding nutrient management guidelines, aiming to enhance soil health, crop nutrient use efficiency (NUE), and mitigate the impacts of climate change on organic grain crops.Our project's long-term goal is to support and enhance organic farming in Wisconsin by providing region- and field- specific soil health promoting strategies and corresponding nutrient management recommendations for organic farmers to build sustainable and climate-resilient agroecosystems. The results generated from this project will enable growers to better understand the impact of SHMPs on soil health, soil seasonal N mineralization rate,crop yield, and climate-resilience, thereby formulating optimal management strategies to enhance the productivity, ecosystem services, and profitability of Wisconsin's organic farms, as well as to prepare them for the changing climate such as drought, floods, and other extremes.