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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Sustainable Agricultural Systems Laboratory » Research » Publications at this Location » Publication #420966
Research Project: Precision Integrated Weed Management in Conventional and Organic Crop Production Systems

Location: Sustainable Agricultural Systems Laboratory

Title: Chapter 11: Cover crop decision support tools

Author
item ACKROYD, VICTORIA - University Of Maryland
item DARBY, HEATHER - University Of Vermont
item REBERG-HORTON, S. CHRIS - North Carolina State University
item PINEGAR, MIKAH - North Carolina State University
item Mirsky, Steven

Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: 6/2/2026
Publication Date: 6/17/2026
Citation: Ackroyd, V., Darby, H., Pinegar, M., Reberg-Horton, C., Mirsky, S. 2026. Cover crop decision support tools. In: Duiker, S., Clark, A. editors. Cover crops for sustainable soil management. Cambridge, UK: Burleigh Dodds Science Publishing Limited. p. 285-302.
DOI: https://doi.org/10.19103/AS.2025.0162.11

Interpretive Summary:

Technical Abstract: Cover crops can provide multiple agroecosystem services, but require management that increases cropping system complexity. An overwhelming amount of information exists pertaining to cover crop management. Assorted groups have sought to distill this knowledge base into decision support tools that provide cover crop recommendations. However, such tools have suffered from a lack of site-specificity, failure to integrate existing data across agricultural systems and scales, a lack of adaptivity and interoperability, and suboptimal user interface design. This chapter reports on Precision Sustainable Agriculture (PSA) network efforts to develop tools that are site-specific, relevant across the US, and user-friendly. Example use cases feature a species selector and a cover crop nitrogen calculator. Future challenges relate to the amount of data held within tools, the need to keep it updated, and the difficulty in elucidating interactions among cash and cover crop genetics, the environment, and management to provide the best possible recommendations.