Early Season Biomass and Weather Enable Robust Cereal Rye Cover Crop Biomass Predictions

Authors

• Alexandra M. Huddell, University of Maryland, University of DelawareFollow
• Brian Needleman, University of Maryland at College Park
• Eugene P. Law, University of Delaware
• Victoria J. Ackroyd, University of Maryland at College Park
• Muthukumar V. Bagavathiannan, Texas A & M University - College Station
• Kevin Bradley, University of Missouri
• Adam S. Davis, United States Department of Agriculture, Agricultural Research Service, Urbana, Illinois
• Jeffrey A. Evans, Farmscape Analytics
• Wesley Jay Everman, North Carolina State University
• Michael Flessner, Virginia Polytechnic Institute and State University
• Nicholas Jordan, University of Minnesota - Twin Cities
• Lauren M. Schwartz-Lazaro, Louisiana State University
• Ramon G. Leon, North Carolina State University
• John L. Lindquist, University of Nebraska-LincolnFollow
• Jason K. Norsworthy, University of Arkansas at Little Rock
• Lovreet S. Shergill, Montana State University
• Mark VanGessel, University of Delaware
• Steven B. Mirsky, United States Department of Agriculture, Agricultural Research Service, Sustainable Agricultural Systems Laboratory, Beltsville

ORCID IDs

Huddell https://orcid.org/0000-0002-6289-6290

Law https://orcid.org/0000-0001-9995-2316

Flessner https://orcid.org/0000-0002-2854-008X

Leon https://orcid.org/0000-0002-1924-3331

Shergill https://orcid.org/0000-0002-3061-421X

Document Type

Article

Date of this Version

2024

Citation

Agricultural and Environmental Letters (2024) 9: e20121

Editor: Peter O’Brien

doi: 10.1002/ael2.20121

Comments

United States government work

Abstract

Farmers need accurate estimates of winter cover crop biomass to make informed decisions on termination timing or to estimate potential release of nitrogen from cover crop residues to subsequent cash crops. Utilizing data from an extensive experiment across 11 states from 2016 to 2020, this study explores the most reliable predictors for determining cereal rye cover crop biomass at the time of termination. Our findings demonstrate a strong relationship between early-season and late-season cover crop biomass. Employing a random forest model, we predicted late-season cereal rye biomass with a margin of error of approximately 1,000 kg ha⁻¹ based on early-season biomass, growing degree days, cereal rye planting and termination dates, photosynthetically active radiation, precipitation, and site coordinates as predictors. Our results suggest that similar modeling approaches could be combined with remotely sensed early-season biomass estimations to improve the accuracy of predicting winter cover crop biomass at termination for decision support tools.