U.S. cereal rye winter cover crop growth database

Alexandra M. Huddell, Resham Thapa, Guillermo S. Marcillo, Lori J. Abendroth, Victoria J. Ackroyd, Shalamar D. Armstrong, Gautam Asmita, Muthukumar V. Bagavathiannan, Kipling S. Balkcom, Andrea Basche, Shawn Beam, Kevin Bradley, Lucas Pecci Canisares, Heather Darby, Adam S. Davis, Pratap Devkota, Warren A. Dick, Jeffery A. Evans, Wesley J. Everman, Tauana Ferreira de AlmeidaMichael L. Flessner, Lisa M. Fultz, Stefan Gailans, Masoud Hashemi, Joseph Haymaker, Matthew J. Helmers, Nicholas Jordan, Thomas C. Kaspar, Quirine M. Ketterings, Eileen Kladivko, Alexandra Kravchenko, Eugene P. Law, Lauren Lazaro, Ramon G. Leon, Jeffrey Liebert, John Lindquist, Kristen Loria, Jodie M. McVane, Jarrod O. Miller, Michael J. Mulvaney, Nsalambi V. Nkongolo, Jason K. Norsworthy, Binaya Parajuli, Christopher Pelzer, Cara Peterson, Hanna Poffenbarger, Pratima Poudel, Mark S. Reiter, Matt Ruark, Matthew R. Ryan, Spencer Samuelson, John E. Sawyer, Sarah Seehaver, Lovreet S. Shergill, Yogendra Raj Upadhyaya, Mark VanGessel, Ashley L. Waggoner, John M. Wallace, Samantha Wells, Charles White, Bethany Wolters, Alex Woodley, Rongzhong Ye, Eric Youngerman, Brian A. Needelman, Steven B. Mirsky

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Winter cover crop performance metrics (i.e., vegetative biomass quantity and quality) affect ecosystem services provisions, but they vary widely due to differences in agronomic practices, soil properties, and climate. Cereal rye (Secale cereale) is the most common winter cover crop in the United States due to its winter hardiness, low seed cost, and high biomass production. We compiled data on cereal rye winter cover crop performance metrics, agronomic practices, and soil properties across the eastern half of the United States. The dataset includes a total of 5,695 cereal rye biomass observations across 208 site-years between 2001–2022 and encompasses a wide range of agronomic, soils, and climate conditions. Cereal rye biomass values had a mean of 3,428 kg ha−1, a median of 2,458 kg ha−1, and a standard deviation of 3,163 kg ha−1. The data can be used for empirical analyses, to calibrate, validate, and evaluate process-based models, and to develop decision support tools for management and policy decisions.

Original languageEnglish
Article number200
JournalScientific data
Volume11
Issue number1
DOIs
StatePublished - Dec 2024

Bibliographical note

Publisher Copyright:
© The Author(s) 2024.

Funding

This study was made possible by funding from USDA Natural Resources Conservation Service Conservation Innovation Grants [award no. # NR21-13G022], USDA National Institute of Food and Agriculture, Agriculture and Food Research Initiative’s Sustainable Agricultural Systems Coordinated Agricultural Project [award no. 2019-68012-29818], USDA National Institute of Food and Agriculture, Hatch Project [award no. MD-ENST-22008], USDA National Institute of Food and Agriculture, Agriculture and Food Research Initiative’s Water Coordinated Agricultural Project [award no. 2018-68011-28372], USDA Area-Wide Pest Management [Project Number 8042-22000-16600D], Wisconsin Fertilizer Research Council project: 276-14, multiple state agricultural experiment stations, and the Hatch program of the National Institute of Food and Agriculture, US Department of Agriculture.

FundersFunder number
USDA Area-Wide Pest Management8042-22000-16600D
USDA National Institute of Food and Agriculture, Agriculture and Food Research Initiative’s Sustainable Agricultural Systems Coordinated Agricultural Project2019-68012-29818
USDA Natural Resources Conservation Service Conservation InnovationNR21-13G022
Wisconsin Fertilizer Research Council276-14
U.S. Department of Agriculture
US Department of Agriculture National Institute of Food and Agriculture, Agriculture and Food Research Initiative2018-68011-28372, MD-ENST-22008
US Department of Agriculture National Institute of Food and Agriculture, Agriculture and Food Research Initiative

    ASJC Scopus subject areas

    • Statistics and Probability
    • Information Systems
    • Education
    • Computer Science Applications
    • Statistics, Probability and Uncertainty
    • Library and Information Sciences

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