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

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 (US)
Article number200
JournalScientific Data
Volume11
Issue number1
DOIs
StatePublished - Dec 2024

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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