U.S. cereal rye winter cover crop growth database

Author:

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

Abstract

AbstractWinter 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.

Funder

United States Department of Agriculture | Natural Resources Conservation Service

United States Department of Agriculture | National Institute of Food and Agriculture

U.S. Department of Agriculture

Publisher

Springer Science and Business Media LLC

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3