A calculator to quantify cover crop effects on soil health and productivity

被引:48
|
作者
Jian, Jinshi [1 ,2 ]
Lester, Brandon J. [1 ]
Du, Xuan [1 ,3 ]
Reiter, Mark S. [1 ,4 ]
Stewart, Ryan D. [1 ]
机构
[1] Virginia Tech, Sch Plant & Environm Sci, Blacksburg, VA USA
[2] Pacific Northwest Natl Lab, Joint Global Change Res Inst, 5825 Univ Res Ct 3500, College Pk, MD USA
[3] Yangling Vocat & Tech Coll, Dept Hydraul Engn, Yangling, Shaanxi, Peoples R China
[4] Virginia Tech, Eastern Shore Agr Res & Extens Ctr, Painter, VA USA
来源
SOIL & TILLAGE RESEARCH | 2020年 / 199卷
基金
美国食品与农业研究所;
关键词
Conservation agriculture; Soil quality; Meta-Analysis; CONSERVATION TILLAGE; CARBON; AGGREGATION; NITROGEN; SYSTEMS; YIELD;
D O I
10.1016/j.still.2020.104575
中图分类号
S15 [土壤学];
学科分类号
0903 ; 090301 ;
摘要
Many producers use cover crops as a means to increase soil health and agricultural productivity, yet benefits of this practice vary depending on environmental and management conditions. In an effort to objectively evaluate how cover crops affect soil properties and crop production across climates and systems, we compiled data from 269 studies that compared cover crop treatments versus no cover crop controls. We then used t-tests and unbalanced analysis of variation tests to evaluate cover crop-related effects on 38 indicators of soil health and productivity. The t-test analysis indicated that cover cropping caused significant changes in 28 of 38 indicators, with differences seen for all physical parameters and most indicators associated with biological and environmental measurements. The unbalanced analysis of variation test allowed us to identify a hierarchy of most to least important environment and management factors for each indicator. Using this hierarchy, we developed a calculator that allows users to evaluate how cover crop usage affects 13 key indicators, including cash crop yield, weed pressure, soil aggregate stability, soil organic carbon, soil nitrogen, and infiltration rates. The calculator requires only four inputs - climatic region, soil texture group, cash crop rotation, and cover crop type - and as output provides mean percent change for each indicator based on the selected factors. The analyses produced in this study provide new insight into specific soil health and productivity responses to cover cropping, and the corresponding web-based calculator will help to ensure that soil health measurements from the field and laboratory are useful to farmers, planners, and regulators. Further, as more data becomes integrated into the calculator, results will continue to improve in accuracy and realism, ultimately helping to make soil health evaluation a practical outcome for more producers.
引用
收藏
页数:8
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