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Statistical Modeling of Yield and Variance Instability in Conventional and Organic Cropping Systems

Permanent URL:
http://handle.nal.usda.gov/10113/49953
File:
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Abstract:
Temporal variation in crop yields has considerable impact at farm, regional, and national levels. To gain a better understanding of the factors contributing to this variation, we quantified the cumulative effects of management practices and soil covariates on total yield (TY), temporal yield variance (TYV) and coefficient of variation (CV) of 2-yr (2 Yr) {corn [Zea mays L.]–soybean [Glycine max (L.) Merr.]} and 4-yr (4 Yr) [corn–soybean–spring wheat (Triticum aestivum L.)–alfalfa (Medicago sativa L.)] crop rotations in conventional (CNV) and organic (ORG) cropping systems. Soil covariates differed individually or as a group in their impact on TY, TYV, and CV. Spatial variation, quantified by soil covariates, did not fully explain variation in TY or TYV; whereas, TYV explained up to 86% of variation in TY, both of which were less variable in ORG than in CNV. Multivariate relationships among TYV, CV, management factors, and covariates indicated that TYs of 4-Yr crop rotations were likely to be more stable than TYs of 2-Yr rotations. The largest and most stable yields obtained under both cropping systems are characterized by a combination of optimum TYV and minimum CV values. We developed a classification scheme of cropping systems, crop rotation phases, and management practices based on the three-way relationship between TY, TYV, and CV, and deviations from their respective means. In addition to its utility in selecting the largest and most stable yield, the scheme can be used to measure stability in crop production and strategically deploy appropriate management practices for a given cropping system or crop rotation.
Author(s):
Jaradat, Abdullah A. , Weyers, Sharon L.
Subject(s):
crop yield , organic production , variance , statistical models , temporal variation , crop rotation , Zea mays , Glycine max , corn , soybeans , spring wheat , Triticum aestivum , alfalfa , Medicago sativa , spatial variation , multivariate analysis , crop models , genetic soil types , field experimentation , Minnesota
Format:
p. 673-684.
Note:
Includes references
Source:
Agronomy journal 2011 May, v. 103, no. 3
Language:
English
Year:
2011
Collection:
Journal Articles, USDA Authors, Peer-Reviewed
Rights:
Works produced by employees of the U.S. Government as part of their official duties are not copyrighted within the U.S. The content of this document is not copyrighted.