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Nonlinear Regression Analysis of Herbicide Absorption Studies

Published online by Cambridge University Press:  20 January 2017

Andrew R. Kniss ,
Joseph D. Vassios ,
Scott J. Nissen  and
Christian Ritz
Andrew R. Kniss*
Affiliation:
Department of Plant Sciences, University of Wyoming, Laramie, WY 82071
Joseph D. Vassios
Affiliation:
Department of Bioagricultural Sciences and Pest Management, Colorado State University, Ft. Collins, CO 80523
Scott J. Nissen
Affiliation:
Department of Bioagricultural Sciences and Pest Management, Colorado State University, Ft. Collins, CO 80523
Christian Ritz
Affiliation:
University of Copenhagen, Department of Basic Sciences & Environment, DK-1871 Frederiksberg C, Denmark
*
Corresponding author's E-mail: akniss@uwyo.edu
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Abstract

Although foliar herbicide absorption has been studied intensively, there is currently no standardized method for data analysis when evaluating herbicide absorption over time. Most peer-reviewed journals require the treatment structure of data be incorporated in the analysis; however, many herbicide absorption studies published in the past 5 yr do not account for the time structure of the experiment. Herbicide absorption studies have been presented in a variety of ways, making it difficult to compare results among studies. The objective of this article is to propose possible nonlinear models to analyze herbicide absorption data and to provide a stepwise framework so that researchers may standardize the analysis method in this important research area. Asymptotic regression and rectangular hyperbolic models with similar parameterizations are proposed, so that the maximum herbicide absorption and absorption rate may be adequately modeled and statistically compared among treatments. Adoption of these models for herbicide absorption analysis over time will provide a standardized method making comparison of results within and among studies more practical.

Keywords

Asymptotic regressionexponential rise to maximumrectangular hyperbolanonlinear regression
Type
Special Topics
Information
Weed Science , Volume 59 , Issue 4 , December 2011 , pp. 601 - 610
Copyright
Copyright © Weed Science Society of America 

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References

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