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1 April 2004 Analysis of Synergistic and Antagonistic Effects of Herbicides Using Nonlinear Mixed-Model Methodology
DAVID C. BLOUIN, ERIC P. WEBSTER, WEI ZHANG
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Abstract

When herbicides are applied in mixture, and infestation by weeds is less than expected compared with when herbicides are applied alone, a synergistic effect is said to exist. The inverse response is described as being antagonistic. However, if the expected response is defined as a multiplicative, nonlinear function of the means for the herbicides when applied alone, then standard linear model methodology for tests of hypotheses does not apply directly. Consequently, nonlinear mixed-model methodology was explored using the nonlinear mixed-model procedure (PROC NLMIXED) of SAS System®. Generality of the methodology is illustrated using data from a randomized block design with repeated measures in time. Nonlinear mixed-model estimates and tests of synergistic and antagonistic effects were more sensitive in detecting significance, and PROC NLMIXED was a versatile tool for implementation.

Additional index words: Least significant difference, linear mixed models, repeated measures, tank mixture.

Abbreviations: DAT, days after treatment; GH, glufosinate plus mixture herbicide; GHD, glufosinate plus mixture herbicide by DAT; ML, maximum likelihood; MSE, mean square error; Rep, replication.

DAVID C. BLOUIN, ERIC P. WEBSTER, and WEI ZHANG "Analysis of Synergistic and Antagonistic Effects of Herbicides Using Nonlinear Mixed-Model Methodology," Weed Technology 18(2), 464-472, (1 April 2004). https://doi.org/10.1614/WT-03-047R1
Published: 1 April 2004
JOURNAL ARTICLE
9 PAGES


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