Analysis of synergistic and antagonistic effects of herbicides using nonlinear mixed-model methodology

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, no...

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Bibliographic Details
Published in:Weed technology 2004-04, Vol.18 (2), p.464-472
Main Authors: Blouin, D.C, Webster, E.P, Zhang, W
Format: Article
Language:English
Subjects:
Analytical estimating
antagonists
Biological and medical sciences
Chemical control
Datasets
Education/Extension
Estimation methods
Fundamental and applied biological sciences. Psychology
Graph theory
Herbicides
Infestation
mathematical models
Modeling
Parasitic plants. Weeds
Phytopathology. Animal pests. Plant and forest protection
Standard error
Statistical variance
synergism
T tests
Weeds
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Summary: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.
ISSN:0890-037X
1550-2740
DOI:10.1614/WT-03-047R1