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

• 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
• ISSN: 0890-037X; 1550-2740
• DOI: 10.1614/WT-03-047R1

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.