Hostname: page-component-848d4c4894-v5vhk Total loading time: 0 Render date: 2024-06-19T07:16:47.114Z Has data issue: false hasContentIssue false
  • English
  • Français

Some Comments on the Assessment of Joint Action in Herbicide Mixtures

Published online by Cambridge University Press:  12 June 2017

Pamela M. Morse
Pamela M. Morse*
Affiliation:
Stat. Res. Serv., Res. Branch, Agriculture Canada, Ottawa, Ont. K1A OC5
Get access Rights & Permissions [Opens in a new window]

Abstract

Methods of assessing and describing the joint action of materials as herbicides are reviewed, and the shortcomings of the terms synergism and antagonism are discussed. Some of the lack of agreement on their meaning and evaluation is attributed to failure to define or recognize appropriate models to represent absence of synergism (and antagonism). General analytical and graphical procedures are presented, and for two simple models, the additive-dose model (ADM) and the multiplicative-survival model (MSM), the dose-response curves and isobols are compared. Three examples from recent literature are reworked.

Type
Research Article
Information
Weed Science , Volume 26 , Issue 1 , January 1978 , pp. 58 - 71
Copyright
Copyright © 1978 by the Weed Science Society of America 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Literature Cited

1. Akobundu, I. O., Sweet, R. D., and Duke, W. B. 1975. A method of evaluating herbicide combinations and determining herbicide synergism. Weed Sci. 23:20–25.Google Scholar
2. Ashford, J. R. 1959. An approach to the analysis of data for semi-quantal responses in biological assay. Biometrics 15:573–581.Google Scholar
3. Ashford, J. R. and Cobby, J. M. 1974. A system of models for the action of drugs applied singly or jointly to biological organisms. Biometrics 30:11–31.CrossRefGoogle ScholarPubMed
4. Ashford, J. R. and Smith, C. S. 1964. General model for quantal response to the joint action of a mixture of drugs. Biometrika 51:413–428.CrossRefGoogle Scholar
5. Ashford, J. R. and Smith, C. S. 1965. An alternative system for the classification of mathematical models for quantal responses to mixtures of drugs in biological assay. Biometrics 21:181–188.Google Scholar
6. Bliss, C. I. 1939. The toxicity of poisons applied jointly. Ann. Appl. Biol. 26:585–615.Google Scholar
7. Carpenter, J. A., Marshman, J. A., and Gibbins, R. J. 1975. The effects of alcohol and meprobramate applied singly and jointly in human subjects. I. Theoretical considerations and literature review. J. Studies on Alcohol, Suppl. 7:1–53.Google Scholar
8. Colby, S. R. 1967. Calculating synergistic and antagonistic responses of herbicide concentrations. Weeds 15:20–22.Google Scholar
9. Darby, S. C. and Ellis, M. J. 1976. A test for synergism between two drugs. Appl. Statist. 25:296–299.Google Scholar
10. Draper, N. R. and Smith, H. 1966. Applied Regression Analysis. John Wiley and Sons, Inc., New York. 407 pp.Google Scholar
11. Finney, D. J. 1952. Probit Analysis. 2nd Ed. University Press, Cambridge, 318 pp.Google Scholar
12. Finney, D. J. 1971. Probit Analysis. 3rd Ed. University Press, Cambridge. 333 pp.Google Scholar
13. Finney, D. J. 1976. Radioligand assay. Biometrics 32:721–740.Google Scholar
14. Gaddum, J. H. 1937. The quantitative effects of antagonistic drugs. J. Physiol. 89:7P–9P.Google Scholar
15. Gowing, D. P. 1960. Comments on tests of herbicide mixtures. Weeds 8:379–391.Google Scholar
16. Hewlett, P. S. 1960. Joint action in pesticides. Pages 27–74 in Metcalf, R. L., ed. Advances in Pest Control Research. John Wiley and Sons, Inc., New York.Google Scholar
17. Hewlett, P. S. 1969. Measurement of the potencies of drug mixtures. Biometrics 25:477–487.Google Scholar
18. Hewlett, P. S. and Plackett, R. L. 1956. The relation between quantal and graded responses to drugs. Biometrics 12:72–78.Google Scholar
19. Hewlett, P. S. and Plackett, R. L. 1959. A unified theory for quantal responses to mixtures of drugs: non-interactive action. Biometrics 15:591–610.Google Scholar
20. Hewlett, P. S. and Plackett, R. L. 1964. A unified theory for quantal responses to mixtures of drugs: competitive action. Biometrics 20:556–575.Google Scholar
21. Loewe, S. 1953. The problem of synergism and antagonism of combined drugs. ArzneimittForsch. 3:285–290.Google Scholar
22. Plackett, R. L. and Hewlett, P. S. 1952. Quantal responses to mixtures of poisons. J.R. Statist. Soc. B 14:141–163.Google Scholar
23. Plackett, R. L. and Hewlett, P. S. 1967. A comparison of two approaches to the construction of models for quantal responses to mixtures of drugs. Biometrics 23:27–44.Google Scholar
24. Puri, P. S. and Senturia, J. 1972. On a mathematical theory of quantal responses to mixtures of drugs: competitive action. Biometrics 20:566–575.Google Scholar
25. Random House Dictionary of the English Language. 1967. Random House, Inc., New York.Google Scholar
26. Rummens, F. H. A. 1975. An improved definition of synergistic and antagonistic effects. Weed Sci. 23:4–6.Google Scholar
27. Rummens, F. H. A., Rummens-Ditters, D. C. M., and Smith, A. E. 1975. The effects of diallate and its isomers on the growth of wild oats. Weed Sci. 23:11–14.CrossRefGoogle Scholar
28. Sprague, J. B. 1969. Measurement of pollutant toxicity to fish. I. Water Res. 3:793–821.Google Scholar
29. Tammes, P. M. L. 1964. Isoboles, a graphic representation of synergism in pesticides. Neth. J. Plant Path. 70:73–80.Google Scholar
30. Veldstra, H. 1956. Synergism and potentiation; with special reference to the combination of structural analogues. Pharmacol. Rev. 8:339–387.Google Scholar
31. Webster's New International Dictionary of the English Language. 1961. 14th Ed. G. C. Merriam Co., Springfield, Mass. Google Scholar