Hostname: page-component-78c5997874-fbnjt Total loading time: 0 Render date: 2024-11-08T05:29:24.995Z Has data issue: false hasContentIssue false
  • English
  • Français

Growth curve analysis for treatments-by-environments interaction effects

Published online by Cambridge University Press:  27 March 2009

R. N. Edmondson
R. N. Edmondson
Affiliation:
Institute of Horticultural Research (Littlehampton), Worthing Road, Littlehampton, West Sussex BN17 6LP
Get access Rights & Permissions [Opens in a new window]

Summary

Growth curves fitted to factorial data can be modelled using an extrinsic time variate or using the mean responses within the levels of a subset of factors. Where factors can be partitioned into a set of ‘treatment’ factors and a set of ‘environment’ factors, fitting growth curves to the mean effects of environments allows the effects of treatments to be assessed relative to a uniform background growth rate. This leads to a test of a null hypothesis of equal treatment effects in all environments, given that the mean growth rate and stage of development in all environments is equal. The approach is exemplified using data from a glasshouse tomato crop experiment testing variety, nutrient and sowing date factors. Variety and nutrient treatment effects were of direct interest but sowing dates were intended to generalize results by providing a range of growing environments. Treatment effects are analysed by modelling running cumulative yield totals by growth curves and regressing variety and nutrient growth variates on the mean growth variate within each sowing date. In the discussion the case of more than one environmental factor is considered.

Type
Research Article
Information
The Journal of Agricultural Science , Volume 112 , Issue 1 , February 1989 , pp. 9 - 17
Copyright
Copyright © Cambridge University Press 1989

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

Draper, N. R. & Smith, H. (1966). Applied Regression Analysis. New York: Wiley.Google Scholar
Grizzle, J. E. & Allen, D. M. (1969). Analysis of growth and dose response curves. Biometrics 25, 357–381.CrossRefGoogle ScholarPubMed
Potthoff, R. F. & Roy, S. N. (1964). A generalized multivariate analysis of variance model useful especially for growth curve problems. Biometrika 51, 313–326.CrossRefGoogle Scholar
Rao, C. R. (1958). Some statistical methods for comparison of growth curves. Biometrics 14, 1–17.CrossRefGoogle Scholar
Rao, C. R. (1965). The theory of least squares when the parameters are stochastic and its applications to the analysis of growth curves. Biometrika 52, 447–458.CrossRefGoogle Scholar
Rowell, J. G. & Walters, D. E. (1976). Analysing data with repeated observations on each experimental unit. Journal of Agricultural Science, Cambridge 87, 423–432.CrossRefGoogle Scholar
Sprent, P. (1966). A generalised least-squares approach to linear functional relationships. Journal of the Royal Statistical Society 28, 278–297.Google Scholar
Wishart, J. (1938). Growth rate determinations in nutrition studies with the bacon pig, and their analysis. Biometrika 30, 16–28.CrossRefGoogle Scholar