Our discussion of the various ways to characterize interaction effects (pp. 672-678) failed to mention the powerful AMMI approach (Gauch 1988, 1992), which is an important major extension of the joint regression approach. An introduction can be found on pages 8-11 in the pdf file of Chapter 11 in Volume 2. AMMI analysis is very closely related to biplots, and there are a few commerical packages for such analysis.

Some references:

• Gauch, H. G. 1988. Model selection and validation for yield traits with interaction. Biometrics 44: 705--715.
• Gauch, H. G. 1992. Statistical Analysis of Regional Yield Trials: AMMI analysis of factorial designs Elsevier. This is a very nice, and quite readable, introduction. Chapter 3 is especially nice in reviewing the variety of joint-regression models to partition G x E.
• Romagosa et al. 1996. Use of additive main effects and multiplicative interaction model in QTL maaping for adaption in barely. Theor. Appl. Genet. 93: 30--37.
• Piepho, H. P. 1988. Methods for comparing the yield stability of cropping systems -- a review. Journal of Agronomy and Crop Science 180: 193--213.

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Bruce Walsh. jbwalsh@u.arizona.edu . Comments welcome.