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Notes: Abstract Following the recognition of the importance of dealing with the effects of genotype-by-environment (G ×E) interaction in multi-environment testing of genotypes in plant breeding programs, there has been substantial development in the area of analytical methodology to quantify and describe these interactions. Three major areas where there have been developments are the analysis of variance, indirect selection, and pattern analysis methodologies. This has resulted in a wide range of analytical methods each with their own advocates. There is little doubt that the development of these methodologies has greatly contributed to an enhanced understanding of the magnitude and form ofG ×E interactions and our ability to quantify their presence in a multi-environment experiment. However, our understanding of the environmental and physiological bases of the nature ofG ×E interactions in plant breeding has not improved commensurably with the availability of these methodologies. This may in part be due to concentration on the statistical aspects of the analytical methodologies rather than on the complementary resolution of the biological basis of the differences in genotypic adaptation observed in plant breeding experiments. There are clear relationships between many of the analytical methodologies used for studying genotypic variation andG ×E interaction in plant breeding experiments. However, from the numerous discussions on the relative merits of alternative ways of analysingG ×E interactions which can be found in the literature, these relationships do not appear to be widely appreciated. This paper outlines the relevant theoretical relationships between the analysis of variance, indirect selection and pattern analysis methodologies, and their practical implications for the plant breeder interested in assessing the effects ofG ×E interaction on the response to selection. The variance components estimated from the combined analysis of variance can be used to judge the relative magnitude of genotypic andG ×E interaction variance. Where concern is on the effect of lack of correlation among environments, theG ×E interaction component can be partitioned into a component due to heterogeneity of genotypic variance among environments and another due to the lack of correlation among environments. In addition, the pooled genetic correlation among all environments can be estimated as the intraclass correlation from the variance components of the combined analysis of variance. WhereG ×E interaction accounts for a large proportion of the variation among genotypes, the individual genetic correlations between environments could be investigated rather than the pooled genetic correlation. Indirect selection theory can be applied to the case where the same character is measured on the same genotypes in different environments. Where there are no correlations of error effects among environments, the phenotypic correlation between environments may be used to investigate indirect response to selection. Pattern analysis (classification and ordination) methods based on standardised data can be used to summarise the relationships among environments in terms of the scope to exploit indirect selection. With the availability of this range of analytical methodology, it is now possible to investigate the results of more comprehensive experiments which attempt to understand the nature of differences in genotypic adaptation. Hence a greater focus of interest on understanding the causes of the interaction can be achieved.

Notes: Abstract An objective of the CSR sugarcane breeding programme in Australia was to assess the scope for broadening the genetic base of the commercial sugarcane germ plasm through interspecific hybridization with Saccharum spontaneum clones. The contribution of both selection history and S. spontaneum to sugar yield and its components was investigated in the germ plasm pool assembled. The analysis was conducted on a data-set of 256 clones, consisting of parents and full-sib families generated from 32 biparental crosses, tested in six environments. The minimum number of generations back to S. spontaneum ancestor in the clone's pedigree was used as a germ plasm score. The geographical origin and selection history of each parent and their use in the biparental crosses were used to develop a selection history score for parents and offspring. The variation for seven attributes, cane yield, commercial cane sugar %, sugar yield, stalk number per stool, stalk weight, fibre % and ash % juice was partitioned according to the germ plasm and selection history scores. Significant (P〈0.05) clone variation and clone x environment interaction for all attributes was present. The germ plasm scores accounted for a significant (P〈0.05) component of the clone variation for all of the attributes except cane yield. There was an increase in sugar yield with an increase in the minimum number of generations back to a S. spontaneum clone. The selection history groups accounted for a high proportion of the variation among parental clones for all of the attributes except cane yield. This suggested that parents were the outcome of strong selection pressure for the commercial cane attributes. However, the selection history groups for the offspring produced by random mating of parents did not account for a high proportion of the variation for the attributes. Using the mixture method of classification we partitioned the 256 clones into five groups for patterns of performance for the seven attributes across the six environments. The five groups emphasized major differences in the patterns of performance for the seven attributes across environments. The distribution of germ plasm and selection history scores in each of the five groups indicated that their patterns of performance were associated with selection history and minimum generations to S. spontaneum. Therefore, both the analysis on selection history and germ plasm scores (extrinsic classification) and the analysis on the mixture method of classification (intrinsic classification) emphasized the influence of selection history on the sugar yield of sugarcane.