Trends and Implications of Genotype by Environment Interaction in South African Sugarcane Breeding
ABSTRACT Genotype by environment interaction (GxE) influences and complicates the selection of superior genotypes in trials by confounding the determination of true genetic values. In South Africa, variety trials are planted at several locations and harvested in the plant to third ratoon crops. The objective of this study was to determine the trends in components of GxE and their implications. The MIXED procedure of Statistical Analysis System (SAS) was used to estimate variance components. Genotype by location interaction was significant for the irrigated and coastal long-cycle programs, indicating the importance of identifying and characterizing sites. Genotype by crop-year interaction was larger and more significant for rain-fed than for irrigated cropping system, indicating the importance of ratooning ability in rain-fed regions. Genotype by location by crop-year interaction was significant (P < 0.01) for yield and sucrose content, highlighting the complexity associated with breeding sugarcane. The coastal long-cycle program was the most complex and generally characterized by large GxE. Separating the coastal hinterland and coastal average potential would be recommended to reduce GxE.
- Crop Science 01/1984; 24:435-440. · 1.48 Impact Factor
- Crop Science 01/1990; 30(2). · 1.48 Impact Factor
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ABSTRACT: Data from 6 series of routine advanced stage selection trials were used to study genotype response across 'test' environments (locations and crop-years) for sugar yield in central Queensland. The objective was to determine whether genotype × environment (G × E) interactions are present for sugar yield in central Queensland and, if so, to interpret the nature of the interactions as well as determine their implications for the selection program. The relative magnitude of the G × E interaction components, namely genotype × location (G × L), genotype × crop-years (G × C), and genotype × location × crop-years (G × L × C), was studied using variance component analysis. In addition, environments were classified based on similarity with which they discriminate amongst genotypes (pattern analyses). The study revealed substantial G × E interactions for sugar yield. The magnitude of variance attributable to the second-order interaction effect, G × L × C, was higher than that of the first-order interaction effects, G × L and G × C, in a considerable number of cases. The pattern of genotypic response across environments was not consistent among the different series of trials. These results indicate that the major contributing factor or pattern underlying G × E interactions for sugar yield in central Queensland may be complex and unpredictable, making it difficult to effectively exploit G × E interactions in the breeding program. Based on logistics and resources, the current practice whereby a manageable number of genotypes (40–50) is evaluated in a subset of locations (3–4 out of 6 possible) for 2 crop-years, and only the elite ones are re-evaluated in further locations and crop-years, appears appropriate.Australian Journal of Agricultural Research 01/2002; 53(9). · 1.30 Impact Factor