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Analysis of Genotype by Environment Interaction in Louisiana Sugarcane Research Plots by GGE Biplots
- Todd, James, Pan, Yong-Bao, Kimbeng, Collins, Dufrene, Edwis, Jr., Waguespack, Herman, Jr., Pontif, Michael
- Sugar tech 2018 v.20 no.4 pp. 407-419
- breeding programs, computer software, crop year, crops, cultivars, genotype, genotype-environment interaction, soil types, statistical analysis, sugarcane, sugars, Louisiana
- Genotype by environment (G × E) interactions complicate genotype selection in breeding programs. In south Louisiana, sugarcane is cultivated under a wide range of environments including soil types and cultural management practices. To evaluate experimental genotypes in different environments, the variety development program places experimental varieties in cooperator’s fields across the sugarcane growing region as part of the selection process. The yield data of these varieties are affected by genotypic and genotype by environmental (GGE) interactions. In this study, the sugar yield data of eleven check varieties sampled over 4 years, including 2–4 crops across 21 locations, were analyzed by GGE biplot software in order to visualize GGE effects. GGE biplots enable the identification of ideal environments for evaluation of different genotypes and genotype performance and stability. Our goal was to assess the stability and representativeness of each check variety and find the best descriptive and representative test evaluation sites within the region using the GGE biplot method. The resulting graphical patterns and statistical analysis suggest yield variability is strongly dependent on crop, year, and variety. No consistent regional or soil patterns were observed. However, there were significant differences among locations for yield discrimination. Yield stability significantly varied by genotype in large plot trials “outfield” and in the small plot trials “nurseries” with some crop years were more representative than others. The results indicate that each crop year has unique growth conditions that affect yield and selection, and highly discriminating locations and stable cultivars were identified to improve selection.