Genotype x environment interactions for cane and sugar yield, and their implications in sugarcane breeding
- SourceAvailable from: Ramon Rea
Dataset: sugar tech 2011 vol 13-2
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ABSTRACT: The performance of quantitative traits in sugarcane (Saccharum spp. complex) often varies across diverse environments because of significant genotype-by-environment interaction (GEI). Our objective was to assess performance stability of 20 advanced sugarcane genotypes across six environments, including two crop seasons in Punjab. Data were obtained on cane yield (t/ha), sucrose % juice, and commercial cane sugar % at harvest and subjected to GGE [genotype (G) plus genotype-environment (GE)] biplot analysis, which revealed high positive correlations between spring and autumn crop seasons at all locations for all measured traits. This implied that genotypes could be evaluated in either crop season, which should reduce testing cost and time. Test environment Faridkot (FDK) spring, being both discriminating and representative, was an ideal test environment for selecting generally adapted genotypes for cane yield. Similarly, Ludhiana (LDH) autumn was an ideal test environment for selecting generally adapted genotypes for quality traits. Co 0238 and CoPb 08214, having high mean performance and stability across environments for cane yield and quality traits, were identified as ideal genotypes. These genotypes can be exploited commercially for the entire state of Punjab. The GGE biplot helped identify a specifically adapted genotype, CoH 119, which was the best performer in Gurdaspur (GDSP) in both crop seasons.Journal of Crop Improvement 09/2014; 28(5). DOI:10.1080/15427528.2014.925025
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ABSTRACT: The objective of this investigation was to evaluate seed yield of twenty durum wheat (Triticum turgidum spp. durum) genotypes. Evaluation of genotype × environment interaction and stability were also carried out at five diverse locations during the 2007-2009 growing seasons. Significant differences were found among the genotypes for seed yield on individual years and combined over years, in all locations. Genotype × environment interaction showed significance (p>0.001) for seed yield. According to the coefficients of linear regression and deviations from the regression model, genotypes G2, G7 and G8 proved to be the most stable while based on α and λ parameters, genotypes G7, G12 and G13 were identified the most stable. Clustering genotypes based on all stability methods and mean yield divided them into four major classes, which Class II had relatively high stability and high mean yield performance. To compare relationships among stability statistics, hierarchical clustering procedure showed that the ten stability statistics and mean yield could be categorized into three major groups, which methods of Group C indicated dynamic concept of yield stability. The genotypic stability, stability variance, superiority index and desirability index provide information for reaching definitive conclusions. Also, the best recommended genotypes, according to the present investigation, were G2 (2697.18 kg ha -1), G7 (2644.70 kg ha -1), G8 (2580.16 kg ha -1) and G10 (2637.43 kg ha -1), which had high mean yield and were the most stable genotypes based on the above mentioned stability statistics.