Yield and adaptation of hexaploid spring triticale

Abstract

Gains in yield and stability were analysed using grain yield data from the 8th to the 14th International Triticale Yield Nursery (ITYN) and differences in adaptation between complete and substituted triticales (X Triticosecale Wittmack) were examined. A trend of improving yield and adaptation was observed. As highly significant genotype x site interaction each year was not adequately described using regression analysis, yield stability was examined by ranking genotypes within sites and summarizing scores for individual genotypes across sites. Cluster analysis was used to study the relationships among sites and among genotypes. There was little evidence of sites grouping on a geographical basis. Grouping of genotypes showed a tendency for complete and substituted triticales to perform differently, suggesting that diversity for adaptation is maximized by utilizing both types in breeding.Progress for grain yield is compared with more spectacular gains in test weight and reasons for the different rates of improvement are postulated.

Nonparametric stability methods for interpreting genotype by environment interaction of bread wheat genotypes (Triticum aestivum L.)

“…We also used the methodology described by Fox et al (1990), who proposed a nonparametric superiority measure for general adaptability using stratified ranking of cultivars. Ranking was done at each location separately and the number of sites at which the cultivar occurred in the TOP, MID, and LOW third of the ranks was computed.…”

“…According to Fox et al (1990) a genotype usually found in the top third of entries across environments can be considered relatively well adapted and stable. Thus, in our study, the most stable genotype was Karahan-99 because it ranked in the top third of genotypes in a high percentage of environments (i.e., had a high TOP value), followed by the AL-2 and AL-3 genotypes, with the least-desirable genotypes being AL-4, Yakar-99, AL-5 and AL-1 (Table 3).…”

“…The other approach is to use nonparametric techniques, and several procedures have been proposed based on comparing ranks of genotypes in each environment, with genotypes with similar ranking across environments being considered stable (Huehn, 1979;Nassar and Huehn, 1987;Kang, 1988;Ketata et al, 1989;Fox et al, 1990). The following four nonparametric measures of phenotypic stability have been proposed by Huehn (1979) and Nassar and Huehn (1987): S i (1) , the genotype absolute rank difference mean as tested over n environments; S i (2) , the between-ranks variance over the n environments; S i (3) , the sum of the absolute deviations of the squares of ranks for each genotype; and S i (6) , the sum of the squares of ranks for each genotype relative to the mean of ranks.…”

“…It is possible to not only assign mean yield ranks, with the genotype with the highest yield being ranked 1, but also ranks for the Shukla stability variance (Shukla, 1972) in which the lowest estimated yield value is ranked 1 (Kang 1988), with the sum of these two sets of ranks resulting in an index in which the genotype with lowest rank-sum is considered to be the most desirable. In addition, a nonparametric superiority measure for general adaptability has been suggested based on stratified ranking of the cultivars in each separate environment, with the proportion of sites at which a specific cultivar occurred in the top third of the ranks (the TOP value), the middle third of the ranks (the MID value) and the lower third of the ranks (the LOW value) being calculated, a genotype with a high TOP value (i.e., occurring principally in the top third of the ranks) being considered as a widely adapted genotype (Fox et al, 1990). Nonparametric statistical procedures have several advantages over parametric stability statistics in that they are easy to use and interpret, no assumptions are needed regarding the distribution of the observed values, removal or addition of one or several genotypes cause little variation in the results and outlier bias is reduced (Huehn, 1990a).…”

Combinação de métodos paramétricos e não-paramétricos na análise de estabilidade de cultivares de cana-de-açúcar

“…Ele obteve essa estimativa pela seguinte equação: Portanto, as cultivares que apresentassem as menores variâncias nos postos foram consideradas as mais está-veis. Fox et al (1990) propuseram uma estratificação destes postos para a definição de estabilidade de determinada cultivar. Eles sugeriram, de maneira mais intuitiva, que as cultivares cujas produções ocupassem consistentemente o terço superior dos postos (menores valores = maiores produções) seriam estáveis e teriam características favoráveis à seleção, ao passo que aquelas que ocupassem o terço inferior dos postos (maiores valores = menores produções) seriam igualmente estáveis, mas não seriam selecionáveis, devido à baixa produção.…”