Genotype x environment interaction of crossover type: detecting its presence and estimating the crossover point

Citation
M. Singh et al., Genotype x environment interaction of crossover type: detecting its presence and estimating the crossover point, THEOR A GEN, 99(6), 1999, pp. 988-995
Citations number
32
Categorie Soggetti
Plant Sciences","Animal & Plant Sciences
Journal title
THEORETICAL AND APPLIED GENETICS
ISSN journal
00405752 → ACNP
Volume
99
Issue
6
Year of publication
1999
Pages
988 - 995
Database
ISI
SICI code
0040-5752(199910)99:6<988:GXEIOC>2.0.ZU;2-1
Abstract
Genotype-environment interaction (GEI) introduces inconsistency in the rela tive rating of genotypes across environments and plays a key role in formul ating strategies for crop improvement. GEI can be either qualitative (i.e., crossover type) or only quantitative (i.e., noncrossover type). Since the presence of crossover-type interaction has a strong implication for breedin g for specific adaptation, it is important to assess the frequency of cross over interactions. This paper presents a test for detecting the presence of crossover-type interaction using the response-environment relationship and enumerates the frequency of crossovers and estimation of the crossover poi nt (CP) on the environment axis, which serves as a cut-off point for the tw o environments groups where different/specific selections can be made. Sixt y-four barley lines with various selection histories were grown in northern Syria and Lebanon giving a total of 21 environments (location-year combina tions). Linear regression of the genotypic response on the environmental in dex represented a satisfactory model? and heterogeneity among regressions w as significant. At a 5% level of significance, 38% and 19% of the pairs sho wed crossover interactions when the error variances were considered heterog eneous and homogeneous, respectively, implying that an appreciable number o f crossovers took place in the case of barley Lines responding to their env ironments. The CP of 1.64 t/ha, obtained as the CP of regression lines betw een the genotype numbers: 19 and 31, provided maximum genotype x environmen t-group interaction. Across all environments, genotype nos. 59 and 12 stood first and second for high yield, respectively. The changes in the ranks of genotypes under the groups of environments can be used for selecting speci fically adapted genotypes.