It is widely believed that hexaploid wheat originated via hybridization of hulled tetraploid emmer with Aegilops tauschii (genomes DD) and that the nascent hexaploid was spelt, from which free-threshing wheat evolved by mutations. To reassess the role of spelt in the evolution of Triticum aestivum, 4 disomic substitution lines of Ae. tauschii chromosome 2D in Chinese Spring wheat were developed and one of them was used to map the Tg locus, which controls glume tenacity in Ae. tauschii, relative to simple sequence repeat (SSR) and expressed sequence tag loci on wheat chromosome 2D. The segregation of SSR markers was used to assess the presence of Tg alleles in 11 accessions of spelt, both from Europe and from Asia. Ten of them had an inactive tg allele in the D genome and most had an active Tg allele in the B genome. This is consistent with spelt being derived from free-threshing hexaploid wheat by hybridization of free-threshing wheat with hulled emmer. It is proposed that the tetraploid parent of hexaploid wheat was not hulled emmer but a free-threshing form of tetraploid wheat.
Cultivar evaluation and mega-environment identification are the most important objectives of multienvironment trials (MET). The objective of this study was to explore the effect of genotype and genotype 3 environment interaction on the grain yield of 19 barley (Hordeum vulgare L.) genotypes via GGE (genotype plus genotype 3 environment) biplot methodology. Experiments were conducted using a randomized complete block design with four replications for 3 yr at 10 locations. The biplot analysis identified three barley mega-environments in Iran. The first mega-environment contained locations Khoy, Mashhad, Miandoab, Karaj, and Nyshabour, where genotype Bahtim7-D1/79-w40762 was the winner; the second mega-environment contained locations Tabriz, Hamedan, Ardabil, and Arak, where genotype Walfajre/W1-2291 was the winner. The location of Zanjan made up the other mega-environment, with 73-M4-30 as the winner. Genotypes Bahtim7-D1/79-w40762 and Walfajre/W1-2291 had the highest mean yield and genotype K-201/3-2 had the poorest mean yield. The estimated relative yield of genotypes at Karaj station shows that genotype Bahtim7-D1/79-w40762 had the highest yield and genotype Owb70173-2H-OH had the poorest. The performances of genotypes Star/Alger and K-201/3-2 were highly variable, whereas genotypes Cossak/Gerbel/Harmal and Toji"S"/Robur were highly stable. The results of this study indicate the possibility of improving progress from selections under diverse location conditions by applying the GGL (genotype plus genotype 3 location) biplot methodology.
Analysis of multienvironment trials (METs) of crops for cultivar evaluation and recommendation is an important issue in plant breeding research. Evaluating both stability of performance and high yield is essential in MET analyses. The objective of this investigation was to compare 10 nonparametric stability methods and apply nonparametric tests (which do not require distributional assumptions) for genotypeby-environment (G 3 E) interaction to 11 lentil (Lens culinaris Medik) genotypes. Nine improved lentil genotypes and two local cultivars were grown in 20 semiarid environments in Iran from 2002 to 2004. Results of nonparametric tests of G 3 E interaction and a combined ANOVA across environments showed there were both crossover and noncrossover G 3 E interactions and genotypes varied significantly for yield. In this study, high values of TOP (proportion of environments in which a genotype ranked in the top third) and low values of rank-sum (sum of ranks of mean yield and Shukla's stability variance) were associated with high mean yield, but the other nonparametric methods were not positively correlated with mean yield and instead characterized a static concept of stability. The results of principal component (PC) analysis and correlation analysis of nonparametric stability statistics and yield indicated that only ranksum and TOP methods would be useful for simultaneously selecting for high yield and stability. These methods recommended FLIP 92-12L as stable and FLIP96-6L as unstable genotypes. A biplot of the first two PCs also revealed that the nonparametric methods grouped as three distinct classes that corresponded to different agronomic and biological concepts of stability.
SU MMARYGenotype by environment (GrE) interaction effects are of special interest for breeding programmes to identify adaptation targets and test locations. Their assessment by additive main effect and multiplicative interaction (AMMI) model analysis is currently defined for this situation. A combined analysis of two former parametric measures and seven AMMI stability statistics was undertaken to assess GrE interactions and stability analysis to identify stable genotypes of 11 lentil genotypes across 20 environments. GrE interaction introduces inconsistency in the relative rating of genotypes across environments and plays a key role in formulating strategies for crop improvement. The combined analysis of variance for environments (E), genotypes (G) and GrE interaction was highly significant (P<0 . 01), suggesting differential responses of the genotypes and the need for stability analysis. The parametric stability measures of environmental variance showed that genotype ILL 6037 was the most stable genotype, whereas the priority index measure indicated genotype FLIP 82-1L to be the most stable genotype. The first seven principal component (PC) axes (PC1-PC7) were significant (P<0 . 01), but the first two PC axes cumulatively accounted for 71 % of the total GrE interaction. In contrast, the AMMI stability statistics suggested different genotypes to be the most stable. Most of the AMMI stability statistics showed biological stability, but the SIPCF statistics of AMMI model had agronomical concept stability. The AMMI stability value (ASV) identified genotype FLIP 92-12L as a more stable genotype, which also had high mean performance. Such an outcome could be regularly employed in the future to delineate predictive, more rigorous recommendation strategies as well as to help define stability concepts for recommendations for lentil and other crops in the Middle East and other areas of the world.
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