10 research outputs found

    AMMI Model to Assess Durum Wheat Genotypes in Multi-Environment Trials

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    The goal of this research was to assess the stability and yield performance of 150 durum wheat genotypes in multi-environment trials in two locations (Diyarbakir and Kiziltepe), in 2011-2012, and 2012-2013 growing seasons. The trials were designed by Lattice Experimental Design with two replications (incomplete block design). The AMMI (Additive Main Effects and Multiplicative Interaction) and GEI (GenotypexEnvironment Interaction) analysis were used in the study to estimate GEI effects on grain yield, because of plant breeders' great interest in these models for breeding programs. AMMI evaluation indicated that genotypes made the most important contributions to treatments Sum of Squares (59.8%), environments (3.5%), and GEI (36.7%), respectively, suggesting that grain yield had been affected by environment. IPCA 1 and IPCA 2 axes (Principal Component) were significant as P< 0.01 and explained 63.8 and 36.2%, respectively. Results showed that Kiziltepe 2013 was more stable and high yielding, meanwhile Diyarbakir 2012 and Diyarbakir 2013 environments were unstable and low yielding. According to stability variance, usually the province lines were more productive and stable than some old cultivars and many landraces/genotypes. Moreover, genotype G24 was more effective in all environments. The GEI model according to AMMI analysis suggested that this genotype can be considered as a candidate, due to extensive adaptability and high performances in all environments

    PROFICIENCY OF BIPLOT METHODS (AMMI AND GGE) IN THE APPRAISAL OF TRITICALE GENOTYPES IN MULTIPLE ENVIRONMENTS

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    WOS: 000469124600043The AMMI (additive main effect and multiplicative interaction) and GGE (genotype, genotype x environment) biplot analyses were used to evaluate and identify stability and yield of Triticale genotypes at three different locations throughout two years (2014-15-2015-16). The AMMI analysis of variance showed significant genotype, environment and GE interaction and indicated 1.31, 98.40 and 0.28% of total variation, respectively. The GGE bi-plot analysis indicated 78.19% of the total variation (PC1 (priciple component) 50.01%, and PC2 26.08%). This study has been useful to discriminate genotypes with superior and stable yield evaluated by the AMMI analysis and yield stability index incorporating the AMMI stability value and yield capacity in a single non-parametric index. The AMMI analysis indicated that G4, G8 (candidate) and G6 were found to be quite promising genotypes. In the GGE biplot analysis genotypes were investigated in two mega-environments, and the first mega-environment covered E3, E5 and E6, and the second mega-environment covered E1, E2 and E4. The genotypes G6, G8, G9 and Gll were the wining genotypes in ME (mega-environment) I, G3, G4 and G12 and in ME II. The GGE and AMMI biplot approaches let us to describe the best genotypes, and G8 to be stable and high yielding for both ME, G6 only for ME I, G4 only for ME II and can be recommended to release as a cultivar

    Examination of physio-morphological parameters related with high heat stress tolerance in durum wheat

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    The heat stress restricts the yield and quality parameters of durum wheat. The objective of this study was to examine some physiological and morphological parameters, which can be easily and quickly measured and resistance to heat stress in durum wheat breeding program. The study was conducted by using a total of 13 of durum wheat genotypes. Trials were conducted in irrigated conditions according to randomised complete blocks design with split plots and 3 replications as normal and late planting time. Drought stress was eliminated with irrigation and heat stress was formed with late planting time. According to heat susceptibility index (HSI), calculated over grain yield, Firat-93, Diyarbakir-81 and Sariçanak-98 varieties showed tolerant/medium tolerant. Low canopy temperature (CT), leaf erectness and waxiness were related with heat tolerance. Although SPAD readings did not relate heat tolerance, it can be used to select the genotypes which have high yield potential. Moreover, the GGE biplot indicated that PCA 1 and PCA 2 axes (principal component) were significant as P < 0.01 and supplied to 76.29% of the complete GT (Genotype × Trait) interaction. When the parameters were analysed for genotypes, four different groups were formed, in which grain filling speed (GFS) formed the first group, chlorophyll content (SPAD), waxiness (WXN), flag leaf steepness (FLS), grain yield (GY) formed the second group, canopy temperature depression (CTD) formed the third group and grain filing duration (GFD) formed in the fourth group. The traits, which located in same group, related to each other. On the other hand, GGE biplot showed that planting times took place in different mega-environments and some cultivars were related with normal planting time, while some others genotypes were related with late planting time. Statistical results indicated that GGE biplot are informative techniques to compare varieties with planting time and traits to discover general stability, adaptation pattern for practical recommendations

    Analysis of promising barley (Hordeum vulgare L.) lines performance by AMMI and GGE biplot in multiple traits and environment

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    The development of stable and adaptable new cultivars are based only on positive results obtained from the interaction between the genotype and the environment. Therefore, the study aimed to test the stability and general adaptability of promising barley lines in terms of grain yield and traits in multi-environments. For this purpose, twelve barley genotypes were used in the study. The trials were carried out with four replications in a random design at seven environments in years 2012-13 and 2013-14. The superior and stable genotypes were identified with GGE biplot and AMMI (Additive main effects and multiplicative interaction) models. The AMMI analysis showed that the major treatment sum of squares was affected by environments (80.6%), GE (14.0%) and genotypes (5.4%), respectively. On the other hand, the first two principal component axes (PCA 1 and PCA 2) contributed to the complete interaction with 88.1%, whereas, PCA 3 and PCA 4 axes only with 12.0%. The GGE biplot indicated that G4 is adaptable for all environments, while Altikat, G2 and G3 showed specific adaptation to E1, E3 and E5, G6, G7 and G8 to E6, respectively. According to both techniques, G2, G3, G6, G7, G8 and Altikat were the best genotypes with high yield, whereas G4 was the best with high yield, and stable and general adaptation. The results of biplot indicated that G4 (ARUPO /K8755//MORA/3/CERISE/SHYRI//ALEL I/4/CANELA/5/HART-BAR) was recommended for release and it was released as HEVSEL in 2017. On the other hand; G7 and G6 were protected as genetic material to use as parent in breeding programs for yield stability and quality respectively. © 2019, ALÖKI Kft., Budapest, Hungary

    ANALYSIS OF PROMISING BARLEY (Hordeum vulgare L.) LINES PERFORMANCE BY AMMI AND GGE BIPLOT IN MULTIPLE TRAITS AND ENVIRONMENT

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    WOS: 000462830400242The development of stable and adaptable new cultivars are based only on positive results obtained from the interaction between the genotype and the environment. Therefore, the study aimed to test the stability and general adaptability of promising barley lines in terms of grain yield and traits in multi -environments. For this purpose, twelve barley genotypes were used in the study. The trials were carried out with four replications in a random design at seven environments in years 2012-13 and 2013-14. The superior and stable genotypes were identified with GGE biplot and AMMI (Additive main effects and multiplicative interaction) models. The AMMI analysis showed that the major treatment sum of squares was affected by environments (80.6%), GE (14.0%) and genotypes (5.4%), respectively. On the other hand, the first two principal component axes (PCA 1 and PCA 2) contributed to the complete interaction with 88.1%, whereas, PCA 3 and PCA 4 axes only with 12.0%. The GGE biplot indicated that G4 is adaptable for all environments, while Altikat, G2 and G3 showed specific adaptation to El, E3 and E5, G6, G7 and G8 to E6, respectively. According to both techniques, G2, G3, G6, G7, G8 and Altikat were the best genotypes with high yield, whereas G4 was the best with high yield, and stable and general adaptation. The results of biplot indicated that G4 (ARUPO /K8755//MORA/3/CERISE/SHYRIHALEL I/4/CANELA/5/HART-BAR) was recommended for release and it was released as HEVSEL in 2017. On the other hand; G7 and G6 were protected as genetic material to use as parent in breeding programs for yield stability and quality respectively
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