Estimation of Combining Ability and Gene Action for Improvement Drought Tolerance in Bread Wheat (Triticum aestivum L.) Using GGE Biplot Techniques

Farshadfar, Ezatollah; Hasheminasab, Hojjat; Yaghotipoor, Anita

doi:10.5539/jas.v4n9p1

Cited by 23 publications

(34 citation statements)

References 12 publications

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“…The other traits in this study including LWC (r = -0.421) and LT (r = 0.468) had no significant correlation with YSI. The differential relations of relative physiological traits to YSI may be attributed to environmental effects on plant growth [11,17]. Delacy et al [34] and Yan [35] stated that genotype by environment interaction is a major problem in the study of quantitative traits because it reduces the association between genotypic and phenotypic values and complicates the process of selecting of genotypes with superior performance.…”

Section: Simple Correlation Analysismentioning

confidence: 99%

“…The results of path analysis were consistent with stepwise multiple linear regression analysis (Table 6) indicating RWP, RWC, CTD and ETE were the best physiological traits related to water status for modeling of YSI. Farshadfar and Hasheminasab [11] reported that genetic gain in developing tolerance in bread wheat could be achieved through indirect selection of physiological indicators related to water status, because the additive genes mainly controlled these traits.…”

Section: Path Analysismentioning

confidence: 99%

“…These indices are highly dependent on yield potential and crop phenology which are characters with a high genotype x environment interaction [6]. Thus, plant breeders have always looked for appropriate and repeatable indicators to screen germplasms for drought tolerance [10][11]. Physiologists have often suggested that the identification and selection of physiological and/or morphological traits is an effective approach to breeding for higher yield, and could be a valuable strategy for use in conjunction with normal methods of plant breeding [12][13].…”

Section: Introductionmentioning

confidence: 99%

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Application of Physiological Traits Related to Plant Water Status for Predicting Yield Stability in Wheat under Drought Stress Condition

Hasheminasab¹

2014

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The objective of the present study was to model the relationship between yield stability index (YSI) and some physiological traits related to plant water status. Fifteen bread wheat (Triticum aestivum L.) genotypes with wide range of sensitivity to drought were used in a randomized complete block design with three replications under two different environments (irrigated and rainfed) in 2012-2013 at the experimental farm of College of Agriculture, Razi University, Kermanshah, Iran. The results showed that YSI had positive and significant relationship with relative water protection (RWP, r = 0.858**), relative water content (RWC, r = 0.594*), canopy temperature depression (CTD, r = 0.669**), stomata resistance (SR, r = 0.643**) and evapotranspiration efficiency (ETE, r = 0.818**), and negative significant correlation with relative water loss (RWL, r = -0.822**) and excised leaf water loss (ELWL, r = -0.543*) under drought stress condition. Also ETE (0.46*) and RWP (0.806) had the highest direct and indirect effects on YSI, respectively. Multiple linear regression analysis indicated that the predicting model for YSI explained 97.9% of the total variation within the measured traits. The residual plots analysis indicated no problem in the model with selected variables. On the other hand, t-test showed that some of the variables are not important to be present in this model. The results of path and stepwise multiple linear

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Section: Simple Correlation Analysismentioning

confidence: 99%

Section: Path Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Application of Physiological Traits Related to Plant Water Status for Predicting Yield Stability in Wheat under Drought Stress Condition

Hasheminasab¹

2014

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“…Thus, it would be expected that additive and additive by additive genetic variances were more important than dominance genetic variance which is contained within SCA. In this respect, many authors obtained similar results among them Desai andSingh (2001), El-Shenawy et al,(2003), Melani and Carena (2005), Katta et al,(2007) Rather et al (2007), Moterle et al,(2011), Borghi et al,(2012), Ezatollah et al,(2012), Gakunga et al,(2012) and Haddadi et al,(2012).…”

mentioning

confidence: 66%

COMPARATIVE STUDY BETWEEN TWO MATING DESIGNS TO ESTIMATE DIFFERENT GENETIC PARAMETERS IN CORN (Zea maize, L.)

El–Adl

El–Hadi

Kash

et al. 2013

Journal of Agricultural Chemistry and Biotechnology

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In Egypt, as well as many other countries, corn is considered an important field crop. Due to the importance of corn, scientists in all countries gave corn breeding great concern. Many authors obtained high values for heterosis from the F1 maize hybrids. It is found that the amounts of heterosis from the MP % for the diallel cross mating design were: 179.30, 17.78, 51.97 and 52.77% for Ear weight, No. of rows/ear, No. of kernels/row and 100 kernels weight at Mansoura location, respectively. The values of heterosis were: 107.13, 9.06, 31.07 and 65.30% for the same traits at the second location (Sohag), respectively. However, the estimated amounts of heterosis with respect to t BP % were: 152.48, 3.79, 26.36 and 38.7% for Ear weight, No. of rows/ear, No. of kernels/row and 100 kernels weight at Mansoura, respectively. They were: 68.70,-1.32, 23.05 and 51.12% for the same traits at Sohag, respectively. But for the line x tester mating design, it is appeared that the amounts of heterosis from the MP % were: 51.14, 3.20, 11.7 and 44.60% for ear weight, No. of rows/ear, No. of kernels/row and 100 kernels weight at Mansoura, respectively. The values of heterosis were: 121.1, 19.0, 42.6 and 50.17% for the same traits at Sohag, respectively. ًWhile the estimated amounts of heterosis with respect to the BP % were: 26.33,-16.13, 1.92 and 24.32% for ear weight, No. of rows/ear, No. of kernels/row and 100 kernels weight at Mansoura, respectively. They were: 89.7,-4.2, 5.5 and 21.82% for the same traits at Sohag, respectively. GCA and SCA are usually used to estimate the types and the nature of gene action that present within hybrids. In this respect, there are different mating designs are known to obtain the estimates for these two components. Among these mating designs i.e. diallel crosses and line x testers mating designs. These two mating designs yield estimates for both GCA and SCA. The mean squares for GCA at Mansoura were highly significant for No. of kernels/row and 100 kernels weight. In general, the magnitudes of the mean squares at Sohag were larger than their corresponding estimates at Mansoura for Ear weight and No. of rows/ear while, it was the vice versa for No. of kernels/row and 100 kernels weight. The mean squares of the GCA of all yield component traits were larger in their magnitudes than their corresponding estimates of SCA at Mansoura. It is found that the results for the line x tester mating design indicated that the mean squares of GCA were highly significant. Therefore, both additive and additive by additive genetic variance appeared to be the most important and reliable component of genetic variances. The presence of significant estimates of GCA and SCA suggest the importance of either additive (GCA) or non additive gene action (SCA). Indeed, superior hybrids depend on the presence of dominance genetic variance. In the same time, superior hybrids would depend on additive by additive genetic epistasis in case of the absence of the dominance variance. Therefore, it is very important to estimate the two ...

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“…Le rendement en grains est un caractère à hérédité complexe et il est fortement affecté par l'environnement [3]. Il est la résultante de l'interaction de plusieurs caractéristiques morpho-physio-agronomiques, dont les composantes du rendement sont les plus déterminantes [4]. L'amélioration des caractères complexes comme le rendement est accomplie via l'amélioration des différentes composantes.…”

Section: Introductionunclassified

Combining ability and gene action estimates for some yield attributes in durum wheat (<i>Triticum turgidum L. var. durum)</i>

Hannachi¹,

Fellahi²,

Rabti³

et al. 2017

J. Fundam and Appl Sci.

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Combining ability and gene action 6 half diallel crosses. Results revealed that ability mean squares were significant for all studied additive and nonadditive components in the predominance of additive gene effects for From the GCA effect, it was observed that combiner for all yield component ombining ability and gene action of a set of durum wheat characters were studied using 6 6 half diallel crosses. Results revealed that general (GCA) and specific (SCA) combining were significant for all studied traits, suggesting the importance of both additive and nonadditive components in the inheritance of these traits. Baker ratio indicate the predominance of additive gene effects for the majority of traits studied except grain yield.it was observed that none of the six parents was yield components. Among the fifteen crosses, Zenati-Bouteille/Flamengo x followed by Waha x Ofanto, Waha x Mexicali 75 and Ofanto x Guemgoum Rkhem the greatest positive SCA effect for grain yield. Days to heading index could be used as an indirect selection criterion for better grain yield.selecting early heading genotypes having high fertile tillers number could improve grain

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Estimation of Combining Ability and Gene Action for Improvement Drought Tolerance in Bread Wheat (Triticum aestivum L.) Using GGE Biplot Techniques

Cited by 23 publications

References 12 publications

Application of Physiological Traits Related to Plant Water Status for Predicting Yield Stability in Wheat under Drought Stress Condition

Application of Physiological Traits Related to Plant Water Status for Predicting Yield Stability in Wheat under Drought Stress Condition

COMPARATIVE STUDY BETWEEN TWO MATING DESIGNS TO ESTIMATE DIFFERENT GENETIC PARAMETERS IN CORN (Zea maize, L.)

Combining ability and gene action estimates for some yield attributes in durum wheat (<i>Triticum turgidum L. var. durum)</i>

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