Multi-environment analysis of grain quality traits in recombinant inbred lines of a biparental cross in bread wheat (<i>Triticum aestivum</i> L.)

Krishnappa, Gopalareddy; Ahlawat, Arvind Kumar; Shukla, R. B.; Singh, Sumit; Singh, Akanksha; Singh, G. P.

doi:10.1556/0806.47.2019.02

Cited by 10 publications

(13 citation statements)

References 21 publications

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“…The variability of plant height and ear emergence data was also affected to a similar extent by this interaction. Significant effect of GE interaction on TKW has been previously reported by other studies (Gómez-Becerra et al, 2010;Tayyar, 2010;Sharma et al, 2013;Khazratkulova et al, 2015;Krishnappa et al, 2019). The high contribution of the genotype to the variation of TKW and plant height indicates that for the studied DH lines these two traits are most stable compared with ear emergence.…”

Section: Discussion Discussion Discussionsupporting

confidence: 71%

Grain size and other agronomical traits variation in a winter wheat population of doubled haploid lines

Ciulcă

Giura²,

Ciulca

2020

Not Bot Horti Agrobo

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In wheat, the size of the grain, respectively its dimensions as well as degree of filled, are important characteristics on which depends both the weight of the grain and yield of flour, the quality of milling and baking as well as the production capacity of the respective genotype. This paper presents the results obtained by studying for three years, under field condition, 85 doubled haploid (DH) lines obtained from the F1’s of ‘G.603-86’ (large grains genotype) × ‘F.132’ (normal grains genotype) crosses using biotechnological Zea system. The environmental conditions of the three years had an important contribution on the genotype × year interaction, which showed also a higher influence on 1000 kernel weight (TKW). The variability of plant height and ear emergence data was also affected to a similar extent by this interaction. Based on the performed results and analyses, were highlighted lines which show high and stable values of TKW (54-64 g), associated with a plants height of approximately 85-100 cm and an ear emergence from May 11 to 17, under some climatic conditions similar to the period of study. These doubled haploids lines can be considered as promising genotypes for using in wheat breeding programs in order to improve yield performances under temperate continental climate conditions.

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Section: Discussion Discussion Discussionsupporting

confidence: 71%

Grain size and other agronomical traits variation in a winter wheat population of doubled haploid lines

Ciulcă

Giura²,

Ciulca

2020

Not Bot Horti Agrobo

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“…AMMI models are widely used in plant breeding. In recent years (2017-2019), they have been applied to evaluate various plant species, from the most popular crops such as wheat [18][19][20][21], oilseed rape [17,22], maize [23][24][25], rice [26][27][28][29], and sugar beet [30] to cassava [31], peanuts [32], and non-edible crops such as cotton [33] and willow [16].…”

Section: Introductionmentioning

confidence: 99%

The Characterization of 10 Spring Camelina Genotypes Grown in Environmental Conditions in North-Eastern Poland

et al. 2020

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Camelina (Camelina sativa (L.) Crantz) is an alternative oilseed crop that is garnering increasing popularity due to its multiple applications and greater tolerance to adverse environmental conditions than oilseed rape. The study analyzed selected traits of 10 Canadian and Polish spring camelina genotypes grown in a field experiment in north-eastern Poland in 2015–2018. The greatest differences were observed in seed yield where the effect of weather and environmental conditions explained 72.7% of variance, the effect of genotype explained 5.9% of variance, and the effect of the genotype-by-environment interaction explained 5.7% of total variance. In contrast, 1000-seed weight was not affected by environmental conditions, and it was differentiated only by genotype which explained 73.3% of variance. Genotype was responsible for 4.5%–25.3% of the variance in the remaining traits. The genotype-by-environment interaction explained 2.0%–18.8% of variance in the examined traits. The additive main effects and multiplicative interaction model (AMMI) revealed that genotype 13CS0787-15 was potentially most suited for cultivation in the temperate climate of north-eastern Poland, Central Europe. This genotype was characterized by the highest seed yields and straw yields, as well as the greatest yield stability.

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“…However, rather than making comparisons over all sorts of GEI studies in wheat, it would make much more sense to search specifically for studies based on RILs, as they typically include a large number of genotypes tested over just a few environments. If some recent studies based on RILs are considered, there is almost no evidence for the dominant effect of E. It was reported for GPC only by Prashant et al [40], while Echeverry-Solarte et al [67] and Krishnappa et al [38] detected equal effects of G and E for the same trait. On the contrary, in Goel et al [68], the effect of E was smallest for GPC, WGC, and TW.…”

Section: Gei Patternsmentioning

confidence: 95%

“…Specifically, regardless of the high and significant effect of GEI, AMMI model was not particularly successful in identifying stable genotypes for loaf volume [41]. Nevertheless, AMMI model has been able to successfully identify specifically adapted as well as stable wheat genotypes for the majority of quality traits examined in RIL populations [38].…”

Section: Introductionmentioning

confidence: 91%

“…Although still not numerous, studies have shown that AMMI model can be used to successfully analyze GEI and its structure for wheat quality traits in RIL populations [37]. Among the traits tested in RIL populations, GPC is shown to be under the largest influence of environment, as well as of joint effects of environment and GEI (>98% and >99% of contribution to the total sum of squares, respectively) [38]. The predominant influence of environment, with more than 90% of phenotypic variation due to the joint influence of environment and GEI was reported by Elangovan et al [39] for both GPC and TW.…”

Section: Introductionmentioning

confidence: 99%

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Capturing GEI Patterns for Quality Traits in Biparental Wheat Populations

et al. 2021

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Genotype-by-environment interaction (GEI) is often a great challenge for breeders since it makes the selection of stable or superior genotypes more difficult. In order to reduce drawbacks caused by GEI and make the selection for wheat quality more effective, it is important to properly assess the effects of genotype, environment, and GEI on the trait of interest. In the present study, GEI patterns for the selected quality and mixograph traits were studied using the Additive Main Effects and Multiplicative Interaction (AMMI) model. Two biparental wheat populations consisting of 145 and 175 RILs were evaluated in six environments. The environment was the dominant source of variation for grain protein content (GPC), wet gluten content (WGC), and test weight (TW), accounting for approximately 40% to 85% of the total variation. The pattern was less consistent for mixograph traits for which the dominant source of variation has been shown to be trait and population-dependent. Overall, GEI has been shown to play a more important role for mixograph traits compared to other quality traits. Inspection of the AMMI2 biplot revealed some broadly adapted RILs, among which, MG124 is the most interesting, being the prevalent “winner” for GPC and WGC, but also the “winner” for non-correlated trait TW in environment SB10.

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Multi-environment analysis of grain quality traits in recombinant inbred lines of a biparental cross in bread wheat (Triticum aestivum L.)

Cited by 10 publications

References 21 publications

Grain size and other agronomical traits variation in a winter wheat population of doubled haploid lines

Grain size and other agronomical traits variation in a winter wheat population of doubled haploid lines

The Characterization of 10 Spring Camelina Genotypes Grown in Environmental Conditions in North-Eastern Poland

Capturing GEI Patterns for Quality Traits in Biparental Wheat Populations

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