Genotype x environment interactions for, heritabilities of, and correlations among quality traits in wheat

Bhatt, G. M.; Derera, N. F.

doi:10.1007/bf00132896

Cited by 28 publications

(13 citation statements)

References 5 publications

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“…For GS to be applied effectively, plant breeders must have a sound understanding of the relationship between traits of interest as it enables optimisation of selection strategies through correlated response to selection (Bernardo 2002 ). Trait correlations in bread wheat have long been reported at the phenotypic level (Bhatt and Derera 1975 ; Fischer and Wood 1979 ). Advances in statistical techniques have since made it possible to draw genetic correlations between traits by separating the genetic variance from the residual error (Gilmour et al.…”

Section: Introductionmentioning

confidence: 99%

Increased genomic prediction accuracy in wheat breeding using a large Australian panel

et al. 2017

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Key message Genomic prediction accuracy within a large panel was found to be substantially higher than that previously observed in smaller populations, and also higher than QTL-based prediction. AbstractIn recent years, genomic selection for wheat breeding has been widely studied, but this has typically been restricted to population sizes under 1000 individuals. To assess its efficacy in germplasm representative of commercial breeding programmes, we used a panel of 10,375 Australian wheat breeding lines to investigate the accuracy of genomic prediction for grain yield, physical grain quality and other physiological traits. To achieve this, the complete panel was phenotyped in a dedicated field trial and genotyped using a custom AxiomTM Affymetrix SNP array. A high-quality consensus map was also constructed, allowing the linkage disequilibrium present in the germplasm to be investigated. Using the complete SNP array, genomic prediction accuracies were found to be substantially higher than those previously observed in smaller populations and also more accurate compared to prediction approaches using a finite number of selected quantitative trait loci. Multi-trait genetic correlations were also assessed at an additive and residual genetic level, identifying a negative genetic correlation between grain yield and protein as well as a positive genetic correlation between grain size and test weight.Electronic supplementary materialThe online version of this article (doi:10.1007/s00122-017-2975-4) contains supplementary material, which is available to authorized users.

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Section: Introductionmentioning

confidence: 99%

Increased genomic prediction accuracy in wheat breeding using a large Australian panel

et al. 2017

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“…The range of protein variation across the data was considered within acceptable deviations from the mean, noting there were some outlier values (Table ). The logic for not adjusting for protein level was based on the high heritability of protein quality tests such as R max (Bhatt & Derera, ; Eagles, Hollamby, & Eastwood, ; Fischer, O'Brien, & Quail, ; O'Brien & Ronalds, ; Pearson, Rosielle, & Boyd, ).…”

Section: Resultsmentioning

confidence: 99%

Evaluating the impact of rainfall and temperature on wheat dough strength in Western Australia

Williams

Diepeveen

2019

Cereal Chem

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Background and objectives Western Australian wheat farmers rely on the international market to sell their wheat. One advantage they have in the market place is Australia's reputation for good and reliable wheat quality. However, consecutive years of weaker‐than‐expected dough strength placed specific consistency concerns on Western Australian hard‐grained wheat exports. To investigate why weak dough strength occurred, a multi‐season set of data was compiled. It was made up of quality results from historical crop reports and breeder trials. Recycling of data was an efficient initial step to examine the problem, but to overcome limitations, modeled climate measurements and phenotype information needed to be combined with the quality data to allow mixed model statistics to be used for analysis of the unbalanced data. Findings The key findings were three climate measurements linked to weak dough properties as measured by extensograph maximum resistance. A negative relationship between dough strength and rainfall in the period 60 days after flowering, tested as the percentage of total growing season rainfall, was found. Two temperature‐related measurements were identified as having a positive relationship with dough strength. These were the number of consecutive days that had a maximum temperature of ≥28°C and mean daily temperature range occurring during the 60‐day period after flowering. Conclusions The combined impact of moisture and temperature levels during the post‐flowering period on wheat dough strength builds on the previous understanding of high temperatures changing dough strength. Significance and novelty The recycling of data was a useful first step in understanding a complex issue, and the results provide a reference guide for further research into understanding the interaction between a changing growing environment and important wheat quality parameters.

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“…It can be concluded that gliadins at this region have higher levels of polymorphisms and thus, could be used as markers for effectively discriminating different wheat variety cultivars or genotypes. Environmental effects on gliadin accumulation Wheat quality depends on a range of factors, including genotype (G), environment (E), and G × E. 36,37) Across environments, the proportion of gliadin increases when flour protein increases. 38) In this study, the possible environmental effects on gliadins in mature wheat grains were investigated with three spring type gluten near-isogenic lines, including CB037, CB037-B, and CB037-C, respectively, harvested from Yinchuan (north), Yuanmou (south), and Beijing (northeast) of China, and analyzed by our optimized UPLC method (Fig.…”

Section: Rp-uplc Optimization For Rapid Separation Of Gliadinsmentioning

confidence: 99%

Rapid separation of seed gliadins by reversed-phase ultra performance liquid chromatography (RP-UPLC) and its application in wheat cultivar and germplasm identification

Han

et al. 2015

Bioscience, Biotechnology, and Biochemistry

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To separate gliadin from wheat flour, a novel and stability-indicating reversed-phase ultra performance liquid chromatography (RP-UPLC) method is established and optimized. A comparative analysis of routine capillary electrophoresis (CE), reversed-phase high-performance liquid chromatography (RP-HPLC), and RP-UPLC was performed and the results showed that the resolution and efficiency of RP-UPLC were significantly higher than those of CE and RP-HPLC. Characteristic RP-UPLC patterns of different bread wheat variety and related species were readily identified. These results demonstrated that our RP-UPLC procedure resulted in significant improvements in sensitivity, speed, and resolution, and thus is highly useful in wheat cultivar and germplasm identification.

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Genotype x environment interactions for, heritabilities of, and correlations among quality traits in wheat

Cited by 28 publications

References 5 publications

Increased genomic prediction accuracy in wheat breeding using a large Australian panel

Increased genomic prediction accuracy in wheat breeding using a large Australian panel

Evaluating the impact of rainfall and temperature on wheat dough strength in Western Australia

Rapid separation of seed gliadins by reversed-phase ultra performance liquid chromatography (RP-UPLC) and its application in wheat cultivar and germplasm identification

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