scholarly journals Quantitative trait loci associated with soft wheat quality in a cross of good by moderate quality parents

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4498
Author(s):  
Gioconda Garcia-Santamaria ◽  
Duc Hua ◽  
Clay Sneller
Keyword(s):  
Soft Wheat ◽  
Water Retention Capacity ◽  
Quality Traits ◽  
Retention Capacity ◽  
Flour Protein ◽  
Solvent Retention ◽  
Flour Yield ◽  
Transgressive Segregants ◽  
End Use ◽  
Genomic Regions

Information on the genetic control of the quality traits of soft wheat (Triticum aestivum) is essential for breeding. Our objective was to identify QTL associated with end-use quality. We developed 150 F4-derived lines from a cross of Pioneer 26R46 × SS550 and tested them in four environments. We measured flour yield (FY), softness equivalent (SE), test weight (TW), flour protein content (FP), alkaline water retention capacity (AWRC), and solvent retention capacity (SRC) of water (WA), lactic acid (LA), sucrose (SU), sodium carbonate (SO). Parents differed for nine traits, transgressive segregants were noted, and heritability was high (0.67 to 0.90) for all traits. We detected QTL distributed on eight genomic regions. The QTL with the greatest effects were located on chromosome 1A, 1B, and 6B with each affecting at least five of ten quality traits. Pioneer 26R46 is one of the best quality soft wheats. The large-effect QTL on 1A novel and accounted for much of the variation for AWRC (r2 = 0.26), SO (0.26) and SE (0.25), and FY (0.15) and may explain why Pioneer 26R46 has such superior quality. All alleles that increased a trait came from the parent with the highest trait value. This suggests that in any population that marker-assisted selection for these quality traits could be conducted by simply selecting for the alleles at key loci from the parent with the best phenotype without prior mapping.

scholarly journals Quantitative trait loci associated with soft wheat quality in a cross of good by moderate quality parents

2017 ◽  
Author(s):  
Gioconda Garcia-Santamaria ◽  
Duc Hua ◽  
Clay Sneller
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Soft Wheat ◽  
Quality Traits ◽  
Gluten Strength ◽  
Retention Capacity ◽  
Significant Difference ◽  
Trait Loci ◽  
End Use ◽  
Trait Associations

Information on the genetic control of the quality traits of soft wheat (Triticum aestivum L. em. Thell) is essential for breeding. Gluten strength is a measure of quality and has particular relevance to soft wheat as identity-preserved programs for strong-gluten soft red winter wheat in the eastern US that is essential to effective biscuit industry. Identifying areas of the soft wheat genome harboring genes for functional end-use quality may assist in selective breeding and in understanding the genetic components of this trait. Our objective was to identify Quantitative Trait Loci associated with end-use quality. We developed 150 F4-derived lines from a cross of Pioneer 26R46 × SS550 and tested them in four environments. We measured flour yield (FY), softness equivalent (SE), test weight (TW), flour protein content (FP), alkaline water retention capacity (AWRC), and solvent retention capacity (SRC) of water (WA), lactic acid (LA), sucrose (SU), sodium carbonate (SO) SRCs. Analyses of variance for the ten quality parameters detected a significant difference between parental means for nine traits except for FP. Recombinant inbred lines presented transgressive segregation and high heritability (0.67 to 0.90) for all traits. Strong positive correlations between AWRC with WA, SO, SU and strong negative correlations of FY with AWRC and the SRC traits were observed. We report 28 marker-trait associations. Many QTL were coincident and in accordance with the trait correlations. There were 10 marker-trait associations from four regions for these traits and only one was not coincident with another. We detected QTL distributed on 8 chromosomes. Loci associated with FP mapped on chromosomes 2B, 5A and 5D explained 16 %, 10 % and 12.9 % of the variation for this trait, respectively. QTLs on chromosome 2B co-segregated for SE. SE was negatively correlated (-0.26) with FP. A positive significant correlation between FP and LA (0.36) was detected, yet; the QTL for these two traits were not coincident in this study. The QTL with the greatest effects were located on chromosome 1A, 1B, and 6B with each affecting at least five of ten quality traits. In particular, QTL with the largest effect on LA and consequently gluten strength were on chromosomes 1A with LOD 9 that explained 42.6 % of LA variation and QTLs on chromosome 1B with LOD 9 that explained 33 % of the variation in LA. Loci on chromosomes 1A and 1B were also important contributors of additive effects for this trait with an increase of 6.5 % and 5.6 %, respectively. The largest QTL on 1A co-segregated for AWRC (25 %), SO (26 %) and SE (25 %), and FY (15 %) may explicate why Pioneer 26R46 has such superior quality. All alleles that increased a trait came from the parent with the highest trait value. This suggests that in any population that marker-assisted selection for these quality traits could be conducted by simply selecting for the alleles from the parent with the best phenotype.

scholarly journals Quantitative trait loci associated with soft wheat quality in a cross of good by moderate quality parents

2017 ◽  
Author(s):  
Gioconda Garcia-Santamaria ◽  
Duc Hua ◽  
Clay Sneller
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Soft Wheat ◽  
Quality Traits ◽  
Gluten Strength ◽  
Retention Capacity ◽  
Significant Difference ◽  
Trait Loci ◽  
End Use ◽  
Trait Associations

Information on the genetic control of the quality traits of soft wheat (Triticum aestivum L. em. Thell) is essential for breeding. Gluten strength is a measure of quality and has particular relevance to soft wheat as identity-preserved programs for strong-gluten soft red winter wheat in the eastern US that is essential to effective biscuit industry. Identifying areas of the soft wheat genome harboring genes for functional end-use quality may assist in selective breeding and in understanding the genetic components of this trait. Our objective was to identify Quantitative Trait Loci associated with end-use quality. We developed 150 F4-derived lines from a cross of Pioneer 26R46 × SS550 and tested them in four environments. We measured flour yield (FY), softness equivalent (SE), test weight (TW), flour protein content (FP), alkaline water retention capacity (AWRC), and solvent retention capacity (SRC) of water (WA), lactic acid (LA), sucrose (SU), sodium carbonate (SO) SRCs. Analyses of variance for the ten quality parameters detected a significant difference between parental means for nine traits except for FP. Recombinant inbred lines presented transgressive segregation and high heritability (0.67 to 0.90) for all traits. Strong positive correlations between AWRC with WA, SO, SU and strong negative correlations of FY with AWRC and the SRC traits were observed. We report 28 marker-trait associations. Many QTL were coincident and in accordance with the trait correlations. There were 10 marker-trait associations from four regions for these traits and only one was not coincident with another. We detected QTL distributed on 8 chromosomes. Loci associated with FP mapped on chromosomes 2B, 5A and 5D explained 16 %, 10 % and 12.9 % of the variation for this trait, respectively. QTLs on chromosome 2B co-segregated for SE. SE was negatively correlated (-0.26) with FP. A positive significant correlation between FP and LA (0.36) was detected, yet; the QTL for these two traits were not coincident in this study. The QTL with the greatest effects were located on chromosome 1A, 1B, and 6B with each affecting at least five of ten quality traits. In particular, QTL with the largest effect on LA and consequently gluten strength were on chromosomes 1A with LOD 9 that explained 42.6 % of LA variation and QTLs on chromosome 1B with LOD 9 that explained 33 % of the variation in LA. Loci on chromosomes 1A and 1B were also important contributors of additive effects for this trait with an increase of 6.5 % and 5.6 %, respectively. The largest QTL on 1A co-segregated for AWRC (25 %), SO (26 %) and SE (25 %), and FY (15 %) may explicate why Pioneer 26R46 has such superior quality. All alleles that increased a trait came from the parent with the highest trait value. This suggests that in any population that marker-assisted selection for these quality traits could be conducted by simply selecting for the alleles from the parent with the best phenotype.

scholarly journals Effect of Radio Frequency Cold Plasma Treatment on Intermediate Wheatgrass (Thinopyrum intermedium) Flour and Dough Properties in Comparison to Hard and Soft Wheat (Triticum aestivum L.)

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Sophie Held ◽  
Catrin E. Tyl ◽  
George A. Annor
Keyword(s):  
Plasma Treatment ◽  
Cold Plasma ◽  
Soft Wheat ◽  
Thinopyrum Intermedium ◽  
Retention Capacity ◽  
Intermediate Wheatgrass ◽  
Hard Wheat ◽  
Protein Secondary Structures ◽  
Solvent Retention ◽  
Solvent Retention Capacity

Cold plasma is an emerging technology to improve microbiological safety as well as functionality of foods. This study compared the effect of radio frequency cold plasma on flour and dough properties of three members of the Triticeae tribe, soft as well as hard wheat (Triticum aestivum L.) and intermediate wheatgrass (Thinopyrum intermedium, IWG). These three flour types differ in their protein content and composition and were evaluated for their solubility, solvent retention capacity, starch damage, GlutoPeak and Farinograph profiles, and protein secondary structures. Plasma treatment resulted in dehydration of flours but did not change protein content or solubility. Farinograph water absorption increased for all flours after plasma treatment (from 56.5–61.1 before to 71.0–81.6%) and coincided with higher solvent retention capacity for water and sodium carbonate. Plasma treatment under our conditions was found to cause starch damage to the extent of 3.46–6.62% in all samples, explaining the higher solvent retention capacity for sodium carbonate. However, Farinograph properties were changed differently in each flour type: dough development time and stability time decreased for hard wheat and increased for soft wheat but remained unchanged in intermediate wheatgrass. GlutoPeak parameters were also affected differently: peak torque for intermediate wheatgrass increased from 32 to 39.5 GlutoPeak units but was not different for the other two flours. Soft wheat did not always aggregate after plasma treatment, i.e., did not aggregate within the measurement time. It was also the only flour where protein secondary structures were changed after plasma treatment, exhibiting an increase from 15.2 to 27.9% in β-turns and a decrease from 59.4 to 47.9% in β-sheets. While this could be indicative of a better hydrated gluten network, plasma-treated soft wheat was the only flour where viscoelastic properties were changed and extensibility decreased. Further research is warranted to elucidate molecular changes underlying these effects.

scholarly journals Genetic Diversity and Association Analysis for Solvent Retention Capacity in the Accessions Derived from Soft Wheat Ningmai 9

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Peng Jiang ◽  
Ping-Ping Zhang ◽  
Xu Zhang ◽  
Hong-Xiang Ma
Keyword(s):  
Quality Evaluation ◽  
First Generation ◽  
Second Generation ◽  
Wheat Breeding ◽  
Soft Wheat ◽  
Neighbor Joining ◽  
Retention Capacity ◽  
Solvent Retention ◽  
First And Second Generation ◽  
Solvent Retention Capacity

Solvent retention capacity (SRC) test is an effective method for quality evaluation of soft wheat. Ningmai 9 is a founder in soft wheat breeding. The SRC and genotype of Ningmai 9 and its 117 derivatives were tested. Association mapping was employed to identify the quantitative trait loci (QTL) associated with SRCs. Ningmai 9 had the allele frequency of 75.60% and 67.81% to its first- and second-generation derivatives, respectively, indicating higher contribution than theoretical expectation. Neighbor-joining cluster based on the genotyping data showed that Ningmai 9 and most of its first-generation derivatives were clustered together, whereas its second-generation derivatives were found in another group. The variation coefficients of SRCs in the derivatives ranged from 5.35% to 8.63%. A total of 29 markers on 13 chromosomes of the genome were associated with the SRCs. There were 6 markers associated with more than one SRC or detected in two years. The results suggested that QTL controlling SRCs in Ningmai 9 might be different from other varieties. Markers Xgwm44, Xbarc126, Xwmc790, and Xgwm232 associated with SRCs in Ningmai 9 might be used for quality improvement in soft wheat breeding.

Evaluation of carbohydrate properties and end-use quality of hexaploid triticale and its relationship to solvent retention capacity

2018 ◽  
Vol 84 ◽  
pp. 95-102
Author(s):  
Bernadett Langó ◽  
Lajos Bóna ◽  
Perry K.W. Ng ◽  
Erika Ács ◽  
Kitti Török ◽  
...  
Keyword(s):  
Hexaploid Triticale ◽  
Retention Capacity ◽  
Solvent Retention ◽  
End Use ◽  
Solvent Retention Capacity

scholarly journals Zastosowanie metody SRC (Solvent Retention Capacity) do określania przydatności technologicznej mąki pszennej

2021 ◽  
Vol 126 (1) ◽  
pp. 39-50
Author(s):  
Bartosz Zimnicki ◽  
Sylwia Mildner-Szkudlarz ◽  
Radosław Spychaj ◽  
Mateusz Gutsche
Keyword(s):  
Triticum Aestivum ◽  
Soft Wheat ◽  
Retention Capacity ◽  
Solvent Retention ◽  
Solvent Retention Capacity

Celem opracowania było przedstawienie syntetycznej wiedzy o metodzie SRC (ang. Solvent Retention Capacity), z uwzględnianiem jej historii, dostępnych wariantów aparaturowych, zasad postępowania podczas wykonania oznaczenia oraz kierunków zastosowania. Metoda SRC została opracowana w połowie XX w. do oceny jakości mąki z pszenicy miękkiej (ang. soft wheat) pochodzącej z Ameryki Północnej. W publikacjach z XXI w. przedstawiono dane wskazujące na przydatność i szeroki zakres stosowania metody SRC także do oceny jakości mąki z klasycznej europejskiej pszenicy zwyczajnej (Triticum aestivum) oraz z mąk uzyskanych z innych zbóż, jak: jęczmień, owies, pszenżyto i żyto. Metoda SRC jest testem solwatacyjnym bazującym na ocenie zdolności pęcznienia składników mąki w środowisku wybranych roztworów. Zastosowanie w omawianej metodzie nie jednego, lecz trzech roztworów (rozcieńczonego wodnego roztworu węglanu sodu, stężonego wodnego roztworu sacharozy i rozcieńczonego wodnego roztworu kwasu mlekowego) oraz wody jest kluczowe dla oceny możliwości zastosowania mąki w poszczególnych procesach technologicznych. Wykorzystanie powinowactwa tych roztworów do głównych funkcjonalnych polimerów mąki pszennej, jakim są białka glutenowe, skrobia uszkodzona oraz pentozany, pozwala na określnie ich wpływu na właściwości mąki oraz na jakość produktów końcowych w technologii piekarskiej i ciastkarskiej. Metoda SRC umożliwia ocenę właściwości mąki, dokonanie doboru odmian czy metod uprawy, co ma istotne znaczenie w młynarstwie oraz w zakładach produkcyjnych, w których mąka pszenna jest podstawowym surowcem.

Solvent retention capacities as indirect selection criteria for sugar snap cookie quality in Chinese soft wheats

2008 ◽  
Vol 59 (10) ◽  
pp. 911 ◽  
Author(s):  
Yong Zhang ◽  
Qijun Zhang ◽  
Zhonghu He ◽  
Yan Zhang ◽  
Guoyou Ye
Keyword(s):  
Selection Criteria ◽  
Selection Criterion ◽  
Indirect Selection ◽  
Mean Value ◽  
Soft Wheat ◽  
Direct Selection ◽  
Genetic Progress ◽  
Retention Capacity ◽  
Cookie Quality ◽  
Solvent Retention

Development of soft wheat cultivars with high sugar snap cookie quality is one of the most important breeding objectives in south China. Lack of an efficient criterion for selection for soft wheat quality is the main reason slowing genetic progress. Seventeen Chinese soft wheat genotypes grown at three locations in 2000–01 and 2001–02 wheat seasons in the Southern Winter Wheat Region, were used to investigate the potential of solvent retention capacity (SRC) parameters as indirect selection criteria for improving cookie diameter. All traits investigated displayed medium to high broad-sense heritability. Lactic acid SRC and sucrose SRC had the highest heritability, with the estimate being 0.92 and 0.86 on across-environment genotype mean value, while ranging from 0.93 to 0.99 and from 0.95 to 0.99, respectively, in the six individual environments. Sucrose SRC was highly significantly and negatively correlated with cookie diameter on both phenotypic and genotypic levels, with values of –0.86 (P < 0.001) and –0.91 (P < 0.001) on across-environment genotype performance, and ranging from –0.71 (P < 0.01) to –0.86 (P < 0.001) and from –0.79 (P < 0.001) to –0.93 (P < 0.001), respectively, in the six environments. Sucrose SRC was found to be a good selection criterion for improving cookie diameter. When applying the same intensity, genetic progress on cookie diameter achieved through sucrose SRC selection was as efficient as that for cookie diameter itself on across-environment genotype performance, while slightly less efficient on within-environment genotype performance, with the relative selection efficiency ranging from 0.81 to 0.90. Moreover, indirect selection through sucrose SRC was always more efficient than direct selection under the assumption of equivalent cost, with the relative efficiency of 1.52 based on across-environment selection, and ranged from 1.22 to 1.36 on within-environment selection.

Selection of cultivars for soft wheat quality. 2. Small scale tests of soft wheat quality

1973 ◽  
Vol 13 (62) ◽  
pp. 299 ◽  
Author(s):  
HJ Moss ◽  
CS Edwards ◽  
NA Goodchild
Keyword(s):  
Soft Wheat ◽  
Small Scale ◽  
Water Retention Capacity ◽  
Wheat Quality ◽  
Retention Capacity ◽  
Fermentation Time ◽  
Cultivar Groups ◽  
Scale Test ◽  
Milling Yield ◽  
Selection Of

Ten small scale tests of soft wheat quality have been investigated for their ability to discriminate between cultivars, and to arrange a series of samples in order of acceptability according to soft wheat criteria. The tests were grain size, fibre, protein, and ash content, pearling resistance, wheatmeal granularity, wheatmeal fermentation time, milling yield (Brabender Quadrumat Mill), sedimentation value and alkaline water retention capacity of the flour. Grain fibre and pearling resistance ranked cultivars in the same order irrespective of location or season, but the ranking according to other tests depended on environmental features. No small scale test nor combination of small scale tests was satisfactory at all sites for predictive purposes. Within most single-cultivar groups grains became harder as they became larger, while the protein level simultaneously declined.

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