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

To understand the effect of low-molecular-weight (LMW) glutenin alleles at the Glu-A3 locus on sodium dodecyl sulfate (SDS) sedimentation volume and solvent retention capacity (SRC) values, 244 accessions of Chinese wheat (Triticum aestivum L.) mini core collections were investigated. In this study the significant differences in wholemeal flour SDS sedimentation volume and SRC values associated with specific glutenin alleles at the Glu-A3 locus were explained. Seven glutenin alleles at the Glu-A3 locus were confirmed by locus-specific polymerase chain reaction (PCR). SDS sedimentation volume and lactic acid SRC value were significantly affected by alleles Glu-A3b and Glu-A3g. Based on total average values, 28 varieties carrying Glu-A3b had significantly higher means of SDS sedimentation volume and lactic acid SRC value, whereas 19 varieties carrying Glu-A3g had significantly lower means. Alleles Glu-A3d and Glu-A3f significantly increased only SDS sedimentation volume and sucrose SRC value respectively. Correlation analysis showed that SDS sedimentation volume was uncorrelated with lactic acid SRC and sucrose SRC values. The Glu-A3 LMW glutenin subunit could predict 12.8% of the variance in SDS sedimentation volume, 4.7% in lactic acid SRC and 6.4% in sucrose SRC.

Relative contribution of wheat flour constituents to Solvent Retention Capacity profiles of European wheats

Suitability of solvent retention capacity tests to assess the cookie and bread making quality of European wheat flours

ABSTRACTThe relationship of solvent retention capacity (SRC) values with four solvents, alveograph and farinograph properties, and cookie‐baking performance was evaluated with 20 Chinese soft wheat genotypes, including four cultivars and 16 advanced lines grown in the 2009–2010 season. Significant positive correlations were observed between water SRC (WSRC), sodium carbonate SRC (SOSRC), lactic acid SRC, and sucrose SRC (SUSRC) values. WSRC, SUSRC, and SOSRC showed significant positive correlations with farinograph water absorption (WA), alveograph P (tenacity), and P/L (ratio of tenacity to extensibility). Cookie diameter was significantly correlated with wet gluten (r = –0.491, P < 0.05), WSRC (r = –0.882, P < 0.001), SUSRC (r = –0.620, P < 0.01), SOSRC (r = –0.712, P < 0.001), P (r = –0.787, P < 0.001), L (r = 0.616, P < 0.01), P/L (r = –0.766, P < 0.001) and WA (r = –0.620, P < 0.01), respectively. SRC values were effective predictors of cookie quality in Chinese soft wheat. Alveograph parameters were more closely correlated to cookie quality than were farinograph parameters.

Genotypic variation of spring wheats for solvent retention capacities in relation to end-use quality

The solvent retention capacity (SRC) test uses the ability of flour to retain a range of solvents as a means of evaluating economically important aspects of wheat (Triticum aestivum L.) quality: pentosan content, starch damage, gluten strength, and general water retention. Inbred lines from three soft spring wheat populations (‘Vanna’/‘Penawawa’, ‘Kanto 107’/IDO488, and M2/IDO470) were produced in replicated, irrigated trials in 2000 and 2001 to assess variance components for the SRC tests. Milling yield, flour ash, flour protein, and sugar snap cookie diameter for these genotypes were determined. Flour solvent (water, 500 g kg−1 sucrose, 50 g kg−1 sodium carbonate, and 50 g kg−1 lactic acid) retention capacities were measured, and variances estimated for genotype, genotype × environment interaction, and error terms. The variance of genotypes for SRC values in the three populations ranged from 0.67 to 0.97 of the total variance (genotype, genotype × environment, and error) not attributed to main effects of year and replication. Correlations among genotypes were significant and positive for water, sodium carbonate, and sucrose SRC within all three populations (r = 0.70 to 0.92, P < 0.01). In all three populations, these SRC values were negatively correlated with cookie diameter (r = −0.54 to −0.89, P < 0.01). Correlations between lactic acid SRC, a measure of gluten strength, and the other SRC values were complex, as was the correlation between lactic acid SRC and cookie diameter. This suggests that milling and baking quality could be improved through manipulation of flour components using SRC selection.

ABSTRACTThe solvent retention capacity (SRC) test is a relatively new AACC Approved Method (56‐11) for evaluating soft wheat flour quality. The test measures the ability of flour to retain a set of four solvents (water, 50% sucrose, 5% sodium carbonate, and 5% lactic acid) after centrifugation. The objective of this study was to evaluate the utility of wheat meal sodium carbonate and lactic acid SRC tests and SDS sedimentation volume within three populations of soft spring wheat inbred lines as tools for selecting for improved flour SRC profiles, flour extraction, and cookie and pastry quality. The populations were derived from the crosses Vanna/Penawawa, Kanto 107/IDO488, and M2/IDO470 and were grown in replicated, irrigated trials in 2000 and 2001 near Aberdeen, Idaho. Within each of the three populations, wheat meal sodium carbonate SRC effectively predicted straight‐grade flour sodium carbonate (r = 0.69–0.81) and sucrose SRC (r = 0.74–0.84). Wheat meal sodium carbonate SRC also was negatively correlated with flour extraction and sugar snap cookie diameter. Wheat meal lactic acid SRC predicted straight‐grade flour lactic acid SRC in only one population. In contrast, SDS sedimentation volume predicted straight‐grade flour lactic acid SRC in all three populations (r = 0.74–0.93). Moreover, SDS sedimentation volume and wheat meal sodium carbonate SRC were independent in two of the three populations. This suggests that the SDS sedimentation and sodium carbonate SRC may measure different intrinsic characteristics. Therefore, a combination of sodium carbonate SRC and SDS sedimentation volume analyses of wheat meal may be an efficient approach to selecting toward target SRC profiles, increased flour extraction, and larger sugar snap cookie diameter in soft wheats.

ABSTRACTNinety‐two wheat genotypes including 50 cultivars released in India and 42 germplasm lines were subjected to solvent retention capacity (SRC) tests using 1 g of flour and 1 g of whole meal to see the relationship with cookie‐making quality and the utility in breeding programs. Very high negative correlations (P < 0.001) were observed between cookie diameter and spread factor and alkaline water retention capacity (AWRC), and solvent retention capacities of both flour and whole meal samples. Multiple regression analysis showed that AWRC explained 43.8%, sodium carbonate SRC 27.3%, lactic acid SRC 15.1%, and protein content 13.8% of the total variability (multiple r = 0.87) in cookie diameter. Total variability (multiple r = 0.85) in spread factor was explained 40.3% by AWRC, 27.4% by SODSRC, 14.5% by LASRC, and 17.8% by protein content. When the technique was further used to reduce the number of parameters contributing to cookie diameter, AWRC explained 67.2% of the total variability (multiple r = 0.85) and the rest by lactic acid SRC and protein content. Surprisingly, multiple regression analysis of whole meal samples exhibited that lactic acid SRC and sodium carbonate SRC explained 88 and 12%, respectively, of the total variability (multiple r = 0.76) in cookie diameter and 78 and 22%, respectively, of the total variability (multiple r = 0.71) in spread factor. Among the soft wheat flour samples selected based on W > 7.70 cm, pentosan content as revealed by sucrose SRC explained 87.7% of the total variability (multiple r = 0.54) of cookie diameter and 83.8% of total variability (multiple r = 0.52) in spread factor. Clustering of genotypes based on SRC profiles using both flour and whole meal produced clusters with similar average cookie diameter and spread factor. The data clearly demonstrate that whole meal tests can be used in screening the recombinant lines as well as in selecting desirable genotypes for making crosses to enhance cookie‐making quality.

The aim of this study was to model various quality measuring tests using Indian wheat varieties having exceptionally high and low gluten strength. Multiple regression analyses for various quality parameters were performed. Lactic acid solvent retention capacity was positively associated with protein content and unextractable polymeric protein while sodium carbonate solvent retention capacity was positively associated with average particle size. Sedimentation value was positively associated with protein content and lactic acid solvent retention capacity. Gluten index was modeled best by lactic acid solvent retention capacity. Dough development time was positively modeled by lactic acid solvent retention capacity. Dough stability was positively modeled with unextractable polymeric protein and negatively with extractable polymeric protein and extractable monomeric protein. Water absorption was modeled positively with both lactic acid and sodium carbonate solvent retention capacity. The models can help in identified varieties giving best performance with one or more quality traits. Practical Applications Modeling of various quality measuring parameters helps in identifying the varieties giving best performance. The variables that would best describe the solvent retention capacity, sedimentation value, gluten index and dough rheological properties of flours from different bread wheat varieties.

SummaryTechnological quality in the sets of eighty commercial wheat samples was evaluated by grain milling traits (test weight, thousand kernel weight, grain hardness as Particle Size Index, one‐stream flour yield) and common analytical parameters (wet gluten and protein contents, Zeleny test value, falling number) together with the solvent retention capacity (SRC) method (AACC 56‐11). For the commercial wheat, the latter analytical procedure (originally designed for flour quality analysis) was verified also for grain wholemeal. Within the mentioned sample group, anova revealed the strongest effect of the harvest year, both for milling and for technological parameters. For the SRC profiles, the effect of the sample form used dominated the crop year influence. The grain SRCs were correlated with the milling traits foursome, while an agreement between the flour SRC profiles and technological quality data was not so tight. However, the flour lactic acid SRC was associated with the wet gluten and protein contents (r = 0.24, P < 0.05), and the protein quality as Zeleny value with the flour water SRC (r = 0.24, P < 0.05). Relationship between Zeleny's value and flour lactic acid SCR was confirmed by nonlinear Spearman correlation (R = −0.26, P < 0.05).

ABSTRACTEnd‐use quality in soft wheat (Triticum aestivum L.) can be assessed by a wide array of measurements, generally categorized into grain, milling, and baking characteristics. Samples were obtained from four U.S. regional nurseries. Selected parameters included test weight, kernel hardness, kernel size, kernel diameter, wheat protein, polyphenol oxidase activity, flour yield, break flour yield, flour ash content, milling score, flour protein content, flour SDS sedimentation volume, flour swelling volume, Rapid Visco Analyzer peak paste viscosity, solvent retention capacity (SRC) parameters, total and water‐extractable arabinoxylan (TAX and WEAX, respectively), and cookie diameter. The objectives were to model cookie diameter and lactic acid SRC as well as to compare exceptionally performing varieties for each quality parameter. Cookie diameter and lactic acid SRC were modeled by using multiple regression analyses and all of the aforementioned quality parameters. Cookie diameter was positively associated with peak paste viscosity and was negatively associated with or modeled by kernel hardness, flour protein content, sodium carbonate SRC, lactic acid SRC, and water SRC. Lactic acid SRC was positively modeled by break flour yield, milling score, flour SDS sedimentation volume, and sucrose SRC and was negatively modeled by flour protein content. Exceptionally high‐ and low‐performing varieties were selected on the basis of their responses to the aforementioned characteristics in each nursery. High‐ and low‐performing varieties exhibited notably wide variation in kernel hardness, break flour yield, milling score, sodium carbonate SRC, sucrose SRC, water SRC, TAX content, and cookie diameter. This high level of variation in variety performance can facilitate selection for improved quality based on exceptional performance in one or more of these traits. The models described allow a more focused approach toward predicting soft wheat quality.

Solvent retention capacity(SRC) is an important index for identification and evaluation of soft wheat varieties. This study aimed at identifying SRC associated markers for marker-assisted selection. One hundred and seventy-six wheat varieties(lines) in different hardness types were screened with 236 pairs of SSR primers and their SRC values of lactic acid,water,sucrose,and sodium carbonate were evaluated in three growing seasons in Lixiahe,Jiangsu Province. The association analysis was carried out using the mixed-linear model(MLM). A total of 1340 fragments were amplified on the 236 SSR loci with an average of 5.5 alleles per locus. The average polymorphism information content was 0.4663. Twenty-eight loci were identified to be associated with lactic acid SRC(13),water SRC(7),sucrose SRC(6),and sodium carbonate SRC(2) at the significant level of P 0.005,and a single locus explained 3.19%–21.84% of phenotypic variation. Marker gwm642 associated with WSRC was detected in three years. Some favorable alleles associated with SRCs were found,such as gwm642-A186,gwm642-A188,and gwm337-A178 for reducing water SRC,gwm337-A178 and gwm337-A186 for reducing sucrose SRC,and cfa2257-A129 for reducing sodium carbonate SRC. These results are informative for marker-assisted selection on SRC properties in wheat.

To select the flour parameters that relate strongly to cake-making performance, in this study the relationship between sponge cake quality, solvent retention capacity (SRC) profile and flour physicochemical characteristics was investigated using 38 soft wheat samples of different origins. Particle size average, protein, damaged starch, water-soluble pentosans, total pentosans, SRC and pasting properties were analysed. Sponge cake volume and crumb texture were measured to evaluate cake quality. Cluster analysis was applied to assess differences in flour quality parameters among wheat lines based on the SRC profile. Cluster 1 showed significantly higher sponge cake volume and crumb softness, finer particle size and lower SRC sucrose, SRC carbonate, SRC water, damaged starch and protein content. Particle size, damaged starch, protein, thickening capacity and SRC parameters correlated negatively with sponge cake volume, while total pentosans and pasting temperature showed the opposite effect. The negative correlations between cake volume and SRC parameters along with the cluster analysis results indicated that flours with smaller particle size, lower absorption capacity and higher pasting temperature had better cake-making performance. Some simple analyses, such as SRC, particle size distribution and pasting properties, may help to choose flours suitable for cake making.

Solvent retention capacity (SRC) is an important index for predicting flour functionality in soft wheat, which includes water SRC, 50% lactic acid SRC, 5% sodium carbonate SRC, and 50% sucrose SRC. To understand the SRC character of wheat varieties in China, We measured four types of SRC in 181 varieties from different wheat regions in 2008–2009 and 2009–2010 growing seasons. According to analysis of variance, all types of SRC were significantly influenced by genotype, year, and wheat region (P 0.01 or 0.05). Besides, the interactions of genotype × year and year × wheat region were also significant (P 0.01).The principal component analysis showed that component 1 had initial eigenvalue higher than 1.0, and explained 72.3% of total SRC variance. The result of clustering based on principal score showed that there was obvious variation of SRC among the 181 varieties, and each wheat region contained varieties with different SRC characteristics. The Middle and Lower Yangtze Valleys Autumn-Sown Spring Wheat Zone had more genetic resources with low SRC than other wheat regions, and varieties with medium and high SRC were mostly distributed in the Yellow and Huai River Valleys Facultative Wheat Zone. A few varieties with low SRC were selected, including Abbondanza, Fazhang 5, Huaimai 17, Ningmai 3, Ningmai 6, Wanmai 48, Xuan 7, Yangmai 13,Yangmai 17, and Zhengmai 004, which can be used in breeding and quality improvement of weak-strength wheat.

Hybrid Solvent Retention Capacity (SRC) to predict Australian soft wheat cookie quality