Application of Wheat Meal Solvent Retention Capacity Tests Within Soft Wheat Breeding Populations

The 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.     

A Rapid,High Throughput Micro Sugar‐Snap Cookie Quality Test Procedure Using Asymmetrical Centrifugal Mixing

A modified AACC 45‐g flour cookie procedure using asymmetrical centrifuge mixing as a replacement for conventional mixing has been developed. Ingredients are added to a pin cup in the same proportion as in the Approved Method 10‐50D (AACC 2000) sugar‐snap cookie test and mixed in a single step for 15 sec at 2,500 rpm. The dough is then processed and the resulting cookies are scored according to the AACC Approved Method 10–52 40‐g flour micro cookie test method. Cookies produced from a control cookie flour and four commercial soft wheat flours with the new mixing method did not show the characteristic surface cracking patterns normally obtained with conventional three‐stage mixing. However, with the exception of one spread value, no significant differences in spread, thickness, or the ratio of spread to thickness were evident when results were compared with those obtained with the AACC Approved Method 10‐50D 225‐g flour test method using a Hobart mixer equipped with a paddle. Cookies produced from two sets of advanced soft white spring wheat breeder lines, including control cultivars, using the asymmetrical centrifuge mixing procedure were also very comparable in spread, thickness, and ratio compared with those produced using 225 g of flour in the AACC Approved Method. Reproducibility of test results for all cookie parameters for both commercial and advanced plant breeder samples were comparable to the AACC Approved Method 10‐50D 225‐g flour test method. The very short mixing time and the ability to quickly clean or use multiple pin cups should allow very high throughput of flour samples relative to the use of conventional mixers for cookie testing.     

Functional and Nutritional Characteristics of Wheat Grown in Organic and Conventional Cropping Systems

The effects of organic versus conventional farming practices on wheat functional and nutritional characteristics were compared. Soft white winter wheat and hard red spring wheat were obtained from multiyear replicated field plots near Pullman, Washington, and Bozeman, Montana. Test weight, kernel weight, and kernel diameter tended to be greater in both soft and hard organic wheat than in conventional wheat in the Pullman studies. Phenolic content and total antioxidant capacity tended to be lower in organic than in conventional wheat. Flour ash, P, and Mg contents in whole wheat flour varied in parallel among cropping systems, but levels were not consistently associated with either organic or conventional cropping systems. Protein contents of whole wheat and refined flours were similar in organic and conventional wheat from Pullman when fertility levels were similar. Higher fertility was associated with higher protein content in both organic and conventional cropping systems. Soft wheat flour from a low‐fertility organic cropping system had lower sodium carbonate, lactic acid, and sucrose solvent retention capacities, lower protein content, and greater cookie diameter and cake volume than soft wheat flour from the higher fertility organic and conventional cropping systems; the change in end‐product quality was significant in one out of two crop years. In the Bozeman hard wheat studies, higher fertility in both organic and conventional cropping systems tended to increase protein content and bread loaf volume. Results indicated that neither organic nor conventional cropping systems were associated with substantially improved mineral and antioxidant nutritional properties, and end‐use quality of wheat was more strongly associated with fertility level than with organic versus conventional cropping systems.     

Environmental Influences on Flour Quality for Sheeted Noodles in Idaho 377s Hard White Wheat

Production of common wheat (Triticum aestivum L.) in the Pacific Northwest of the United States specifically for Asian noodle products is a relatively new goal for grain producers. We surveyed commercial fields of the hard white spring wheat cultivar Idaho 377s in two years to determine the variables contributing to Asian noodle quality and to validate previous observations made with small‐plot research. Fields were surveyed in 1998 and 1999 in two areas of the Snake River Plain of southeastern Idaho separated by ≈100 km, with both irrigated fields and rain‐fed fields sampled in both zones. Samples were evaluated for grain characteristics then milled and evaluated for flour quality, alkaline noodle color, and color and texture of nonalkaline Chinese (salted, neutral pH) noodles. Grain from rain‐fed fields produced brighter and more yellow alkaline noodles than grain from irrigated fields. Grain produced in rain‐fed fields also had lower peak flour pasting viscosity than grain produced in irrigated fields. Flour ash was lowest in grain from rain‐fed fields located in a higher elevation district (Upper Valley) and greatest in grain from irrigated fields located in a lower elevation district (Lower Valley). Noodle hardness and chewiness were greater in Chinese noodles made from grain produced in the Upper Valley than grain from the Lower Valley. Chinese noodle color had significant interaction with the location and irrigation management used for producing the grain. However, Chinese noodle brightness was consistently negatively correlated with flour protein concentration. The color and texture of noodles produced from flours milled from on‐farm commercial production was consistent with previous experiment station small‐plot research.     

Oat Tocols: Saponification vs. Direct Extraction and Analysis in High‐Oil Genotypes

Tocols are natural antioxidants that occur in grains that may benefit human and animal health. Therefore, it is important to accurately measure their concentrations in foods and feeds and to determine how genetics and growing environment can influence their levels. The first objective was to evaluate saponification versus direct extraction for the analysis of tocols in oat (Avena sativa L.). The second was to determine the effects of growing environment, hulled versus hulless phenotype, and genetic background on tocol concentration, and to see whether tocol and lipid concentrations were associated. For the first objective, oat grain samples from two locations were either extracted by saponification or directly with methanol, and extracts were analyzed by HPLC. The saponification method increased yield by ≈25% and was less time‐consuming, so it was adopted for the second objective. For the second objective, oat genotypes were developed by crossing high‐oil parents from Iowa State University with hulled and hulless cultivars adapted to arid Western environments. These were grown at Aberdeen and Tetonia, ID, and the tocols and lipid concentrations were analyzed at Madison, WI. There were significant effects of growing environment, genotype, and the presence or absence of hulls on tocol concentrations. Tocol and lipid concentrations were not correlated. Progeny of crosses involving the genotype IA91098‐2 had tocol concentrations that exceeded both parents.     

Puroindoline Genotype of the U.S. National Institute of Standards & Technology Reference Material 8441, Wheat Hardness

Grain hardness (kernel texture) is of central importance in the quality and utilization of wheat (Triticum aestivum L.) grain. Two major classes, soft and hard, are delineated in commerce and in the Official U.S. Standards for Grain. However, measures of grain hardness are empirical and require reference materials for instrument standardization. For AACC Approved Methods employing near‐infrared reflectance (NIR) and the Single Kernel Characterization System (39‐70A and 55‐31, respectively), such reference materials were prepared by the U.S. Dept. of Agriculture Federal Grain Inspection Service. The material was comprised of genetically pure commercial grain lots of five soft and five hard wheat cultivars and was made available through the National Institute of Standards and Technology (SRM 8441, Wheat Hardness). However, since their establishment, the molecular‐genetic basis of wheat grain hardness has been shown to result from puroindoline a and b. Consequently, we sought to define the puroindoline genotype of these 10 wheat cultivars and more fully characterize their kernel texture through Particle Size Index (PSI, Method 55‐30) and Quadrumat flour milling. NIR, SKCS, and Quadrumat break flour yield grouped the hard and soft cultivars into discrete texture classes; PSI did not separate completely the two classes. Although all four of these methods of texture measurement were highly intercorrelated, each was variably influenced by some minor, secondary factors. Among the hard wheats, the two hard red spring wheat cultivars that possess the Pina‐D1b (a‐null) hardness allele were harder than the hard red winter wheat cultivars that possess the Pinb‐D1b allele based on NIR, PSI, and break flour yield. Among the soft wheat samples, SKCS grouped the Eastern soft red winter cultivars separate from the Western soft white. A more complete understanding of texture‐related properties of these and future wheat samples is vital to the use and calibration of kernel texture‐measuring instruments.     

Effects of Genotype and Environment on Glutenin Polymers and Breadmaking Quality

Six genotypes of hard red spring (HRS) wheat were grown at seven environments in North Dakota during 1998. Effects of genotype and environment on glutenin polymeric proteins and dough mixing and baking properties were examined. Genotype, environment, and genotype‐by‐environment interaction all significantly affected protein and dough mixing properties. However, different protein and quality measurements showed differences for relative influences of genotype and environment. Total flour protein content and SDS‐soluble glutenin content were influenced more by environmental than genetic factors, while SDS‐insoluble glutenin content was controlled more by genetic than environmental factors. Significant genotypic and environmental effects were found for the size distribution of SDS‐soluble glutenins and between SDS‐soluble and SDS‐insoluble glutenins as well as % SDS‐insoluble glutenins. With increased flour protein content, the proportions of monomeric proteins and SDS‐insoluble glutenin polymers appeared to increase, but SDS‐soluble glutenins decreased. Flour protein content and the size distribution between SDS‐soluble and SDS‐insoluble glutenin polymers were significantly correlated with dough mixing properties. Environment affected not only total flour protein content but also the content of different protein fractions and size distributions of glutenin polymers, which, in turn, influenced properties of dough mixing. Flour protein content, % SDS‐insoluble glutenin polymers in flour, and ratio of SDS‐soluble to SDS‐insoluble glutenins all were highly associated with dough mixing properties and loaf volume.     

小黑麦基因型与环境互作效应及产量稳定性分析

选用26个小黑麦品种(系),在西北高寒农牧交错区的不同试点和供水条件下,利用GGE双标图法研究了小黑麦基因型与环境互作效应以及稳产性.结果表明:在自然干旱条件下,小黑麦平均籽粒产量为1805.5 ks/hm2,较普通小麦对照增产54.6%;在灌水条件下,小黑麦平均产量为7196.1 kg/hm2,较对照增产67.2%....     

Effect of Wheat Genotype and Environment on Relationships Between Dough Extensibility and Breadmaking Quality

Dough extensibility affects processing ease, gas retention, and loaf volume of finished products. The Kieffer dough extensibility test was developed to assess extensibility of small dough samples and is therefore adapted for use in breeding programs. Information is lacking on relationships between wheat growing environments and dough properties measured by the Kieffer dough extensibility test. This study documents the variability of dough extensibility (Ext), maximum resistance to extension (Rmax), and area under the extensibility curve (Area) in relation to breadmaking quality, and the effect of wheat growing environments. Mixograph, Kieffer dough extensibility, and bake tests were performed on flour milled from 19 hard red spring wheat (Triticum aestivum L.) genotypes grown during three growing seasons (2007‐2009) at six South Dakota locations. Although both genotype and environment had significant effects on Kieffer dough extensibility variables, environment represented the largest source of variation. Among genotype means, Area was most correlated (r = 0.63) with loaf volume, suggesting that by selecting lines with increased Area, loaf volume should improve. Rmax was positively correlated (r = 0.58) with loaf volume among genotype means but negatively correlated (r = –0.80) among environmental means. Ext was positively correlated (r = 0.90) with loaf volume among environmental means. Weather variables were correlated with Rmax, Ext and loaf volume and therefore could help predict end‐use quality.     

Lipid Extraction from Wheat Flour Using Supercritical Fluid Extraction

Environmental concerns, the disposal cost of hazardous waste, and the time required for extraction in current methods encouraged us to develop an alternate method for analysis of wheat flour lipids. Supercritical fluid extraction (SFE) with carbon dioxide has provided that medium and the method is fully automatic. Crude fats or nonstarch free lipids (FL) were extracted from 4–5 g of wheat flour by an SFE system. To develop optimum conditions for SFE, various extraction pressures, temperatures, and modifier volumes were tried to provide a method that would produce an amount of lipids comparable to those extracted by the AACC Approved Soxhlet Method and the AOCS Official Butt Method using petroleum ether as solvent. Using several wheat flour samples, the best conditions were 12.0 vol% ethanol (10.8 mol%) at 7,500 psi and 80°C to extract the amount of FL similar to those by the AACC and AOCS methods. Using solid‐phase extraction, lipids were separated into nonpolar lipid (NL), glycolipid (GL), and phospholipid (PL) fractions. The mean value of five flours was 1.15% (flour weight, db) by the SFE method, 1.07% by the Butt method, and 1.01% by the Soxhlet methhod. The SFE‐extracted lipids contained less NL and more GL than either the Butt or Soxhlet methods. All three methods extracted lipids with qualitatively similar components. The overall benefit for SFE over the Soxhlet or Butt methods was to increase the number of samples analyzed in a given time, reduce the cost of analysis, and reduce exposure to toxic chemicals.     

Adaptation of AACC Method 56‐11, Solvent Retention Capacity,for Use as an Early Generation Selection Tool for Cultivar Development

The solvent retention capacity (SRC) profile is useful for studying flour components contributing to end‐use functionality. The method tests four different solvents with 5 g of flour each. Because of the amount of grain (30–40 g) typically needed to produce 20 g of flour for the SRC test, the method is not well‐suited for assessing end‐use quality of early generation breeding material, where grain quantities are limited. The method was therefore modified to require only 0.2 g of ground wheat instead of 5 g of flour per SRC solvent. The small‐scale SRC results using whole meal had correlations of r = 0.86 for lactic acid, r = 0.85 for sodium carbonate, r = 0.78 for sucrose, r = 0.74 for sodium bicarbonate (the alkaline water retention capacity method) and r = 0.69 for water when compared with SRC values from full‐scale tests using 5 g of flour. Overall, cultivars with SRC values at the extremes of the distribution were in the same ranked order for the small‐ and large‐scale SRC test results. However, variation in ranked order of cultivars between test methods was detected among samples that were not at the extremes of the distribution. Traditionally, successful wheat breeding strategies involve eliminating or advancing lines from the extremes of the distribution to increase the proportion of desirable genotypes within breeding programs. Results indicated that advancing promising germplasm or eliminating germplasm with inferior end‐use quality potential is possible using the small‐scale SRC technique to evaluate early generation wheat breeding material, as a sort of breeding triage.     

Association Between % SDS‐Unextractable Polymeric Protein (%UPP) and End‐Use Quality in Chinese Bread Wheat Cultivars

Trial I, with 33 spring cultivars, and trial II, with 21 winter cultivars, sown in four environments in the northwestern China spring wheat region and northern winter wheat region, respectively, were used to study the effect of genotype and environment on the size distribution of polymeric proteins. Association between quantity and size distribution of polymeric protein and dough properties (both trials) and northern‐style Chinese steamed‐bread (CSB) (trial I) and pan bread (trial II) qualities were also investigated. In trial I, all protein attributes, such as flour protein content, SDS‐extractable polymeric protein in the flour (EPP), SDS‐unextractable polymeric protein in the flour (UPP), and percent UPP in total polymeric protein (%UPP), were largely determined by environment, whereas variation in dough strength resulted from variation in UPP and %UPP across environments. In trial II, EPP was largely determined by environment, and UPP and %UPP were largely determined by genotype. These differences might result from different levels of protein content and dough strength in the two trials. The EPP was positively correlated with dough extensibility and was generally negatively correlated with dough stability and maximum resistance in both trials. However, %UPP was significantly positively correlated with dough stability and maximum resistance and end‐use quality in both trials. In trial I, correlation coefficients between %UPP and maximum resistance and CSB score were r = 0.90 and 0.71, respectively, whereas in trial II, the correlation coefficients between %UPP and maximum resistance and pan bread score were 0.96 and 0.87, respectively. Therefore, selection for high %UPP together with high‐quality glutenin subunits should lead to improved dough strength and end‐use quality in Chinese wheats.     

不同生态环境对强筋小麦品质的影响

研究分析不同生态环境对强筋小麦“陕优225”品质的影响结果表明,“陕优225”在黄淮麦区不同生态区种植有较强的适应能力,其品质均达到强筋小麦国家标准且具有良好的稳定性。“陕优225”品质适宜生态区以黄淮麦区旱肥地雨养生态区、中等肥力补充灌溉区为最佳,其品质可达到强筋粉小麦标准,且制粉宜选用后熟期4个月以上的小麦籽粒,其生态品质表达最佳。     

Characterization of a Unique “Super Soft” Kernel Trait in Wheat

Kernel texture in wheat (Triticum sp.) is central to end‐use quality and utilization. Here we report the discovery of a novel soft kernel trait in soft white winter wheat (T. aestivum L.). Two heritable kernel phenotypes were selected among F₃‐derived sibs, hereafter designated “normal soft” (wild‐type) and “super soft.” Normal soft lines exhibited single kernel characterization system (SKCS) hardness index (HI) values typical of soft wheat (HI ≈ 20), whereas the super soft lines were unusually soft (HI ≈ 5). Under some environments, individual super soft lines exhibited HI values as low as HI = –4. The super soft trait was manifested in reduced SKCS kernel texture and higher break flour yields, with some increase in sodium carbonate SRC (solvent retention capacity) values and sponge cake volumes. Straight‐grade flour yield, flour ash, milling score, and cookie diameter were largely unaffected. With the possible exception of the sodium carbonate SRC values, we observed no indication that the super soft trait conferred any negative aspects to commercial soft wheat quality. As such, the super soft trait may provide wheat breeders with new opportunities to modify the end‐use quality of wheat.     

Modeling End‐Use Quality in U.S. Soft Wheat Germplasm

End‐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.     

Variability and Relationships Among Mixolab,Mixograph, and Baking Parameters Based on Multienvironment Spring Wheat Trials

Because of the large number of cultivars that require examination in the development of spring wheat (Triticum aestivum L.) cultivars, breeding programs use predictive methods to test end use quality. The Mixograph is a widely used predictive test with which end use quality of many genotypes can be assessed in a short time. By comparison, the Mixolab is a relatively new device with additional capability that might be used for the same purpose. Our objective was to document variability of, and relationships among, 20 parameters obtained from Mixolab, Mixograph, and bake tests. Tests were performed on flour from 18 genotypes grown in 20 environments. Both genotype and environment had significant effects on quality parameter values. Several Mixograph and Mixolab parameters were highly significantly correlated, particularly when genotype mean values over environments were considered. Correlations between loaf volume and Mixolab parameters within environments were inconsistent and suggest that average genotype values over environments will be most useful. For example, the correlation between Mixolab stability and loaf volume (r = 0.25, P < 0.001) was much higher when genotype averages (r = 0.70, P < 0.001) were considered. Our results show that selection for Mixolab stability and water absorption should help delineate and improve the selection of genotypes with greater loaf volume.     

Solvent Retention Capacity (SRC) Testing of Wheat Flour: Principles and Value in Predicting Flour Functionality in Different Wheat‐Based Food Processes and in Wheat Breeding—A Review

Solvent retention capacity (SRC) technology, its history, principles, and applications are reviewed. Originally, SRC testing was created and developed for evaluating soft wheat flour functionality, but it has also been shown to be applicable to evaluating flour functionality for hard wheat products. SRC is a solvation test for flours that is based on the exaggerated swelling behavior of component polymer networks in selected individual diagnostic solvents. SRC provides a measure of solvent compatibility for the three functional polymeric components of flour—gluten, damaged starch, and pentosans—which in turn enables prediction of the functional contribution of each of these flour components to overall flour functionality and resulting finished‐product quality. The pattern of flour SRC values for the four diagnostic SRC solvents (water, dilute aqueous lactic acid, dilute aqueous sodium carbonate, and concentrated aqueous sucrose solutions), rather than any single individual SRC value, has been shown to be critical to various successful end‐use applications. Moreover, a new predictive SRC parameter, the gluten performance index (GPI), defined as GPI = lactic acid/(sodium carbonate + sucrose) SRC values, has been found to be an even better predictor of the overall performance of flour glutenin in the environment of other modulating networks of flour polymers. SRC technology is a unique diagnostic tool for predicting flour functionality, and its applications in soft wheat breeding, milling, and baking are increasing markedly as a consequence of many successful, recently published demonstrations of its extraordinary power and scope.     

A Comprehensive Survey of Soft Wheat Grain Quality in U.S. Germplasm

Wheat (Triticum aestivum L.) quality is dependent upon both genetic and environmental factors, which work in concert to produce specific grain, milling, flour, and baking characteristics. This study surveyed all of the 132 soft wheat varieties (cultivars and advanced breeding lines) grown in the U.S. regional nursery system, which encompassed the three main soft wheat producing regions of the United States (eastern and southern soft red winter and western soft white). The quality parameters included test weight, kernel hardness, weight, and diameter, wheat and flour protein, polyphenol oxidase, break flour yield, flour yield, flour ash, milling score, flour swelling volume, flour SDS sedimentation volume, solvent retention capacity (SRC) for water, sodium carbonate, sucrose, and lactic acid, Rapid Visco Analyzer peak pasting viscosity, and cookie diameter. High levels of variation were observed among varieties, regions, and specific environments, with environment being in general a much greater source of variation than varieties. Variety was observed to have a relatively stronger influence on wheat quality in the western nurseries, compared with the eastern and southern regions, where location effects had a stronger impact on overall wheat quality. The greater influence of variety was particularly notable for kernel hardness in the western nurseries. Kernel hardness also varied considerably as a result of environment. For the two soft red winter wheat nurseries, the western U.S. environment produced substantially harder kernels (37–40) compared with the same varieties grown in eastern U.S. locations (15–20). Intertrait quality relationships were observed to be unique to the specific nursery and germplasm in which they were studied, and these relationships were not consistent across nurseries. Nevertheless, on average, soft wheat quality was fairly similar across the United States, indicating that breeding and testing models have been successful in achieving a relatively uniform target for quality. However, many traits showed high levels of variability among varieties, suggesting that a greater level of selection for end‐use quality would benefit end users by increasing consistency and reducing variability. The often large role of environment (location) in quality indicates that end users must be assiduous in their origination and grain procurement. Clearly, “nursery mean” quality does not reflect the potential that can be obtained, as reflected by a few exceptional soft wheat varieties.     

Solvent Retention Capacities of Indian Wheats and Their Relationship with Cookie‐Making Quality

Ninety‐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.     

Influence of Cultivar and Environment on Water‐Soluble and Water‐Insoluble Arabinoxylans in Soft Wheat

Arabinoxylans are hydrophilic nonstarch polysaccharides found in wheat grain as minor constituents. Arabinoxylans can associate with large amounts of water through hydrogen bonding and can form oxidative gels. These properties are important factors in end‐use quality of wheat. The objective of this study was to delineate the influence of wheat cultivar and growing environment on variation in water‐soluble (WS‐AX), waterinsoluble (WI‐AX), and total (TO‐AX) arabinoxylan contents of flour and whole grain meal. This study included seven spring and 20 winter soft white wheat cultivars grown in 10 and 12 environments, respectively (each evenly split over two crop years). Univariate analysis of variance (ANOVA) and multivariate analysis of variance with canonical analysis (MANOVA) was used to evaluate sources of variation. Variation in arabinoxylan contents and absolute amounts (xylose equivalents) among the two cultivar sample sets (spring and winter) was similar, and both cultivar and environment were significant sources of variation. The cultivar‐by‐environment interaction was relatively unimportant. Results indicate that the variation in arabinoxylan content is primarily influenced by cultivar and secondarily influenced by environment. Within arabinoxylan fractions, WS‐AX content is primarily influenced by genotype, while WI‐AX content is more greatly influenced by the environment.