Hard White Wheat Research Articles

Hard White Wheat and Gold Medal Flour: General Mills' Contracting Program*

General Mills produces Gold Medal Flour, the largest branded flour product in the United States. General Mills wants to switch from using hard red wheat to hard white wheat to produce Gold Medal Flour. Hard white wheat is not widely produced in the United States. To ensure a stable supply, General Mills is creating an extensive contracting program in the northern and central Great Plains. The objective of this case is for students to understand alternative methods for procuring wheat and the importance of wheat variety functionality.

Constraints to Adoption of Hard White Wheat in Western Kansas

Constraints to Adoption of Hard White Wheat in Western Kansas

High‐Speed NIR Segregation of High‐ and Low‐Protein Single Wheat Seeds

ABSTRACTWheat breeders need a nondestructive method to rapidly sort high‐ or low‐protein single kernels from samples for their breeding programs. For this reason, a commercial color sorter equipped with near‐infrared filters was evaluated for its potential to sort high‐ and low‐protein single wheat kernels. Hard red winter and hard white wheat cultivars with protein content >12.5% (classed as high‐protein, 12% moisture basis) or < 11.5% (classed as low‐protein) were blended in proportions of 50:50 and 95:5 (or 5:95) mass. These wheat blends were sorted using five passes that removed 10% of the mass for each pass. The bulk protein content of accepted kernels (accepts) and rejected kernels (rejects) were measured for each pass. For 50:50 blends, the protein in the first‐pass rejects changed as much as 1%. For the accepts, each pass changed the protein content of accepts by ≈0.1%, depending on wheat blends. At most, two re‐sorts of accepts would be required to move 95:5 blends in the direction of the dominant protein content. The 95:5 and 50:50 blends approximate the low‐ and high‐protein mixture range of early generation wheat populations, and thus the sorter has potential to aid breeders in purifying samples for developing high‐ or low‐protein wheat. Results indicate that sorting was partly driven by color and vitreousness differences between high‐ and low‐protein fractions. Development of a new background specific for high‐ or low‐protein and fabrication of better optical filters for protein might help improve the sorter performance.

Examination of spectral pretreatments for partial least-squares calibrations for chemical and physical properties of wheat.

Use of near-infrared (NIR) diffuse reflectance on ground wheat meal for prediction of protein content is a well-accepted practice. Although protein content has a strong bearing on the suitability of wheat (Triticum aestivum L.) for processed foods, wheat quality, as largely influenced by the configuration and conformation of the monomeric and polymeric endosperm storage proteins, is also of great importance to the food industry. The measurement of quality by NIR, however, has been much less successful. The present study examines the effects and trends of applying mathematical transformations (pretreatments) to NIR spectral data before partial least-squares (PLS) regression. Running mean smooths, Savitzky-Golay second derivatives, multiplicative scatter correction, and standard normal variate transformation, with and without detrending, were systematically applied to an extensive set of hard red winter wheat and hard white wheat grown over two seasons. The studied properties were protein content, sodium dodecyl sulfate (SDS) sedimentation volume, number of hours during grain fill at temperature <24 degrees C, and number of hours during grain fill at temperature >32 degrees C. The size of the convolution window used to perform a smooth or second derivative was also examined. The results indicate that for easily modeled properties such as protein content, the importance of pretreatment was lessened, whereas for the more difficult-to-model properties, such as SDS sedimentation volume, wide-window (>20 points) smooth or derivative convolutions were important in maximizing calibration performance. By averaging 30 PLS cross-validation trial statistics (standard error) for each property, we were able to ascertain the inherent modeling ability of each wheat property.

Phytase activity in extracts of flour and bran from wheat cultivars: enhanced extractability with β-glucanase and endo-xylanase

Phytase (EC 3.1.3.8) hydrolyzes phytic acid to myo-inositol and inorganic phosphate through intermediate myo-inositol phosphates. Microbial phytase has been employed to minimize the negative effects of phytic acid in cereal-based feeds, however, other sources such as wheat, would be natural alternatives. Investigations were therefore carried out to determine the levels of phytase activity in various cultivars and how the extraction of the enzyme may be enhanced using buffers fortified with glycanases. We screened 23 cultivars and the results showed that bran from hard white wheat cultivars had relatively lower levels of activity, ranging from about 1.5 to about 2.5 FTU/g bran, whereas hard red wheat cultivars had much higher levels, ranging from approximately 2 to 5.5 FTU/g bran. These levels were greatly enhanced, up to 5-fold, when extraction buffer contained a commercial preparation consisting of β-glucanase (EC 3.2.1.6) and endo-xylanase (EC 3.2.1.8) (Natugrain) (opt 1%) from BASF. The effect of glycanases was concentration and cultivar dependent, but not significantly influenced by temperature exposure of mixtures of samples with extraction buffers prior to extraction. Relative increases were more substantial in hard white than in hard red wheat cultivars. The additional value of supplementing grain-based diets with glycanases for monogastric animals is discussed.

Environmental Effects on Developing Wheat as Sensed by Near‐Infrared Reflectance of Mature Grains

ABSTRACTFor 30 years, near‐infrared (NIR) spectroscopy has routinely been applied to the cereal grains for the purpose of rapidly measuring concentrations of constituents such as protein and moisture. The research described herein examined the ability of NIR reflectance spectroscopy on harvested wheat to determine weather‐related, quality‐determining properties that occurred during plant development. Twenty commercial cultivars or advanced breeding lines of hard red winter and hard white wheat (Triticum aestivum L.) were grown in 10 geographical locations under prevailing natural conditions of the U.S. Great Plains. Diffuse reflectance spectra (1,100–2,498 nm) of ground wheat from these samples were modeled by partial least squares one (PLS1) and multiple linear regression algorithms for the following properties: SDS sedimentation volume, amount of time during grain fill in which the temperature or relative humidity exceeded or was less than a threshold level (i.e., &gt;30, &gt;32, &gt;35, &lt;24°C; &gt;80%, &lt;40% rh). Rainfall values associated with four pre‐ and post‐planting stages also were examined heuristically by PLS2 analysis. Partial correlation analysis was used to statistically remove the contribution of protein content from the quantitative NIR models. PLS1 models of 9–11 factors on scatter‐corrected and (second order) derivatized spectra produced models whose dimensionless error (RPD, ratio of standard deviation of the property in a test set to the model standard error for that property) ranged from 2.0 to 3.3. Multiple linear regression models, involving the sum of four second‐derivative terms with coefficients, produced models of slightly higher error compared with PLS models. For both modeling approaches, partial correlation analysis demonstrated that model success extends beyond an intercorrelation between property and protein content, a constituent that is well‐modeled by NIR spectroscopy. With refinement, these types of NIR models may have the potential to provide grain handlers, millers, and bakers a tool for identifying the cultural environment under which the purchased grain was produced.

End‐Use Quality of Hard Red and Hard White Spring Wheat Contaminated with Grain of Contrasting Classes

ABSTRACTShort growing seasons and lack of water limit the number of crops that can be productively grown in the Northern Great Plains, but wheat is uniquely adapted to the region. Growers interested in diversification of their operations are growing more than one class of wheat to target different markets. This has led to the challenge of maintaining class purity, in that contamination with alternate classes results in lower prices to the farmer. The primary rationale is that mixtures may have poor end‐use quality. In these experiments, we tested hard red spring wheat and hard white spring wheat contaminated with different levels of soft white spring wheat, durum wheat, hull‐less barley, and the hard wheat of the alternate kernel color for milling and baking quality. Our results showed that contamination of hard red and hard white spring wheat with soft white wheat and hull‐less barley often influenced end‐use quality in that flour yield was negatively affected at relatively low levels. Loaf volume was normally only affected at higher levels. Durum wheat contamination caused fewer quality problems at generally higher levels of contamination. Contamination of hard red or hard white wheat by hard wheat of the alternate color class rarely affected quality, and effects were both positive and negative, depending on quality attributes of the pure samples. Growers wishing to diversify by growing both hard red and hard white wheat would benefit if buyers and end users were willing to accept higher levels of contamination for alternate classes that are unlikely to cause problems in eventual end use.

W98616, a white-seeded spring wheat with increased preharvest sprouting

White-seeded spring wheat germplasm line W98616 was selected for improved levels of preharvest sprouting resistance. W98616 has levels of seed dormancy comparable to Columbus, a red-seeded sprouting-resistant cultivar. W98616 has similar test weight, kernel weight, maturity, plant height, grain protein, and kernel hardness, but is lower yielding and 2 d later heading relative to BW264, a hard white wheat cultivar. Key words: Triticum aestivum L., germplasm, white spring wheat, preharvest sprouting resistance

Quantitative Trait Loci Associated with Milling and Baking Quality in a Soft × Hard Wheat Cross

Interclass hybridization between soft and hard wheat (Triticum aestivum L.) results in new genetic combinations of potential value. We investigated whether interclass hybridization could improve end‐use quality of both classes. Our objectives were to analyze quality traits in a population of recombinant inbred lines (RILs) derived from a cross between the good quality soft white wheat NY6432‐18 (NY18), and good quality hard white wheat Clark's Cream (CC), identify quantitative trait loci (QTLs) for those traits, and use linkage analysis to determine which parent was contributing favorable alleles at specific QTLs for a given trait. The population was assessed for milling, protein and dough mixing, hydration, cookie and loaf traits. Traits were measured in two to six environments grown over three seasons in Ithaca, NY. The molecular map for the population contains 370 molecular markers including restiction fragment length polymorphisms (RFLPs), microsatellites, and markers derived from known function genes in wheat. Linkage groups have been located to all the wheat chromosomes except for 7D. Pinb derived from the puroindoline b gene on chromosome 5DS was the major QTL for milling, hydration, and cookie baking traits. The major QTL for mixograph peak time was at the Glu‐Dy1 marker, derived from Glu‐D1‐2 gene on chromosome 1DL. The Glu‐Ax1 and Glu‐By1 markers were QTLs for mixograph peak height and tolerance, respectively. QTLs for flour protein quantity were detected on chromosome 2B. With the exception of the hydration traits, multiple regression models included alleles from both parents. Interclass hybridization may be an underexploited wheat breeding strategy for improvement of agronomic and quality traits in wheat.

Comparison of Asian Noodles from Some Hard White and Hard Red Wheat Flours

ABSTRACTAsian noodles were prepared by an objective laboratory method that included adding optimum water to the dry ingredients, mixing the ingredients to homogeneous salt distribution, and sheeting of the dough under low shear stress. The lightness (L*) values of alkaline‐ and salt‐noodle doughs made from 65% extraction hard white wheat flours (except KS96HW115 flour at ≈70% extraction) were higher than those from 60% extraction hard red wheat flours (except Karl 92 flour at ≈70% extraction). A hard white spring wheat, ID377s, and a Kansas line of hard white winter wheat, KS96HW115, to be released in 2000, gave the highest L* values for dough sheets stored for 2 and 24 hr at 25°C. Cooking losses were 5–9 percentage points higher for alkaline noodles than salt noodles, but the cooking yields of the two types of Asian noodles were almost the same. Cooked alkaline noodles made from a high‐swelling flour (SP93≈21 g/g) gave higher tensile strength than those made from several low‐swelling flours (SP93 ≈15 g/g) with the same protein contents (≈12.5%). However, the cooked salt noodles gave the same tensile strength.

High-molecular-weight glutenin subunit composition of Pakistani hard white spring wheats grown at three locations for 2 years and its relationship with end-use quality characteristics

Eleven Pakistani hard white spring wheat cultivars, along with one durum wheat and two hard white American-grown wheat cultivars, were evaluated for their high-molecular-weight (HMW) glutenin subunit composition via sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE). The relationships among different quality characteristics and between these characteristics and HMW glutenin subunits were computed. Three to six HMW glutenin subunits were observed in Pakistani bread wheat cultivars. The presence of HMW glutenin subunits was not affected by growth locations or crop years. However, variations in intensities were observed. Correlations were noticed between certain HMW glutenin subunits and some quality attributes, such as protein, farinograph dough development time, farinograph water absorption, loaf volume and mixograph peak height. The presence of HMW glutenin subunit 20 in the older wheat cultivars C591 and C273, known for excellent chapati quality, indicated a possible relationship between this band and chapati quality. This observation will need to be confirmed by testing a larger number of wheat samples known to have characteristics for both good and poor chapati quality. © 2000 Society of Chemical Industry

Quantitative Trait Loci Associated with Kernel Traits in a Soft × Hard Wheat Cross

Kernel morphology and texture influence the value of wheat (Triticum aestivum L.). The objectives of this study were to determine associations between kernel traits and molecular markers and to identify quantitative trait loci (QTLs) affecting kernel traits in a soft × hard white wheat cross. Seventy eight F2:5‐derived recombinant inbred lines (RILs) from cross between the soft white wheat NY6432‐18 (NY18) and the hard white wheat ‘Clark's Cream’ (CC) were developed by single seed descent. Kernel texture was measured by near infrared reflectance (NIR) on RIL grain samples from six environments. Digital image analysis (DIA) was used to measure kernel length, width, area, perimeter on grain samples from four environments. Test weight and thousand kernel weight (TKW) were also determined. Shape factor and density factor were calculated. The map for this population consisted of 313 molecular markers in 47 linkage groups located on all wheat homoeologous chromosome groups. Linkage groups that mapped to wheat homoeologous group 2 chromosomes were highly skewed towards NY18 alleles. Genotype effects and genotype × environment interactions were highly significant for most traits. QTLs for kernel width and kernel length also influenced kernel area and TKW, but did not influence each other. The pinB marker at the puroindoline B locus on chromosome 5DS explained over 60% of the phenotypic variation for kernel texture. QTLs for kernel traits were located on chromosomes IA, 2B, 2D, 3B, 7A, and 7B.

Preharvest Sprouting of Hard Red and Hard White Wheats in Kansas (1999)

Wheat in Kansas usually ripens under warm, dry conditions that favor development of excellent grain for bread making. However, the ripe grain can sprout in the spike when moist conditions delay harvest and promote germination. Persistent rain, heavy dew, and high humidity that stimulate preharvest sprouting are most common in eastern Kansas and least common in western Kansas. In central Kansas, moist conditions caused sprouting in 1979, 1989, 1993, and 1999. Moisture swells wheat kernels and activates enzymes that break down proteins, starches, lipids, and other constituents in the endosperm. Flour milled from the endosperm of sprouted wheat produces bread that is porous and sticky and has a low loaf volume. The grain has little value to the milling and baking industries and is discounted heavily. More than 4% damaged kernels-including sprouted kernels-causes grain to be rated Grade 3 or lower and unacceptable for bread making. Grain that is slightly sprouted might be blended with sound grain for making flour, but grain that is severely sprouted usually is used for livestock feed. Ripe grain is dormant and must pass through a period of afterripening before it can germinate, even under favorable conditions. The length of the afterripening period is highly variable, ranging from a few days in some varieties to a month or longer in others. Differences in the length of the afterripening period, or dormancy, greatly affect susceptibility of wheat varieties to preharvest sprouting. Most hard red win-

Characteristics of Noodle Flours from Japan

ABSTRACTThe compositions and physical properties of Japanese salt and alkaline noodle flours were contrasted and compared to those of flours from U.S. hard white and soft white wheats (HWW and SWW) and from Australian SWW wheats often segregated for salt noodles. The alkaline noodle flours averaged 11.5% protein, which was 3% higher than the salt noodle flours, and they had lower ash content (0.35 vs. 0.41%). Granulation of the salt noodle flours showed the same proportion of small particles (&lt;38 μm) as in soft wheat flours but different levels of intermediate and large particles. The level of small particles was ≈10% greater in salt noodle flours than in the alkaline noodle flours. The alkaline noodle flours had ≈8% more fine particles and 2.5% more damaged starch than the HWW flours, which is consistent with fine grinding of hard wheat flour in the noodle flour. Starch damage also was higher in the salt noodle flours (5.3%) than in the SWW flours. The salt noodle flours had a higher sodium dodecyl sulfate (SDS) sedimentation volume and a higher gluten index than the SWW flours from the United States. The SDS volume and gluten index were lower for the alkaline noodle flours than for the HWW flours, showing the preference for a mellow gluten of low‐intermediate strength in alkaline noodle flour. Mixograph data also supported the conclusions of mellow gluten in alkaline noodle flour. The swelling powers (1.7% at 92.5°C) for Australian SWW, salt noodle, U.S. HWW, U.S. SWW, and alkaline noodle flours, were 19.4, 18.1, 17.0, 16.1, and 15.8 g/g, respectively, showing the preferences for high‐ and low‐swelling starch, respectively, in the salt noodle and the alkaline noodle flour. A similar order of flour swelling was indicated by peak viscosity of flours heated at 12% solids in starch paste viscosity analysis. Water holding capacity of flour was correlated highly (r = 0.95, P &lt; 0.01) with swelling power, both measured at 1.7% flour solids at 92.5°C.

Developing noodles from US wheat varieties for the Far East market: sensory perspective

This study was undertaken to better understand the noodle texture profile of fresh and wet noodle styles in Taiwan, Thailand and Malaysia in order to meet their different quality requirements. Totals of 16 patent flour samples for Taiwan, and 18 straight grade flour samples each for Thailand and Malaysia, were milled from US hard white wheat varieties. Noodles were made with an Ohtake noodle machine using conditions specific for each of the noodle styles. A lexicon of 17 texture descriptors was utilized for texture evaluation by a descriptive panel. Noodle quality was evaluated by each country's noodle representatives. The Taiwanese raw noodles were characterized as the smoothest, springiest, and were highest in integrity of noodles. Thai bamee noodles were the hardest, most dense, most cohesive noodles and were also more in starch between teeth and toothpull. Malaysian hokkien noodles were the softest, least dense, cohesive and least sticky. The high and low texture quality samples determined by each country's noodle representatives were characterized by the descriptive panel and the important sensory attributes which defined texture quality of each country's style noodle were identified.

Relationship between Baking and Noodle Quality in Hard White Spring Wheat

There is growing interest in the use of hard white wheat (Triticum aestivum L.) for both the production of oriental noodles and making bread. It would be desirable if new hard white wheat cultivars produced flour suitable for both purposes. Our objective was to address the feasibility of developing such dual purpose white wheats. We tested several hard white spring wheat lines grown in three locations in Montana for quality characteristics associated with both end‐use products. The hard white spring wheat lines had bread‐making quality similar to that observed for high quality hard red spring wheat check cultivars. The hard white spring wheat flours differed from Australian Standard White by producing significantly harder noodles that were not as bright, particularly after 24 h of noodle storage. Significant variation existed among the hard white lines for noodle color, suggesting selection during breeding might improve color characteristics. However, superior noodle color was correlated with low protein in two environments and with poor loaf volume in one environment. The challenge facing breeders in the development of dual purpose hard white spring wheats will be to improve noodle characteristics while maintaining good bread‐making qualities.

Allelic variation at the storage protein loci of 55 US‐grown white wheats

AbstractFifty soft white and hard white wheat cultivars (Triticum aestivum L.), and five club wheat cultivars (T. compactum L.) were partially characterized in terms of their storage protein compositions, i.e. gliadins, and high molecular weight and low molecular weight glutenin subunits (HMW‐GS and LMW‐GS, respectively). At the Glu‐1 loci, HMW‐GS composition 1,7 + 9,2+ 12 was found to be predominant, being expressed in 11 cultivars out of 55. The most common alleles at the loci coding for gliadins and LMW‐GS were found to be Gli‐A1/Glu‐A3a (43.6%), Gli‐B1/Glu‐B3b (36.4%), Gli‐D1a/Glu‐D3a (38.1%) and Gli‐Dli/Glu‐D3a (21.8%). Two‐dimensional fractionation (acid‐poly‐acrylamide gel electrophoresis (A‐PAGE) × sodium dodecyl sulphate‐polyacrylamide gel electrophoresis (SDS‐PAGE)) of reduced and alkylated glutenins revealed that the number and the relative mobility of LMW‐GS polypeptides were different from those reported for the corresponding Glu‐3 alleles of hard‐bread wheat cultivars. This result could account for the different technological properties of soft white wheats compared with hard‐bread wheat cultivars, owing to the major impact of LMW‐GS on dough quality.

Variation in Polyphenol Oxidase Activity and Quality Characteristics Among Hard White Wheat and Hard Red Winter Wheat Samples

ABSTRACTPolyphenol oxidase (PPO) has been related to an undesirable brown discoloration of wheat‐based end products. Consumer acceptance and product quality are generally decreased by the darkening phenomena. Two sets of wheat samples (Triticum aestivum L.) were investigated for variation in grain and flour PPO levels. Samples included 40 advanced experimental hard white winter wheat lines grown at two Kansas locations and 10 hard red winter wheat genotypes grown at three Nebraska locations. The variability in grain and flour PPO activities was influenced by growing location and population for the hard white wheat samples. There also was a significant influence of population by growing location interactions on PPO activity in both grain and flour. Genotype and growing location both contributed to variability in flour PPO activity among the hard red wheat samples. The variation in flour PPO activities among growing locations appeared larger than variation produced by genotypes tested for the hard red wheat samples. Quality parameters, such as wheat physical properties, flour protein and ash contents, grain color, and milling yield significantly correlated with grain and flour PPO activities. Among red wheat samples, flour PPO activity was related to 100 kernel weight, first reduction flour yield, and flour ash content. Grain PPO activity was related to variation in grain color observed among hard white samples. The relationship of quality characteristics with grain and flour PPO activities varied among white and red wheat samples.

Sensory evaluation of a hard white compared to a hard red winter wheat

AbstractTraditionally bread wheats grown in the USA have been hard red genotypes. Introduction of hard white genotypes provides an opportunity for the comparison of the products and evaluation of consumer acceptance. MT 7811, a hard white wheat, and ‘Norwin’, a hard red winter wheat, were grown in adjacent plots in each of two years. Grain from each was divided, with half milled into whole wheat flour (wholemeal) and the other half milled into white flour (milled flour). Breads made from wholemeal and milled flour from each wheat genotype were tested by panelists for differences. Color differences were easily detected. The Wilcoxon‐Mann Whitney rank sums test was used to evaluate signal detection data. Both crust and crumb differences between the two wheats could be detected by some panelists. Differences could be detected between the two wheat types in either wholemeal or milled flour bread. Crust differences were often greater than crumb differences. Trained panelists commented on some bitterness in red wheat products and a sweetness in white wheat products.

Evaluation of Flour Particle Size Distribution by Laser Diffraction, Sieve Analysis and Near-infrared Reflectance Spectroscopy

Laser diffraction and sieve analysis were used to measure flour particle size distributions as per cent volume and per cent weight, respectively, among different wheat types and milling methods. Near-infrared (NIR) reflectance spectroscopy was used to predict the per cent volume of flour particles within selected size ranges based on laser diffraction reference values. According to laser diffraction analysis, 89-98% of the flour particle were distributed within the size ranges 10-41 μm and 41-300 μm, and 2-11% of the particles were distributed within the size range < 10 μm. Flour particle size distributions were different (P<0·05) among the wheat types tested, except that hard red winter and hard white wheats were not different in flour particle size < 10 μm, and hard red spring and hard white wheats were not different in flour particle size within 10-41 μm and 41-300 μm. The milling method affected particle size distributions of hard wheat flours but not those of soft wheat flours. A high correlation (r = 0·95) occurred between per cent volume and per cent weight of hard wheat flour particles < 45 μm, but the correlation decreased (r = 0·77) when soft wheat flours were included in the comparison. Near-infrared calibration equations were developed by partial least-squares regression for predicting the per cent volume of flour particles. The per cent volume of flour particles within the size ranges < 10 μm, 10-41 μm and 41-300 μm were predicted by NIR within ± 2 standard errors for ≥ 96% of the flours tested.