The major components of wheat flour are keys to its functionality in processing and product quality. The major components, other than the lipids, are polymers: starch, protein, and non-starchy polysaccharides (NSP). In wheat NSP are primarily arabinoxylans (AX). These components are compartmentalized in the grain but are forced into close contact after the disruption caused by the milling process. These components further interact once water is added to the flour to create doughs and batters. It is these interactions and the water holding capacities of these polymeric components that are the unifying thread for most of this dissertation, other than the inclusion of nutritional traits in chapters 6 and 7. This dissertation consists of three independent studies, the last of which had two parts. Study one was "Effect of carbonate on co-extraction of arabinoxylans (AX) with glutenin macropolymer (GMP)". The aim of this study was to investigate if the level of AX in GMP increased under alkaline extraction conditions compared to extractions done in water. The amount of wet GMP obtained from alkaline extraction was greater than that from water extraction. Hard wheats had overall higher GMP wet weights than soft wheats. The level of AX in GMP extracted under alkaline conditions was greater than that in GMP extracted with water and the amount of increase was generally higher in soft wheats. Study two was "Optimization of water addition to noodle doughs". The aim of this study was to determine if a lubricated squeezing flow (LSF) technique could be useful in determination of optimum water addition to noodle doughs. Comparing the LSF method with alternative methods (Mixograph and sieving test), optimum water additions predicted by LSF for both salted and alkaline soft-wheat derived noodle doughs were equivalent or slightly higher than those predicted by the Mixograph and sieving test. For both salted and alkaline hard-wheat derived noodle doughs, optimum water additions predicted by the LSF method were substantial higher than those predicted by the Mixograph but equivalent or slightly higher than those predicted by the sieving test. Relaxation time was the most useful parameter in determining optimum water addition for the soft-wheat noodle doughs. The LSF method in its current form was found to be not adequate for all noodle types. Additional work with LSF parameters altered to improve sensitivity and with more of samples should be performed. Study three was "Determination of wheat quality and quantitative trait locus analysis". Part 1 was to measure a comprehensive set of quality phenotypes (including nutritional parameters) on a wheat population derived from the cross Tubbs [soft] x NSA98-0995 [hard]; (T x N). Part 2 was to identify if there were quantitative trait loci (QTL) associated with the traits determined in part 1. Considerable and transgressive segregation was observed for many of the studied traits. The transgressive segregation could useful, in that lines with superior soft-wheat quality can be identified that could be introduced quickly into the wheat breeding program from this elite x elite cross. Hardness index was significantly correlated with several important traits related to the solvent absorption capacity of the flour. Composite interval mapping detected a total of significant 28 QTLs on 10 wheat chromosomes for 15 end-use quality and nutrition traits in 2 harvest years. QTLs for total antioxidant activity (TAA) and total phenolic content (TPC) were identified for the first time. QTLs for TAA were on chromosomes 3B and 5BS, while the QTL for TPC was on chromosome 7AC. Hybridization between Tubbs and NSA surprisingly produced superior soft-wheat quality with potentially higher in nutritional values. The QTLs identified in this study could be useful in marker-assisted selection for future pre-selection of progeny from Tubbs or NSA. / Graduation date: 2012

The Asian noodle market is responsible for the increased volume of wheat imported to that region in recent years. Soft white wheat produced in the Pacific Northwest is mainly used for baked products, whereas an Australian wheat, Australian Standard White, is preferred for noodles. To enter this market soft white-wheat cultivars with properties similar to or better than Australian Standard Whitemust be developed. This process is difficult as little is known of the factors that influence noodle quality. The use of grain-protein percentage, kernel hardness, and six viscosity parameters measured by the Rapid Visco Analyzer for predicting Japanese udonnoodle quality was evaluated. The Rapid Visco Analyzer was developed to indicate quickly and reliably the starch properties of a small wheat sample. Experimental material included advanced winter-wheat selections from the Oregon State University wheat-breeding program and Stephens, a widely grown winter-wheat cultivar. Two commercial spring cultivars, Owens and Klasic, thought to have good noodle quality were used as checks as was straight grade flour milled from Australian Standard White wheat. The material was grown at two locations (Rugg and Chambers) which represent diverse environments and management systems. Protein content, kernel hardness, and six viscosity parameters (Peakl, Low, Peak2, Peakl-Low, Peak2-Low, Peakl-Peak2) were measured. A sensoryevaluation panel evaluated the end product for surface appeal, texture, and taste. Within each location differences were found for all traits except protein content at the Rugg site and surface appeal at the Chamber location. Between the two experimental sites the only traits for which no differences were detected were kernel hardness and surface appeal. Significant entry by location interactions were observed for kernel hardness, Peakl- Peak2, and the three sensory-evaluation traits. Kernel hardness and grain-protein percentage were not associated, however both were negatively associated with the viscosity parameters. Associations of grain-protein, kernel hardness, and the viscosity parameters with the sensory evaluation traits were not statistically determined. A softer kernel texture appeared most useful for predicting Japanese udon-noodle quality as determined by sensory evaluation. Grain-protein percentage was not a good indicator by itself, but each cultivar may have a protein-content range within which noodle quality is optimized. This range may be influenced by the kernel texture. The viscosity parameters did not appear useful for predicting noodle quality as determined by the sensory evaluation panel. A more sensitive sensory evaluation method may be required to detect small however important differences and different viscosity parameters should be investigated. Based on the sensory-evaluation data several experimental entries appeared promising in having the desired quality profile for Japanese udon-noodles. / Graduation date: 1994

Typescript. / Digitized by Kansas Correctional Industries

The particle size distribution produced from first break roller milling of wheat determines the flows through the rest of the mill and hence the quality of the final flour, and is affected by debranning and by the operation of the roller mill. The Double Normalised Kumaraswamy Breakage function (DNKBF) gives a quantitative basis to describe breakage during first break milling of wheat and to interpret effects. Previous work developed and extended the breakage equation in order to understand and predict wheat breakage based on distributions of the grain characteristics and the operating parameters of the mill. However, broken particles vary in composition as well as size; therefore the primary objective of the current work was to extend the DNKBF during first break milling to include particle composition, using fingerprints of pericarp, aleurone, endosperm and germ. Meanwhile, debranning is a technology that has enhanced flour milling in recent years, leading to improvements in quality that are not well understood but that start with the effect on milling. A second objective of the current work was therefore to apply the DNKBF to describe and interpret the effects of debranning on wheat breakage and, in so doing, to clarify the physical significance of the DNKBF parameters. Samples of Mallacca (hard wheat) and Consort (soft wheat) were debranned for nine different times, at three roll gaps and under S-S and D-D dispositions. The DNKBF successfully described the normalised particle size distribution at different debranning times. The DNKBF describes wheat breakage in terms of Type 1 and Type 2 breakage, where Type 1 describes a relatively narrow distribution of mid-sized particles, whilst Type 2 describes a wide size range of predominantly small particles extending to very large particles. The proportion of Type 1 breakage increased at longer debranning times, while Type 2 breakage decreased, for both wheats under both dispositions. S-S milling tended to produce more Type 1 breakage than D-D. A mechanism of wheat breakage is proposed to explain the co-production of very large and small particles via Type 2 breakage, and hence the effect of debranning. The proposed mechanism is that small particles of endosperm arise from scraping of large flat particles of wheat bran under the differential action of the rolls; removal of the bran reduces the production of the large bran particles and thus reduces the opportunity for the scraping mechanism that produces the very small particles. The composition of broken particles can be characterised considering the four major wheat components, pericarp, aleurone, endosperm and germ. Kernels of Mallacca and Consort wheats were manually dissected to isolate these components. FTIR spectroscopy was able to distinguish the different components in milled fractions. However, attempts to quantify the relative contribution of each wheat component in milled fractions (by measuring specific peak heights and by Partial Least Squares, PLS) were compromised by technical limitations. An alternative approach aimed to fingerprint the components using sugar analysis by HPLC, with some success; however the technique was too complex and limited by the detection limit of HPLC, in particular for arabinose and xylose. Instead, the botanical distributions within eight milled fractions of Mallacca and Consort wheats milled under S-S and D-D dispositions were analyzed by PLS models developed by Barron (2011). The concentration functions were then found by applying the DNKBF to the particle size distributions and to the compositional distributions, the ratio of the DNKBFs giving the concentration function. The DNKBF was able to describe the data well for the four botanical components studied in both wheats: pericarp, aleurone, intermediate layer and starchy endosperm. The analysis clarified the nature of the particles produced on breakage, showing that for Mallacca wheat, the pericarp and aleurone layer compositions mostly varied with particle size in similar ways. Intermediate layer showed broadly similar results to those for pericarp and aleurone in the Mallacca wheat despite being the least accurate component predicted. However, for Consort wheat, the intermediate layer behaved differently from pericarp and aleurone, suggesting a different breakage mechanism, perhaps associated with how the wheat hardness affects breakage of the bran and the production of large flat bran particles. Creation of pericarp/intermediate layer/aleurone dust during milling was notable, in particular for Mallacca wheat. The relative uniformity of the Mallacca compositions in relation to pericarp, intermediate layer and aleurone, which varied in consistent ways with particle size, was also notable. By contrast, for Consort wheat, the relative proportions of these three components appear to vary substantially in particles of different size, pointing to very different breakage origins. It seems that in the hard wheat, the breakage patterns are dominated by the endosperm physical properties, while for the soft wheat, the behaviour of the large bran particles produced is dictated much more by the properties and structure of the bran layers than by the hardness of the endosperm. The approach presented is practical to describe, quantify and interpret the effects of breakage on component distributions, in order to understand the fate of kernel components during milling and hence the origins of flour quality.

Wheat improvement most often has been accompanied by a narrowing germplasm base, as newer cultivars have been derived from intercrosses between elite germplasm. However, there is a concern that narrow germplasm may restrict breeding improvement for important traits such as resistances to new biotic and abiotic stresses. In addition to germplasm base, the wheat kernel is a major component of wheat grain yield and an important factor for milling characteristics. Focusing on wheat kernel characteristics might be a key element to improve wheat genotypes for agronomic and quality traits. With the intention to broaden the wheat germplasm, and to explore the associations between kernel traits and agronomic as well as quality traits, a two-year study was initiated in 2009 to examine the influence of the kernel traits on the agronomic and quality attributes of a 160 Recombinant Inbred Lines (RIL) population developed from an adapted (ND 705) and a non-adapted genotype (PI 414566). The experiment was conducted at Prosper and Carrington, North Dakota, during 2009 and 2010. The RIL population had a better performance at Carrington than Prosper due to favorable climatic conditions at this location, in 2009 and 2010. The results in this study showed that kernel traits had a high correlation among them and they exhibited continuous variations suggesting a polygenic inheritance. Grain yield, kernel volume weight (KVW), and flour extraction were highly correlated with kernel width, length/width ratio, weight, and area. Eight RIL yielded better than the adapted parent ND 705 and two of the RIL along with three checks were significantly superior for gram yield compared with the other genotypes across all environments. Although the non-adapted parent has a facultative grown habit, several RIL required fewer days to flower compared to the adapted parent. Two RIL had better flour extraction compared to the other genotypes included in this study. These results indicated that kernel traits can play a significant role in improving agronomic and quality traits. Higher values for grain yield, KVW, and flour extraction were significantly associated with spheroid or round shape (short and plump), large, and heavy kernels. The high agronomic and quality attributes showed by some RIL demonstrated that the use of a non-adapted parent can broaden the genetic variability while increasing the genetic gain for certain traits. Also, breeders should pay attention to kernel size and shape during the parental selection for the development of populations with improved agronomic and quality traits.

Little is known about the effects of arabinoxylans (AX) on noodle quality. The aim of this study was to observe interrelationships between wheat flour AX, SRC tests, and noodle quality attributes, and to investigate the use of SRCs to predict cookie diameter. Cookie diameter is the most common index of overall soft wheat quality used in practice. Duplicate samples of 63 soft white wheat (Triticum aestivum) varieties and breeding lines grown at Corvallis in 2002 were selected to study the relationships between flour and noodle characteristics. Kernel hardness was positively correlated with starch damage, total AX and water-extractable AX (WEAX) content but negatively correlated with break flour yield. In this set of samples, despite significant correlations, the sodium carbonate and sucrose SRC tests were not considered to be reliable predictors of cookie diameter due to low numerical correlation coefficients. A modified extraction method for WEAX-SE and WUAX-SE was optimized and reduced in scale. During method development, WUAX 1-SE and WUAX 2-SE fractions that had been treated with protease and amylase respectively were observed using SEHPLC. The equivalent fractions had been discarded in other studies. In this study, AX was found to present in these fractions. A subset of 12 lines was used for further AX extraction. WUAX 2-SE had the highest molecular weight, followed by WUAX1-SE, and then WEAX-SE. The molecular weights of WEAX-SE ranged from approximately 411,305 and 447,282. However, molecular weight of WUAX 1-SE and WUAX 2-SE could not be specifically defined in this study. In addition, WEAX-SE contained a higher degree of substitution than WUAX 1-SE and WUAX 2-SE. For the whole sample set, flour protein content was negatively correlated with ti5A cooked noodle hardness, adhesiveness and chewiness but positively correlated with springiness. At the very low flour protein contents of this sample set, protein composition, which related to lactic acid SRC, became more important for noodle texture. Both starch damage and sodium carbonate SRC were positively correlated with cooked noodle hardness and chewiness at t₀ and t [subscript 15A] Total AX and WUAX were positively correlated with adhesiveness at to, which might result from gummy and sticky characteristics of AX. Using the subset of 12 lines, described above, increased xylose and arabinose contents reflected overall higher AX abundance, and were related to harder kernel texture, poor milling properties. They were also related to higher water, carbonate and sucrose SRCs, and smaller cookie diameter. A/X ratios of WEAX-SE and WUAX 1-SE were positively correlated with flour yield and break flour yield. The WUAX 2-SE fraction seemed to behave different from the WEAX-SE and WUAX 1-SE fractions. The relationships between A/G ratio, and milling characteristics and SRC were opposite to A/X ratios for all fractions. Decreased MW and increased abundance of WUAX in this sample set was related to poorer milling characteristics. There appeared to be no direct systematic relationships between AX and cooked noodle texture parameters in this study. However, AX content appeared to affect noodle texture indirectly, mediated through the effects ofAX on kernel hardness, milling properties, starch damage, reduced FSV, and hence harder noodle texture. Kernel hardness index, flour yield, break flour yield and tisw cooked noodle hardness were able to be predicted with some confidence using stepwise multiple regressions that used selected parameters from the WEAX, WUAX 1-SE and WUAX 2-SE fractions. / Graduation date: 2004