Influence of Soft Wheat Characteristics on Quality of Batter-based Products Public Deposited


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  • Wheat is a globally traded staple crop. Wheat is important in human diets because of its agronomic adaptability, physical characteristics, functionality for the production of leavened products and nutritional value. Two significant characteristics make wheat an important staple food-crop. First, the proteins present in wheat endosperm have attributes that enable gas retention after the proteins are hydrated and mechanically worked during dough production. Second, a wider variety of products can be made out of wheat compared to other cereals. Wheat quality is defined in terms of suitability for specific end-uses. This is important for breeders, farmers, flour millers, and food producers and consumers. In the U.S. Pacific Northwest (PNW) climatic conditions favor production of soft wheat. Three soft wheat types are planted in the PNW, soft white winter (SWW), soft white spring (SWS), and club (CLUB). Batter-based products are important applications for soft wheats and include a wide range of products such as pancakes and waffles, cakes, and coatings. Pancakes are produced from fluid batters using a single step mixing process and contain sugar concentrations < 30% in their formulations. Cakes are complex food systems where their classification is based on mixing process to produce the batters and the sugar-flour ratio concentrations in their formulations. This dissertation is focused on the functionality, analysis, and selection of soft wheat quality traits that affect end-product performance and also developing a methodology to rapidly predict cake quality. The first study (Chapter 3) was concerned with the functionality of SWW wheats in pancake making. The aim of this study was to observe the differences in genotype and protein concentration on batter flow and pancake making performance of a collection of SWW wheats. Two formulations were used in the study: one based on Finnie et al (2006) called "old" and another based on the AACC-I Approved Method 10-80.01 called "new". The "new" lean formulation had an improved ability to distinguish the performance of different flours compared with the “old” as a result of wider range of pancake diameters. This study showed that pancake making performance would not be optimized by conventional superior high-quality soft wheat flours with soft kernel texture, high break flour yield, and low water-, carbonate-, and sucrose SRCs. From our results it appears that for unchlorinated flours, at least for thicker pancakes, the most appropriate flour would have higher water and sucrose SRCs and be grown under management conditions conductive to higher protein. The second study (Chapter 4) was a meta-analysis of data collected by the USDA Western Wheat Quality Laboratory (Pullman, WA). This study was done to advance understanding soft wheat quality traits that differentially affect sugar-snap cookie diameter (CODI) and Japanese sponge cake (SC) volume (CAVOL). Principal component analysis (PCA) and partial least square (PLS) regression models were used to obtain useful actionable information from the data. The overall data showed that break flour yield (BKFY) was the single most important trait positively associated with both CAVOL and CODI. SWW wheats showed CVs > 10% for kernel hardness (SKHRD), grain and flour protein concentrations, ash, sucrose-, and lactic acid SRCs. These observations suggested that hardness, protein, ash, and the two SRCs were more sensitive to G&E effects than were the end-product traits that had CVs < 10%. The third study (Chapter 5) was built on the second study by adding two additional quality tests, oxidative gelation capacity (PeakOXI) and median particle size, to the potential prediction of CODI and CAVOL. Similar to the second study, BKFY was the single most important trait positively associated with both CAVOL and CODI. Virtual selection of SWWs based on either BKFY or SKHRD alone showed (in both the second and third studies) that using these enabled a gain of 134 mL for CAVOL and 0.6 cm for CODI using SKHRD and 122 mL for CAVOL and 0.58 cm for CODI using BKFY (Chapter 5). PeakOXI was significantly correlated with CODI but not with CAVOL. This contrasted with our hypothesis that PeakOXI would affect both products similarly. Notably 13 SWW samples had PeakOXI values higher than 800 cP. PeakOXI values this high have never been observed in soft wheats prior to this study. This is a valuable genetic resource for further studies that may lead to ways to better exploit oxidative gelation. The fourth study (Chapter 6) expanded the concepts in previous studies and included the use of a test to measure cake-batter viscosity in an attempt to predict cake quality. This study investigated the relationships between wheat quality traits, cake batters, and cake making quality in three cake types: SC, layer cake (LC), and pound cake (PoC). This study differed from the studies in Chapters 4 and 5 and was similar to Chapter 3 as the samples were fewer but specifically chosen to span the entire range of typical SWW quality. In this study we also developed a viscosity-based method to predict SC and LC quality that takes only eight minutes. This could be useful for screening or selection for cake quality in soft wheat breeding programs. In SC, there were no significant differences in cake quality traits between varieties. However, SC volume had a strong negative association with PeakOXI. For LC, the variety Tubbs, with harder kernel and higher absorption characteristics, had the largest LC volume. In contrast to SC, LC volume was significantly and positively associated with PeakOXI. In PoC, Kaseburg, with the highest protein content, had the largest cake volume. PoC was significantly and positively associated with flour protein concentration suggesting that flour proteins were important for larger volumes and confirming other observations in the literature. In contrast to LC and SC, PoC was not significantly associated with PeakOXI. The overall impact of the studies reported is: - For pancakes, the most important soft wheat trait is flour protein concentration. Water-, and sucrose SRCs were potentially useful parameters for predicting pancake quality. - For SC and sugar-snap cookies, break flour yield was the most important single trait in predicting higher SC volumes and larger cookie diameters. Therefore, selection in soft wheat breeding should be focused on kernel hardness and break flour yields as primary factors.
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