|FUERST, E - Washington State University|
Submitted to: Cereal Chemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/21/2014
Publication Date: 1/21/2015
Publication URL: http://handle.nal.usda.gov/10113/60194
Citation: Kiszonas, A., Fuerst, E.P., Morris, C.F. 2015. Modeling end-use quality in U. S. soft wheat germplasm. Cereal Chemistry. 92:57-64.
Interpretive Summary: Wheat quality is the product of grain, milling, and baking characteristics. These characteristics help define the best end-product use for specific wheat varieties. Many different parameters within these three categories can be used to evaluate end-use quality. Determining the importance of each parameter on the overall end-use quality as defined by the consumer product can prove challenging given the genetic diversity of wheat and the highly variable environments in which wheat is grown across the United States. It is important to identify which quality measures provide the most accurate assessment of end-use quality in order to optimize commercial use and consumer acceptance. The first two objectives of this study were to model both cookie diameter and Lactic acid SRC in order to better understand the associations of grain, milling, and baking parameters with the overall end-use quality. The third objective was to examine exceptionally high and low performing varieties to see if their arabinoxylan content was associated with differences in grain, milling, and baking. The results of this research demonstrates the need to look at a select few parameters when assessing soft wheat quality, prior to baking.
Technical Abstract: 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 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, milling score, flour protein, flour SDS sedimentation volume, flour swelling volume, peak paste viscosity, solvent retention capacity (SRC) parameters, total and water-extractable AX (TAX and WEAX), and cookie diameter. The objectives were to model cookie diameter and Lactic acid SRC as well as compare exceptionally performing varieties for each quality parameter. Cookie diameter and Lactic acid SRC were modeled using multiple regression analyses, and including all of the aforementioned quality parameters. Cookie diameter was positively associated with peak paste viscosity, and negatively associated, or modeled, by kernel hardness, flour protein, 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, while being 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, Carbonate SRC, Sucrose SRC, Water SRC, TAX content, and cookie diameter. The models described allow a more focused approach toward predicting soft wheat quality.