Document Type
Thesis - Open Access
Award Date
2017
Degree Name
Master of Science (MS)
Department / School
Agronomy, Horticulture, and Plant Science
First Advisor
Karl Glover
Keywords
Wheat quality, Loaf volume, Gluten index
Abstract
Wheat (Triticum aestivum L.) is the most widely cultivated crop in the world and contributes about 20% of the total dietary calories and proteins globally. Unique properties of doughs formed from wheat flour make it feasible to produce a range of food, including bread. Loaf volume is the most perceptible indicator for breadmaking quality. Selection in the early generations for loaf volume is difficult due to the requirement of the large volume of grains and due to the costly, time-consuming, and labor-intensive evaluation process. Identification of simple and reliable predictive tests for loaf volume is highly desirable. This study mainly aimed to predict loaf volume by the Gluten Index method using the Glutomatic system. The advantages of Gluten Index method for measuring the quality of wheat flour is due to the short testing time (approx. 10 min) and the small amount of sample required (10 g). The quality test was performed on a sample set of 48 spring wheat genotypes grown each year at three locations in South Dakota from 2012 to 2016. Among the 48 genotypes, 15 were consistently grown in all 15 environments. Relative contributions of genotype and environment to variation in loaf volume and other ten quality parameters were determined. Flour protein content, kernel protein content, gluten index, gluten remained, and gluten remained × gluten index (GR×GI) were found to be most significantly correlated with loaf volume. Environment and measurement error contributed greatly to variation in loaf volume. Loaf volume was greatly affected by year. Loaf volume variation among genotypes was smaller compared with variation among different environment. Loaf volume had a low broad-sense heritability, ranging from 0.21 to 0.42 when data from all 48 genotypes grown at three locations each year were used for analysis. The broad-sense heritability reduced to 0.19 when data from the 15 consistently grown genotypes in all 15 environments were used for analysis. Regression analysis based on data from genotype mean from 3 locations of the 48 genotypes showed that a model with two variables, GR × GI and flour protein content, could explain over 30% of the phenotypic variation in loaf volume in three consecutive years, with R2 value being 0.39 in 2014, 0.33 in 2015, and 0.47 in 2016, respectively. When only one variable is used in the model, the model with GR×GI explained about 30-33% of the phenotypic variation in loaf volume from 2014 to 2016. The model with flour protein content as variable explained about 14-39% of phenotypic variation in loaf volume from 2014 to 2016. The model with GR × GI and flour protein content as variables explained 32-53% of the phenotypic variation in loaf volume from 2014 to 2016 when data from the 15 consistently grown genotypes were used for analysis. Results from this study suggest that if the Glutomatic system was used for selection of experimental breeding lines, selecting those with high GR × GI and flour protein content would contribute to increased loaf volume potential.
Library of Congress Subject Headings
Wheat -- Quality.
Gluten.
Dough.
Bread.
Description
Includes bibliographical references (pages 90-97)
Format
application/pdf
Number of Pages
141
Publisher
South Dakota State University
Recommended Citation
Lu, Yaming, "Using Gluten Index to Improve Spring Wheat Loaf Volume Prediction" (2017). Electronic Theses and Dissertations. 2173.
https://openprairie.sdstate.edu/etd/2173