2007 Annual Report
Identify wheat of different oxidation requirements and determine effect of oxidative enzymes and transglutaminase upon quality characteristics. Begin biochemical analysis on the effect of enzymes on protein interactions. Characterize enzyme effects on protein interactions between glutenin and albumins. Characterize effect of HMW-GS contribution of wheat on enzyme mediated crosslinking.
Identify and begin to collect wheat samples to represent various growing environments. Begin isolating starch for analysis. Use LDS and our correction model to detect environmental differences in starch ratios. Isolate the starch fractions from different environments for chemical analysis. Compare starch size distributions and chemical analysis to different environments.
Characterize by RP-HPLC and SEC-HPLC, the protein fractions of the various near- isogenic lines that are produced in year 1 study by our collaborators. Relate the period of formation and amount of particular glutenin (polymeric) and gliadin (monomeric) proteins to the HMW-GS in the various near-isogenic lines. Correlate information obtained in this year 1 and 2 study with the data on bread or tortilla quality characteristics, provided by the HWWQL. Characterize the protein fractions of the various near-isogenic lines that were produced by our collaborators. Determine the sizes of the polymeric fractions and the MW distributions of the polymeric proteins. Relate polymer sizes and molecular weight distributions to quality characteristics, provided by the HWWQL. Determine if particular proteins are markers for quality traits.
Develop inexpensive lab-on-a-chip technology to extract and separate wheat gliadins in less than 1 min. Develop lab-on-a-chip system to extract, separate and identify wheat varieties in seconds. Develop a portable lab-on-a-chip system to extract, separate wheat proteins, and identify wheat varieties and/or the quality of wheat varieties or mixtures in seconds.
Relationship of bread quality to kernel, flour, and dough properties – A study was conducted to measure the relationship between bread quality and 49 hard red spring (HRS) or 48 hard red winter (HRW) grain, flour, and dough quality characteristics. The estimated bread quality attributes included loaf volume, bake mix time, bake water absorption, and crumb grain score. Models for predicting loaf volume, bake mix time, and water absorption from various quality parameters contained in the data set were successful, although crumb grain score was not well estimated. For loaf volume models, grain or flour protein content was the most important parameter included. Bake water absorption was best estimated when using mixograph water absorption, and flour or grain protein content. Bake water absorption models could generally be improved by including farinograph, mixograph, or alveograph measurements. Bake mix time was estimated best when using mixograph mix time, and models could be improved by including protein composition data. When the data set was divided into calibration and prediction sets, the loaf volume and bake mix time models still looked promising for screening samples. When including only variables that could be rapidly measured (protein content, test weight, single kernel moisture content, single kernel diameter, single kernel hardness, and bulk moisture content, and dark hard and vitreous kernels), only loaf volume could be predicted with accuracies adequate for screening samples.
4b. THE ENVIRONMENTAL IMPACT ON WHEAT STARCH SIZE DISTRIBUTION DURING GRAIN FILLING. The environmental impact on the starch size distribution during grain filling of hard red winter wheat has been collected and collated. These samples were all grown at the the Kansas State University Agronomy Study plots over a 6 year period of time. Statistical analysis of this data is nearing completion and correlations to some weather conditions have been noted. The larger starch size distributions (everything > 20 µm) are positively correlated to increased cumulative precipitation, while the 5-20 µm starch size distributions are negatively correlated to decreased cumulative precipitation and decreased cumulative and average evapo-transpiration rates. Decreasing soil and air temperatures also appear to have a negative correlation to the 5-20 µm starch populations, while increasing soil and air temperatures has a positive correlation to the 20-30 µm starch populations.
4c. THE EFFECT OF THE ENVIRONMENT ON STARCH SIZE DISTRIBUTION OF CANADIAN WHEAT VARIETIES. This study was done in collaboration with the University of Manitoba. Large qualities of starch were isolated from ~350 established Canadian wheat varieties grown throughout the country. Detailed environmental data has been compiled to correlate starch size distribution to various quality parameters. Laser diffraction starch size distributions were collected in duplicate to incorporate into a “G X E quality model system”. The data is currently in the analysis phase but soon we expect to get a more complete picture of how the environment affects wheat quality, specifically the quality of starch.
4d. IDENTIFICATION OF PROTEIN COMPOSITION FOR IDEAL TORTILLAS: The tortilla industry is one of the fastest growing segments of the U.S. baking industry with annual sales surpassing $6 billion. Flour used in tortilla production has been typically optimized for bread making and thus the flour properties that determine good quality bread do not necessarily provide good quality tortillas. The results indicated better tortillas with a longer shelf-life were obtained with higher protein content flours containing HMW-GS 5+10. This data will allow wheat breeders to target the characteristics for development of tortilla or multi-use wheat lines and decrease the addition of additives to adjust flour quality in the tortilla industry.
All of these research accomplishments fall under the National Program 306 "Quality and Utilization of Agricultural Products”, specifically on component 1 “Quality Characterization, Preservation, and Enhancement”. Multiple Problem Areas of this component are directly addressed in the objectives -- Problem Areas 1a (Definition and Basis for Quality); 1b (Methods to Evaluate and Predict Quality) and 1c (Factors and Processes that Affect Quality). The elucidation of fundamental biochemical processes and their role in determining product quality is paramount for the development of accurate methods for quality measurement.
Akdogan, H.P., Tilley, M., Chung, O.K. 2006. Effect of emulsifiers on textural properties of whole wheat tortillas during storage. Cereal Chemistry. 83(6): 632-635.
Park, S., Bean, S., Chung, O.K., Seib, P.A. 2006. Levels of protein and protein composition in hard winter wheat flours and the relationship to breadmaking. Cereal Chemistry. 83(4):418-423.
Maghirang, E.B., Lookhart, G.L., Bean, S., Pierce, R.O., Xie, F., Caley, M.S., Wilson, J.D., Seabourn, B.W., Chung, O.K., Dowell, F.E. 2006. Comparison of quality characteristics and breadmaking functionality of hard red winter and hard red spring wheat. Cereal Chemistry. Vol. 83(5):520-528.
Tilley, M., Pierucci, V., Tilley, K.A., Chung, O.K. 2006. Effects of Processing on Wheat Tortilla Quality: Benefits of Hard White Wheat. Journal of Food Science. 27(11):152-158.