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United States Department of Agriculture

Agricultural Research Service


Location: Grain Quality and Structure Research Unit

Project Number: 5430-44000-018-00
Project Type: Appropriated

Start Date: Oct 01, 2004
End Date: Sep 30, 2009

Determine and evaluate the intrinsic end-use quality of hard winter wheat progenies for wheat breeding programs in the hard winter wheat growing Great Plains Area in order to enhance U.S. hard winter wheat attributes desired by both domestic and international customers, develop rapid and objective methods for estimating/predicting textural and quality differences from: (a) small samples (< 10 g) in early generation hard winter wheat breeding lines to promote efficient selection of hard winter wheat lines for needed-quality bases, which would result in the possibility of shortening the breeding program by 1-2 years without sacrificing intrinsic quality evaluation efforts; and (b) from commercial hard winter wheats to enhance the marketing system based on intrinsic quality and determine and evaluate quality parameters directed toward uses of hard winter wheats in non traditional, non-bread products such as tortillas and Asian noodles, to promote U.S. hard winter wheats in the domestic and export markets.

Graphic images of the mixograph curve for each wheat line in the HWWQL database will be added for the next release of the database, as well as an interface for user-selected statistical analyses; study the effects of flour particles and starch granular size distributions on bread crumb grain; study flour hydration and the interaction of water with flour proteins, starches, and lipid and determine optimum hydration point by FTIR; develop modified micro-scale PPO test; develop micro-scale noodle-making test and tortilla-making methods; study the rheological properties of tortillas and tortilla doughs to understand and predict quality parameters. Investigate the breadmaking quality relationships between various methods (pound loaf, pup loaf, and micro-loaves using 35-g, 10-g, and 2-g flour) to obtain the conversion factors for loaf volumes: study the changes in the secondary structure of the gluten matrix in dough during mixing and determine optimum dough development by FTIR; screen breeder samples for PPO and noodle-making quality; continue studying and developing methods for measuring the rheological properties of tortillas and tortilla doughs, and correlate NIR prediction models to those properties. Study both genetic and environmental effects on protein and lipid contents and composition with breeders samples grown at various locations; determine by FTIR and Raman spectroscopy the influence of covalent bonding on dough strength, specifically disulfide bonds within and between polypeptide chains as well as bonds between amino acid side-chains in the gluten polymer (e.g. tyr-tyr bonds); screen breeder samples for PPO, noodle color, and noodle-making quality; establish texture analyzing processes for raw and cooked noodles; begin to develop small scale rheological methods and analyze the molecular size distribution of tortilla dough proteins to predict end-use properties of tortillas. Investigate the effect of variation in kernel hardness and weight in wheat samples on milling and baking properties and continue to study the relationships between wheat physical characteristics and end-use properties, which may be used to segregate wheats based on quality; study protein-starch, protein-lipid, and starch-lipid interactions in a model system during mixing, fermentation, and baking stages; determine the influence of various standard ingredients on dough rheology by FTIR; screen breeder samples for PPO, noodle color, and eating quality, based on a texture analysis of raw and cooked noodles; continue to provide early generation information to breeders that predict the tortilla making properties of wheats. Complete prediction models for quality attributes desired by breeders and industry; apply mid-IR information on dough rheology to the development of near-IR measurement of important dough rheology parameters during mixing; develop an online "real-time" dough monitoring system to be used by the HWWQL and baking industry; develop NIR calibration models for rapid measurement of PPO and noodle-making quality in breeder and commercial samples; complete prediction models for tortilla rheology and quality attributes desired.

Last Modified: 9/10/2014
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