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United States Department of Agriculture

Agricultural Research Service

Title: Prediction of Quality Characteristics of Hard Winter Wheats Using Single Kernel and Mixograph Parameters

Authors
item Chung, Okkyung
item Ohm, Jae-Bom - KANSAS STATE UNIVERSITY
item Caley, Margo
item Seabourn, Bradford

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: July 25, 2000
Publication Date: November 5, 2000
Citation: Chung, O.K., Ohm, J., Caley, M.S., Seabourn, B.W. 2000. Prediction of quality characteristics of hard winter wheats using single kernel and mixograph parameters. Abstract No. 428 in: 2000 AACC Annual Meeting Program Book. p.171. Meeting Abstract.

Interpretive Summary: Presented at the 2001 American Association of Cereal Chemists Annual Meeting held in Charlotte, NC, from October 14-18, 2001.

Technical Abstract: Single kernel and mixograph parameters of hard winter wheats were gathered from federal regional nurseries from 1990 to 1999. Eight characteristics and 12 machine parameters obtained from Single Kernel Characterization System were used to develop a prediction model of flour yield by continuum regression. Flour yield showed mean values of 68.8% and standard deviations of 6.6 and 3.5 for calibration (n=1200) and validation sets (n=300), respectively. Prediction model of flour yield showed an R2 of 0.696 for calibration set and 0.684 for validation set. Wheat protein content, single kernel characteristics, and objective computer-analyzed mixograph parameters were also used to develop prediction models of bread-making properties by continuum regression. Bread loaf volume showed mean values of 880 cm3 and standard deviations of 96 and 86 for calibration and validation sets, respectively. Prediction model of bread loaf volume showed R2 of 0.754 and 0.698 for calibration (n=1097) and validation (n=319) sets, respectively. Prediction models of mixograph mixing tolerance and baking water absorption, mixing time, and specific loaf volume showed R2 values of 0.713, 0.726, 0.865, and 0.814 for the calibration set and 0.676, 0.741, 0.835, and 0.779 for the validation set, respectively.

Last Modified: 4/19/2014
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