May
2008
Volume
85
Number
3
Pages
359
—
365
Authors
Craig F. Morris,2,3
Arthur D. Bettge,2
Marvin J. Pitts,4
G. E. King,5
Kameron Pecka,2,6 and
Patrick J. McCluskey7
Affiliations
This research was supported, in part, by a grant to the WWQL from the USDA GIPSA. Mention of trademark or proprietary products does not constitute a guarantee or warranty by the U.S. Department of Agriculture and does not imply its approval to the exclusion of other products that may also be suitable.
USDA-ARS Western Wheat Quality Laboratory, Washington State University, Pullman, WA 99164-6394.
Corresponding author. Phone: +1.509.335.4062. Fax +1.509.335.8573. E-mail: morrisc@wsu.edu
Department of Biological Systems Engineering, Washington State University, Pullman, WA 99164-6120.
Department of Food Science & Human Nutrition, Washington State University, Pullman, WA 99164-6394. Currently assigned to the Western Wheat Quality Laboratory.
Current address: Leprino Foods, Tracy, CA 95376-2095.
USDA-GIPSA Federal Grain Inspection Service, Kansas City, MO 64133.
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RelatedArticle
Accepted December 31, 2007.
Abstract
ABSTRACT
The three major classes of endosperm texture (grain hardness) of soft and hard common, and durum wheat represent and define one of the leading determinants of the milling and end-use quality of wheat. Although these three genetic classes are directly related to the Hardness locus and puroindoline gene function, much less is known about the kernel-to-kernel variation within pure varietal grain lots. Measurement of this variation is of considerable interest. The objective of this research was to compare kernel texture as determined by compression failure testing using endosperm bricks with results of whole-kernel hardness obtained with the Single Kernel Characterization System 4100 hardness index (SKCS HI). In general terms, the variation obtained with the SKCS HI was of similar magnitude to that obtained using failure strain and failure energy of endosperm brick compression. Objective comparisons included frequency distribution plots, normalized frequency distribution plots, ANOVA model R2, and coefficients of variation. Results indicated that compression testing and SKCS HI similarly captured the main features of texture classes but also reflected notable differences in texture properties among and within soft, hard, and durum classes. Neither brick compression testing nor the SKCS HI may be reasonably expected to correctly classify all individual kernels as to genetic texture class. However, modest improvements in correct classification rate or, more importantly, better classification related to end-use quality may still be achievable.
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ArticleCopyright
This article is in the public domain and not copyrightable. It may be freely reprinted with customary crediting of the source. AACC International, Inc., 2008.