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Compressive Strength of Wheat Endosperm: Comparison of Endosperm Bricks to the Single Kernel Characterization System
Author(s) -
Morris Craig F.,
Bettge Arthur D.,
Pitts Marvin J.,
King G. E.,
Pecka Kameron,
McCluskey Patrick J.
Publication year - 2008
Publication title -
cereal chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.558
H-Index - 100
eISSN - 1943-3638
pISSN - 0009-0352
DOI - 10.1094/cchem-85-3-0359
Subject(s) - endosperm , kernel (algebra) , texture (cosmology) , mathematics , compression (physics) , biological system , coefficient of variation , statistics , botany , composite material , biology , materials science , computer science , artificial intelligence , pure mathematics , image (mathematics)
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 R 2 , 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.