PREDICTING A HARDNESS MEASUREMENT USING THE SINGLE-KERNEL CHARACTERIZATION SYSTEM

The single-kernel characterization system (SKCS) crushes individual ke rnels and uses algorithms based on the force-deformation profile data to classify wheat samples into soft, hard, or mixed market classes. Th ose data data were utilized to produce a predictive equation for softn ess equivalent (SE), a direct measure of wheat kernel texture obtained from milling wheat on a modified Brabender Quadrumat Jr. mill and sie ving system. Predicted SE values had a high correlation (r(2) = 0.996) with actual SE milling values. In contrast to SKCS hardness index val ues, predicted SE values accurately responded to varying kernel moistu re content and kernel size, within the ranges examined. Therefore, usi ng the SKCS data to predict an independent measure of kernel texture ( e.g., SE) may be a valuable augmentation to or replacement for using S KCS algorithms to classify wheat.