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United States Department of Agriculture

Agricultural Research Service

Title: Determining Vitreous Subclasses of Hard Red Spring Wheat by Using Near Infrared Spectroscopy

Authors
item Wang, D - KSU, MANHATTAN, KS 66502
item Dowell, Floyd
item Dempster, Richard - AIB, MANHATTAN, KS 66502

Submitted to: Transactions of the ASAE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: January 8, 2002
Publication Date: May 1, 2002
Citation: Wang, D., Dowell, F.E., and Dempster, R. 2002. Determining vitreous subclasses of hard red spring wheat by using near infrared spectroscopy. Transactions of the American Society of Agricultural Engineers. 79(3):418-422.

Interpretive Summary: The number of dark hard vitreous (DHV) kernels in hard red spring wheat is an important grading factor that is associated with protein content, kernel hardness, milling properties, and cooking quality. The current visual method of determining DHV and non-DHV (NDHV) wheat kernels is time consuming, tedious, and subjective. The objective of this research was to classify DHV and NDHV wheat kernels by using near-infrared (NIR) spectroscopy. Results show that the major contributors to classifying DHV and NDHV kernels are protein content, kernel hardness, starch content, kernel color, and a scattering effect on the absorption spectrum. Bleached kernels were the most difficult to classify. The sample set with bleached kernels yielded lower classification accuracies of 91.1 to 97.1% compared to 97.5 to 100% for the sample set without bleached kernels. Results show that NIR spectroscopy can be used to objectively differentiate DHV from NDHV kernels. This should improve classification accuracy and ultimately improve the quality and consistency of food products made from hard red spring wheat.

Technical Abstract: The content of dark hard vitreous (DHV) kernels in hard red spring wheat is an important grading factor that is associated with protein content, kernel hardness, milling properties, and cooking quality. The current visual method of determining DHV and non-DHV (NDHV) wheat kernels is time consuming, tedious, and subject to large errors. The objective of this research was to classify DHV and NDHV wheat kernels including kernels that are checked, cracked, sprouted, or bleached by using near-infrared (NIR) spectroscopy. Spectra from single DHV and NDHV kernels were collected using a diode-array NIR spectrometer. The dorsal and crease sides of the kernels were viewed. Three wavelength regions, 500-750nm, 750-1700 nm, and 500-1700 nm, were compared. Spectra were analyzed by using partial least squares (PLS) regression. Results show that the major contributors to classifying DHV and NDHV kernels are light scattering, protein content, kernel hardness, starch content, and kernel color effects on the absorption spectrum. Bleached kernels were the most difficult to classify because of their high lightness values. The sample set with bleached kernels yielded lower classification accuracies of 91.1 to 97.1% compared to 97.5 to 100% for the sample set without bleached kernels. More than 75% of misclassified kernels were bleached. Classification models that included the dorsal side gave the highest classification accuracies (99.6 to 100%) for the testing sample set. Wavelengths in both the visible and NIR regions or the NIR regions or the NIR region alone yielded better classification accuracies than these in the visible region only.

Last Modified: 4/19/2014
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