Publication no. C-2004-0728-01R |  VIEW ARTICLE

Detecting Vitreous Wheat Kernels Using Reflectance and Transmittance Image Analysis.

Feng Xie (1), Tom Pearson (2,3), Floyd E. Dowell (3), and Naiqian Zhang (1). (1) Biological and Agricultural Engineering Department, Kansas State University, 147 Seaton Hall, Manhattan, KS 66506. (2) Corresponding author. E-mail: <tpearson@gmprc.ksu.edu> (3) USDA-ARS, Grain Marketing and Production Research Center, 1515 College Avenue, Manhattan, KS 66502. Cereal Chem. 81(5):594-597. Accepted March 15, 2004. This article is in the public domain and not copyrightable. It may be freely reprinted with customary crediting of the source. American Association of Cereal Chemists, Inc., 2004.

The proportion of vitreous durum kernels in a sample is an important grading attribute in assessing the quality of durum wheat. The current standard method of determining wheat vitreousness is performed by visual inspection, which can be tedious and subjective. The objective of this study was to evaluate an automated machine-vision inspection system to detect wheat vitreousness using reflectance and transmittance images. Two subclasses of durum wheat were investigated in this study: hard and vitreous of amber color (HVAC) and not hard and vitreous of amber color (NHVAC). A total of 4,907 kernels in the calibration set and 4,407 kernels in the validation set were imaged using a Cervitec 1625 grain inspection system. Classification models were developed with stepwise discriminant analysis and an artificial neural network (ANN). A discriminant model correctly classified 94.9% of the HVAC and 91.0% of the NHVAC in the calibration set, and 92.4% of the HVAC and 92.7% of the NHVAC in the validation set. The classification results using the ANN were not as good as with the discriminant methods, but the ANN only used features from reflectance images. Among all the kernels, mottled kernels were the most difficult to classify. Both reflectance and transmittance images were helpful in classification. In conclusion, the Cervitec 1625 automated vision-based wheat quality inspection system may provide the grain industry with a rapid, objective, and accurate method to determine the vitreousness of durum wheat.


Figure 1 is in color in this online article.