Skip to main content
ARS Home » Plains Area » Manhattan, Kansas » Center for Grain and Animal Health Research » Grain Quality and Structure Research » Research » Publications at this Location » Publication #100027

Title: PREDICTION OF GLIADIN AND SOLUBLE/INSOLUBLE HMW GLUTENIN FRACTIONS IN WHOLE KERNEL WHEAT BY NEAR-INFRARED REFLECTANCE SPECTROSCOPY

Author
item Seabourn, Bradford
item BEAN, S - KANSAS STATE UNIVERSITY
item Lookhart, George
item Chung, Okkyung

Submitted to: Cereal Foods World
Publication Type: Abstract Only
Publication Acceptance Date: 7/21/1999
Publication Date: N/A
Citation: Seabourn, B.W., Bean, S.R., Lookhart, G.L., Chung, O.K. 1999. Prediction of gliadin and soluble/insoluble hmw glutenin fractions in whole kernel wheat by near-infrared reflectance spectroscopy. Cereal Foods World. Abstract No. 93 in: 1999 AACC Annual Meeting Program Book. p.177. Meeting Abstract.

Interpretive Summary: To be presented at the 84th AACC Meeting held October 31-November 3, 1999, in Seattle, WA.

Technical Abstract: We confirmed in a recent study that gliadin and polymeric proteins (insoluble glutenins) could be predicted with sufficient accuracy from the near-infrared reflectance (NIR) spectra of wheat flour. In this study, we looked at the potential for predicting gliadin (G), soluble glutenin (SG), and insoluble glutenin (IG) contents from the NIR spectra of whole kernel wheat. One hundred hard winter wheats were obtained from the USDA/ARS Hard Winter Wheat Quality Laboratory (HWWQL), Manhattan, KS. The wheats were grown at two federal regional breeding nurseries during the 1993-1995 crop years. The wheats were selected using the HWWQL Relational Database based upon their aggregate milling and baking scores. The flours from these wheats were analyzed by HPLC for their G and SG contents, and by Leco Nitrogen Analyzer for their IG content. Using NIR spectra of the whole kernel wheats, we found that G and IG fractions could be predicted with an accuracy acceptable for screening purposes (r(^2) > 0.60). For IG, the standard error of cross-validation for the model was (r(^2) = 0.79), which was slightly lower than what was previously found in our study with flour (r(^2) = 0.83). In both wheat and flour, we were unable to predict SG content. However, G content could be predicted in both wheat (r(^2) = 0.76) and flour (r(^2) = 0.79). Since IG has been confirmed in a number of studies to play an important role in bread making, particularly dough strength, these results indicate that NIR may be very useful in plant breeding programs and quality laboratories where rapid screening for dough strength of large numbers of wheat lines is needed.