|Barton Ii, Franklin|
Submitted to: Journal of Agricultural and Food Chemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/17/1997
Publication Date: N/A
Citation: Interpretive Summary: Near-infrared (NIR) reflectance spectroscopy, which measures the amount of light energy reflected by a substance, is a very rapid and accurate method of measuring certain constituents of materials without requiring extensive sample preparation, or creating chemical waste. In previous publications from this laboratory it was demonstrated that NIR reflectance spectroscopy could be used to predict the dietary fiber content of a wide range of cereal products including products with high sugar content. In this study, the calibration for dietary fiber is expanded to include high fat cereal products, (for example, granolas and crackers) and an equation developed to predict total dietary fiber in cereal products containing high fat and/or high sugar. The accuracy of the calibration was similar to that of the previous calibrations. Thus, an NIR model was developed to predict total dietary fiber in a wide range of cereal products with a wide range of fat and sugar content. The NIR calibration reduces the time required to determine total dietary fiber content of cereal products from 2-3 days, using the original method, to a few minutes, using NIR spectroscopy, and has potential benefit for both the cereal product industry and agencies responsible for monitoring compliance with the Nutrition Labeling and Education Act.
Technical Abstract: The near-infrared (NIR) spectral properties of cereal products containing high fat or sugar can differ substantially from the spectral properties of other cereal products. An existing NIR, partial least squares model for the prediction of dietary fiber in cereal products was expanded to include products with high fat content and products with high sugar and crystalline esugar. Dry milled cereal and grain products were analyzed in the laboratory by AOAC method 991.43 for determination of total dietary fiber and scanned with an NIRSystems monochromator. ISI software was used for data analysis and selection of representative high fat and high sugar samples. The fat-expanded and fat- and sugar-expanded models had similar standard errors of cross validation (SECV) and multiple coefficient of determination to the existing model, with acceptable standard error of performance (SEP) and coefficient of determination when tested with independent validation samples. The fat- and sugar-expanded model had SECV, multiple coefficient of determination, SEP and coefficient of determination of 1.73%, 0.98, 1.32%, and 0.99, respectively. The existing model was, thus, expanded to include high fat, high sugar, and high crystalline sugar cereal products while maintaining model accuracy.