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ARS Home » Research » Publications at this Location » Publication #173369
Title: NIR ANALYSIS OF LIPID CLASSES IN PROCESSED CEREAL PRODUCTS

Author
item VINES, LAURA - UNIVERSITY OF GEORGIA
item KAYS, SANDRA
item KOEHLER, P. - UNIVERSITY OF GEORGIA

Submitted to: Near Infrared Spectroscopy International Conference Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: 12/23/2004
Publication Date: 4/9/2005
Citation: Vines, L.L., Kays, S.E., Koehler, P.E. 2005. NIR analysis of lipid classes in processed cereal products [abstract]. Tenth International Conference on Near Infrared Spectroscopy. p. 92.

Interpretive Summary:

Technical Abstract: Declaration of total and saturated fat content of processed and packaged foods is required for nutrition labeling in the U.S.A.; declaration of mono- and polyunsaturated fat is voluntary. The accepted methods for analysis of these components are extremely labor-intensive and time consuming; therefore, near infrared spectroscopy was investigated as a rapid method for their analysis in foods. Total lipid and fatty acid composition were determined in diverse cereal food products by AOAC Method 996.01 and near infrared spectra obtained using a dispersive near infrared instrument (range 400-2498 nm). Individual chemometric models (n=72-73) for the prediction of total, saturated, polyunsaturated and monounsaturated fatty acids were developed with WINISI and ISI40 multivariate analysis software and tested with an independent validation set (n=34-36). The standard error of cross validation and multiple coefficient of determination for the prediction of total fat were 11.2 (range 5-432) g per kg and 0.99, respectively, and for saturated fat were 10.8 (range 1-147) g per kg and 0.88. Total fat was predicted in all validation samples within the accuracy required by U.S.A. nutrition labeling legislation. Saturated, monounsaturated, and polyunsaturated fats were predicted within the accuracy required for nutrition labeling in 91%, 97% and 91% of the validation samples, respectively. It may be possible to improve the models for the prediction of lipid classes by modification of the reference method. In conclusion, NIR spectroscopy has excellent potential for prediction of lipid classes in processed cereal products.