Submitted to: Journal of Agricultural and Food Chemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/7/2004
Publication Date: 2/12/2005
Citation: Vines, L.L., Kays, S.E., Koehler, P.E. 2005. A near infrared reflectance model for the rapid prediction of total fat in cereal foods. Journal of Agricultural and Food Chemistry. 53:1550-1555. Interpretive Summary: Near-infrared (NIR) reflectance spectroscopy is a technique that measures the amount of light energy, in a specific region of the electromagnetic spectrum, reflected by a substance and relates that energy to a measured component of the substance by mathematical modeling. The technique is rapid and does not require the use, or disposal, of chemicals. Since the enactment of the Nutrition Labeling and Education Act (NLEA), total fat content in cereal foods has been determined using an official reference method (AOAC Method 996.01), which is very labor intensive, costly, time consuming, and requires the use and disposal of hazardous organic solvents. The objectives of this study were to construct a model, using near-infrared reflectance spectroscopy, for the prediction of total fat in cereal products and assess the model's accuracy for U.S. nutrition labeling. A rapid and accurate NIR model was developed to predict total fat content in cereal products containing a wide range of fat, grain types, additives and processing methods. All independent test samples were predicted by the model within NLEA accuracy guidelines. Thus, the NIR reflectance model can be used by the food industry, commercial analysis laboratories, and regulatory agencies that monitor labeling accuracy.
Technical Abstract: AOAC Method 996.01, used to determine total fat in cereal foods as defined by the U.S. Nutrition Labeling and Education Act (NLEA), is laborious, time consuming and solvent dependent. Near-infrared (NIR) reflectance spectroscopy, a rapid and environmentally benign technique, was investigated as a potential method for prediction of total fat. Near-infrared reflectance spectra (1104-2494 nm) of ground cereal products (n=72) were obtained using a dispersive spectrometer and total fat determined by AOAC Method 996.01. Using multivariate analysis, a modified partial least squares model was developed for total fat prediction, having a SECV of 1.12% (range 0.5-43.2%) and multiple coefficient of determination of 0.99. The model was tested with independent validation samples (n=36); all samples were predicted within NLEA accuracy. Near-infrared reflectance spectroscopy, therefore, has considerable potential for determination of total fat in diverse cereal products for nutrition labeling and monitoring.