|Barton Ii, Franklin|
Submitted to: Journal of Agricultural and Food Chemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: December 15, 2003
Publication Date: February 20, 2004
Citation: Kays, S.E., Barton Ii, F.E. Energy from fat determined by near-infrared reflectance spectroscopy. Journal of Agricultural and Food Chemistry 52(6): 1669-1674. 2004. Interpretive Summary: Near infrared(NIR) spectroscopy represents a rapid and accurate method of measuring constituents of materials without requiring extensive sample preparation, nor creating chemical waste. A considerable advantage of NIR spectroscopy as an analytical technique is the ability to quantitatively determine several constituents of a product simultaneously. Previous work has demonstrated that NIR reflectance spectroscopy can be used to predict total dietary fiber, protein, fat, gross energy and utilizable energy, rapidly and accurately, in a wide range of cereal products. The objective of the study was to investigate the potential of NIR to determine the energy derived from fat in diverse cereal products. It was found that NIR models could be developed to predict the amount of energy from fat per gram of product and the percent of energy from fat. Statistics indicated that all NIR models provided accurate prediction of energy derived from fat in a aset of independent validation samples. The study 1) shows that the time required for the analysis of energy in cereal products can be drastically reduced using NIR and 2) has expanded the potential of NIR for the rapid evaluation and monitoring of most macro nutrients on the nutrition label.
Technical Abstract: The potential of NIR spectroscopy for the evaluation of energy derived from fat was explored in diverse cereal products. Using NIR reflectance spectra (1104-2494 nm) obtained with a NIRSystems 6500 scanning monochromator and reference values for energy obtained from Soxlet analysis of fat using a conversion factor of nine kcal per g of fat to calculate fat energy, a modified partial least squares model was developed for the prediction of calories derived from fat per g sample. The SECV and multiple coefficient of determination for prediction of kcal from fat per g sample (n=51) were 0.103 kcal and 0.97, respectively, and the standard error of performance, coefficient of determination, bias and slope using an independent validation set (n=55) were 0.076 kcal, 0.99, 0.004 kcal and 0.99, respectively. Similar accuracy was obtained for prediction of the percent of calories derived from fat in a product. Statistics derived for all models indicate that NIR spectroscopy provides a rapid and accurate method for the prediction of energy derived from fat in cereal foods.