RAPID PREDICTION OF ENERGY CONTENT IN CEREAL FOOD PRODUCTS WITH NIRS

Authors: Kays, Sandra; Barton Ii, Franklin

Submitted to: Near Infrared Spectroscopy International Conference Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: 6/6/2001
Publication Date: 6/10/2001
Citation: Kays, S.E., Barton II, F.E. 2001. Rapid prediction of energy content in cereal food products with nirs. 10th International Conference on Near Infrared Spectroscopy. Abstracts, pp. 5-11.

Interpretive Summary:

Technical Abstract: Energy content, expressed as calories per gram, is an essential part of the evaluation and marketing of foods in developed countries. This study investigated the ability of NIRS methods to predict the energy value of diverse cereal food products. NIR spectra of cereal food products were obtained with an NIRSystems monochromator and the wavelength range used for ranalysis was 1104-2494 nm. Gross energy of the foods was measured by oxygen bomb calorimetry (Parr Manual No. 120) and expressed as calories per gram (CPG1, range 4.05-5.49 kcal/g). Energy value was adjusted for unutilized protein (CPG2, range 3.99-5.38 kcal/g) and unutilized protein and insoluble dietary fiber (CPG3, range 2.42-5.35 kcal/g). Using a multivariate analysis software package (ISI International) partial least squares models were developed for the prediction of energy content. The standard error of cross validation and multiple coefficient of determination for CPG1 n=127) were 0.060 kcal/g and 0.95, respectively, an the standard error of performance, coefficient of determination, bias and slope using an independent validation set (n=59) were 0.057 kcal/g, 0.98- 0.027 kcal/g and 1.05 respectively. The PLS loading for factor 1 (Pearson correlation coefficient 0.92) had significant absorption peaks correlated to C-H stretch groups in lipid at 1722/1764 nm and 2304/2346 nm and O-H groups in carbohydrate at 1434 and 2076 nm. Thus the model appeared to be predominantly influenced by lipid and carbohydrate. Models for CPG2 and CPG3 showed similar trends with standard errors of performance, using the independent validation set, of 0.058 and 0.088 kcal/g, respectively, and coefficients of determination of 0.96. Thus NIRS provides a rapid and efficient method of predicting energy content of diverse cereal foods.