Medical Journals

Near-infrared Spectroscopy for Measurement of Total Dietary Fiber in Homogenized Meals.

Authors:
  • Kim Yookyung
  • Singh Mukti
  • Kays Sandra E

From: Agricultural Research Service, U.S. Department of Agriculture, P.O. Box 5677, Athens, Georgia 30604-5677, USA.

Journal of agricultural and food chemistry

  • Publish Date: Jan 2006
  • ISSN: 0021-8561
  • Volume: 54
  • Issue: 2
  • Pages: 292-8
  • Medium: Print
  • Language: English
  • Citation (JAMA): Kim Yookyung, Singh Mukti, Kays Sandra E, et al. Near-infrared Spectroscopy for Measurement of Total Dietary Fiber in Homogenized Meals.. J. Agric. Food Chem. Jan 2006;54:292-8

Abstract

Near-infrared (NIR) reflectance spectroscopy was investigated as a method for prediction of total dietary fiber (TDF) in mixed meals. Meals were prepared for spectral analysis by homogenization only (HO), homogenization and drying (HD), and homogenization, drying, and defatting (HDF). The NIR spectra (400-2498 nm) were obtained with a dispersive NIR spectrometer. Total dietary fiber was determined in HDF samples by an enzymatic-gravimetric assay (AOAC 991.43), and values were calculated for HD and HO samples. Using multivariate analysis software and optimum processing, partial least squares models (n = 114) were developed to relate NIR spectra to the corresponding TDF values. The HO, HD, and HDF models predicted TDF in independent validation samples (n = 37) with a standard error of performance of 0.93% (range 0.7-8.4%), 1.90% (range 2.2-18.9%), and 1.45% (range 2.8-23.3%) and r(2) values of 0.89, 0.92, and 0.97, respectively. Compared with traditional analysis of TDF in mixed meals, which takes 4 days, NIR spectroscopy provides a faster method for screening samples for TDF. The accuracy of prediction was greatest for the HDF model followed by the HD model.

Mesh Headings (Keywords): Animals, Dietary Carbohydrates, Dietary Fiber, Dietary Proteins, Food Analysis, Regression Analysis, Spectroscopy, Near-Infrared, Vegetables


Check for Full Text / PubMed Unique Identifier (PMID): 16417282


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