Spectral Library Searching: Mid-Infrared versus Near-Infrared Spectra for Classification of Powdered Food Ingredient

Abstract

The objective of this study was to determine the potential of using mid- or near-infrared diffuse reflectance spectra to construct food ingredient spectral libraries for product identification and checking. Samples (106) consisting of buttermilk, dehydrated onion, cheese and milk-egg powders, wheat flours, and two powdered seasonings were scanned “as is” (not diluted with KBr using diffuse reflectance) at 4 and 16 cm⁻¹ resolution in the mid-infrared on a Digilab FTS-60 and a Perkin-Elmer Model 2000 and in the near-infrared on an FTS-60 (4 and 16 cm⁻¹ resolution) and NIRSystems Model 6500 scanning monochromator (10 nm bandwidth). A custom-made sample transport device was used on the FTS-60, a rotating sample cup on the NIRSystems 6500, and a stationary cell for the Perkin-Elmer 2000. Every third sample of each group was used as a test sample and searched against a library containing the remaining samples. Results showed that only full spectrum based searches with the use of Euclidian distance or correlation (with or without a first derivative) were useful. All unknowns were correctly classified by using near-infrared spectra generated on either the scanning monochromator or the FTS-60 (4 cm⁻¹ resolution) or by using any of the mid-infrared spectra. Results demonstrated that near- or mid-infrared spectral libraries of powdered food ingredients can be used for product identification and checking.