Download PDF

ASABE annual international meeting 2011, Date: 2011/08/07 - 2011/08/10, Location: Louisville, Kentucky, USA

Publication date: 2011-08-07
Pages: 975 - 986
ISSN: 9781618391568

American Society of Agricultural and Biological Engineers Annual International Meeting 2011, ASABE 2011

Author:

Nguyen, Nghia
Watté, Rodrigo ; Aernouts, Ben ; Herremans, Els ; Verhoelst, Eva ; Tsuta, Mizuki ; Verboven, Pieter ; De Baerdemaeker, Josse ; Nicolai, Bart ; Saeys, Wouter

Keywords:

Spatially resolved spectroscopy, light scattering and absorption, diffusion equation, food microstructure and composition

Abstract:

Food quality is critically determined by its microstructure and composition. These properties could be quantified non-invasively by means of optical properties (absorption and reduced scattering coefficients) of the food samples. In this research, a spatially-resolved spectroscopy setup based on a fiber-optic probe was developed for acquiring spatially-resolved diffuse reflectance of five model foods with different designed microstructures and compositions in the range 400 – 1100 nm. A model for light propagation in turbid media based on diffusion approximation for solving the radiative transport equation was employed to derive optical properties (absorption and reduced scattering coefficients) of these model foods. The accuracy of this light propagation model was validated on solid phantoms with known optical properties. Results of solid phantoms indicated that diffusion equation is sufficiently accurate for modeling light propagation in the investigated samples. Derived reduced scattering coefficients µs’ of the model foods obviously showed a logical correlation with the corresponding microstructures of the model foods analyzed by optical microscopy. Estimated absorption coefficients µa were also in good agreement with the designed ingredients of these model foods. The research results clearly support the potential of spatially-resolved spectroscopy for non-destructive food quality inspection and process monitoring in the food industry.