Fourier transform infrared (FT-IR) spectroscopy is a simple, rapid, and reliable technique that has been widely researched and applied for analysis of food components, which can identify types of chemical bonds in a molecule by producing an infrared absorption spectrum that is like a molecular "fingerprint". FTIR combined with chemometrics, including SIMCA and PLS, makes it a strong technique to identify unknown materials, determine the quality or consistency of a sample, and determine the amount of components in a mixture.
The world snack food market reached an estimated $66 billion in 2003, with the United States accounting for about a third of it. However the sensor devices currently available are not suitable in a food processing operation. There is an urging demand for rapid, high through-put, and real-time instruments for the food industry. The objective of this research was to evaluate the feasibility of infrared systems combined with chemometric analysis for rapid quality assessment in applications to Ohio’s snack industry.
Snack products samples were grounded and spectra were collected using MIR and NIR equipped with 3-bounce ZnSe MIRacle attenuated total reflectance accessory or a diffuse reflection-integrating sphere separately. Partial Least Square Regression (PLSR) was used to construct prediction models. The spectra showed characteristic absorption bands for sugars (MIR and NIR) and the salt-induced changes in the NIR water spectrum as affected by salt content. Best performance PLSR models for salt content were generated from NIR reflectance (SECV=0.016% and r = 0.96) whereas similar statistics were obtained for sugar levels (SEP ~0.02mg/g cereal and r > 0.98).
FTIR combined with PLSR analysis provided a rapid quality assessment technique, which can finally improve the quality control of snack food industry by saving testing time, decreasing investment and providing reliable results.