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Use of spectroscopic data for automation in food processing industry

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Abstract

Advances in spectroscopy now enable researchers to obtain information about chemical and physical components in food or biological materials at the molecular level. Various spectroscopic techniques (e.g., atomic absorption spectroscopy, Raman and Fourier-transform infrared spectroscopy, near infrared spectroscopy, nuclear magnetic resonance spectroscopy, mass spectroscopy, X-ray fluorescence spectroscopy, ultra-violet spectroscopy) have been used to study structure-function relationships in foods (both liquid and solid) to improve overall food quality, safety and sensory characteristics; to investigate fungal infections in plant materials (e.g., fruits, seeds); or to study mobility of different chemical components in food materials. Processing, analyzing, and displaying these data can often be difficult, time-consuming, and problem-specific. Chemometrics is well established for calibrating the spectral data to predict concentrations of constituents of interest. Similarly, proteomics deals with the structure-function relationship of proteins. Since most of the food processing industries are becoming increasingly automated, there is a need to understand how the spectroscopic data can be used for automation. In this paper, we have provided basic working principles of the above mentioned spectroscopic techniques, examples of the use of spectral data in food processing, methods of analysis of spectral data and their integration in the automation process.

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Acknowledgement

Authors thank the Canada Research Chairs Program for partial funding of this study.

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Author notes

  1. Prabal K. Ghosh

    Present address: Food Development Centre, Portage la Prairie, MB, R1N 3J9, Canada

Authors and Affiliations

  1. Biosystems Engineering, University of Manitoba, Winnipeg, MB, R3T 2N2, Canada

    Prabal K. Ghosh & Digvir S. Jayas

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  1. Prabal K. Ghosh
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  2. Digvir S. Jayas
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Corresponding author

Correspondence to Digvir S. Jayas.

Additional information

Meeting presentation: Food Processing Automation Conference, Providence, RI, 28–29 June 2008. ASABE Publication Number 701P0508 cd.

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Ghosh, P.K., Jayas, D.S. Use of spectroscopic data for automation in food processing industry. Sens. & Instrumen. Food Qual. 3, 3–11 (2009). https://doi.org/10.1007/s11694-008-9068-7

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