The use of rapid instrumental methods to assess freshness of half shell Pacific oysters, Crassostrea gigas: A feasibility study

• Published in: Innovative Food Science & Emerging Technologies
• Main Authors: Madigan, Thomas, Kiermeier, Andreas, Carragher, John, De Barros Lopes, Miguel, Cozzolino, Daniel
• Format: Article in Journal/Newspaper
• Language: English
• Published: Elsevier BV 2013
• Subjects: Digital image analysis; Near-infrared reflectance spectroscopy; Oysters; Shelf-life; 1600 Chemistry; 1106 Food Science; 2209 Industrial and Manufacturing Engineering; Pacific; Crassostrea gigas
• Online Access: https://espace.library.uq.edu.au/view/UQ:ac18fe7

This study aimed to assess the feasibility of the use of instrumental methods such as digital image analysis (DIA) and near-infrared reflectance spectroscopy (NIRS) to objectively characterise changes in freshness (shelf-life) of half shell Pacific oysters, Crassostrea gigas. Oysters were stored in air under PVC film for five days at 4 C. On a daily basis, oysters were photographed with a digital camera, spectra were collected using a Fourier transform NIR spectrometer in reflectance mode and odour analysed by a sensory panel. Calibrations based on NIRS were successfully developed for days of storage (R = 0.8, RER = 5.37) and odour (R = 0.77, RER = 7.77) with the latter being influenced by wavelengths typically associated with aromatic compounds. However, colour (derived from digital images) was found to be a poor indicator of freshness. This work has demonstrated the feasibility of NIRS as an objective measure of oyster freshness. Industrial relevance This manuscript describes a feasibility study that assesses the use of digital image analysis and near-infrared spectroscopy to objectively define the freshness of half shell oysters. Successful near-infrared calibrations were developed for days of refrigerated storage and also for odour. We have also demonstrated the potential for use this applications in food processors and retailers to rapidly evaluate freshness and quality of products. The proposed method shows promise for at-line analysis.