AI Article Synopsis
- The primary method for assessing fish freshness is sensory inspection, with a newer Quality Index Method (QIM) offering an alternative based on specific species parameters.
- A research project focused on using computer vision and 3D scanning to analyze the eye features of European hake over 13 days of ice storage, demonstrating a correlation with traditional freshness measures.
- The study suggests this non-destructive technique could lead to a portable tool for reliably evaluating fish freshness during transportation and marketing.
Article Abstract
The most commonly used method for fish freshness determination is the sensory inspection; alternative sensory methods such as the Quality Index Method (QIM), based on the significant sensory parameters of one specific species, have been recently suggested. Considering that most of the sensory parameters are based on chromatic and morphological visual impression, the set-up of an objective method using computer vision techniques is very promising. The objective of this research was to characterize the changes in eye chromatic and morphological characteristics of European hake (Merluccius merluccius) during 13 days of storage on ice, using a tailored computer vision technique and a 3D scanner. Results obtained by multivariate statistical analysis of the colour spectra of eye images and by the eye concavity index using a 3D scanner permitted to estimate fish unacceptability after 7 days of storage, in agreement with results obtained by QIM sensory analysis. Moreover, H NMR was used to evaluate the production of trimethylamine (TMA) and the Ki index, confirming a good correlation with eye chromatic and morphological features. This preliminary study showed the high potentiality of the developed method as a non-destructive technique for raw fish freshness characterization / prediction, being a promising approach to create a robust portable instrument for the evaluation of fish freshness in real transport and marketing conditions.
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| http://dx.doi.org/10.1016/j.foodres.2018.08.091 | DOI Listing |
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