Non-destructive stochastic model-based detection of diet-induced alterations in fish texture
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ORIGINAL PAPER
Non-destructive stochastic model-based detection of diet-induced alterations in fish texture Kriton Grigorakis • Dimitrios Dimogianopoulos
Received: 13 December 2011 / Accepted: 11 October 2012 / Published online: 30 October 2012 Springer Science+Business Media New York 2012
Abstract A stochastic model-based scheme detecting diet-induced textural alterations in fish muscle in an innovative, non-destructive manner is presented. The scheme operates on proven fault diagnosis principles as used in mechanical systems. It combines a cost-effective instrument setup, along with a non-destructive, vibration-like testing of fish samples and an accurate (under typical uncertainties) stochastic modeling of their response. The identified models provide key indicators indirectly related to the tested fish’s texture, itself affected by (and, thus indicative of) its dietary history. Statistical hypothesis tests perform comparisons of such key indicators from tests with fish samples of different dietary histories. The issued statistical decisions allow for reliable tracing of fish on the basis of the diet-induced textural changes, while quantifying the risk of the decision-making process. Validation tests involved samples from two distinct fish groups sharing similar dietary histories except for a supplementation of dietary taurine at 1 % level in one of them. The altered textural characteristics in taurine-supplemented fish (initially suggested by taste panel evaluation) were effectively detected via the proposed scheme. These promising results suggest the scheme’s potential as a non-destructive, costeffective and reliable solution for fish traceability.
Kriton Grigorakis and Dimitrios Dimogianopoulos have equal sharing for authorship. K. Grigorakis (&) Hellenic Centre for Marine Research, Institute of Aquaculture, Agios Cosmas, Hellinikon, 16777 Athens, Greece e-mail: [email protected] D. Dimogianopoulos Department of Automation, Technological Education Institute of Piraeus, 12244 Athens, Greece
Keywords Dicentrarchus labrax Sea bass Texture Diet Traceability Stochastic model-based diagnosis Statistical hypothesis test
Introduction The need for rapid and non-destructive control in food quality has been a source of intense motivation for researchers in the relevant sector [1]. Since raw fish is a highly perishable food, intensive efforts have been invested for reliably and rapidly assessing its major quality attributes. Among them, freshness has received commendable attention, as shown by several different assessment methodologies reported [2–4]. Recent work [5] presented the development of rapid, non-destructive techniques, which could provide accurate evaluation of fish freshness in a costeffective and user-friendly manner. The key idea was to test a system involving a fish as part of a tailor-made instrument setup, and use model identification principles for assessing its mechanical properties. Alterations in fish texture due to reduced freshness should affect the mechanical properties of the overa
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