Multisensor for fish quality determination

Ólafsdóttir, Guðrún; Nesvadba, P.; Natale, Corrado Di; Careche, Mercedes; Oehlenschläger, Jörg; Tryggvadóttir, Soffía Vala; Schubring, Reinhard; Kroeger, Michael; Heia, Karsten; Esaiassen, Margrethe; Macagnano, Antonella; Jørgensen, Bo

doi:10.1016/j.tifs.2003.08.006

Cited by 248 publications

(136 citation statements)

References 12 publications

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“…The state of freshness can be described by a variety of definite properties of the fish which can be assessed by various indicators [6] . These properties, and thus the freshness and quality of the end product, are dependent on different biological and processing factors that influence the degree of various physical, chemical, biochemical and microbiological changes occurring post mortem in fish [1] . Freshness makes a major contribution to the quality of fish or fishery products.…”

Section: Figmentioning

confidence: 99%

“…One of the most unique characteristics of fish as food is that it is a highly perishable commodity. Consequently time passed after catch and the temperature 'history' of fish is very often the key factor determining the final quality characteristics of fish products [1] . Sensory assessment has always played a key role in quality and freshness evaluation in the fish industry.…”

Section: Introductionmentioning

confidence: 99%

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A Review on Correlations between Fish Freshness and pH during Cold Storage

Abbas¹,

Mohamed²,

Jamilah³

et al. 2008

American J. of Biochemistry and Biotechnology

119

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Freshness of fish in most markets was found to be the significant quality parameter. The state of fish freshness was assessed by various methods but most of them were costly, time-consuming and not user friendly tools which made the development of simple, easy, undemanding and reliable system for the evaluation of fish freshness unresolved goal. The findings of many researchers revealed that there was remarkable correlation between the pH and the fish freshness which suggested that this physical characteristic could be used as suitable tool for the analysis and fish freshness evaluation rather than sensory evaluation method which inherent many uncertainties. Based on this demand, this paper was established with the objective of reviewing the literature which focused on the pH as one of the simple and reliable freshness indicator for cold stored fish samples.

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Section: Figmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Review on Correlations between Fish Freshness and pH during Cold Storage

Abbas¹,

Mohamed²,

Jamilah³

et al. 2008

American J. of Biochemistry and Biotechnology

119

View full text Add to dashboard Cite

show abstract

“…Due to its rapid deterioration, freshness has become one of the most important quality parameters of fish and fish products for the consumers, traders, and processors (Huang et al 2011). The conventional methods for fish freshness determination are usually based on principles of physical, chemical, microbiological, and sensory evaluation (Olafsdottir et al 2004), these techniques however, although reliable and accurate, are destructive, tedious, involve chemicals use, and above all require highly skilled personnel (Zaragozá et al 2012). In this regard, there is therefore the need to develop and evaluate a convenient, accurate, reliable, and environmentally friendly analytical method for fish freshness determination.…”

mentioning

confidence: 99%

“…An excellent introduction to sensor technologies for fish freshness detection can be found in refs. ( Olafsdottir et al 2004;Cheng et al 2013b). However, all these sensor technologies have their own advantages and disadvantages (Olafsdottir et al 2004;Cheng et al 2013b).…”

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A nondestructive method for fish freshness determination with electronic tongue combined with linear and non-linear multivariate algorithms

et al. 2014

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Han F., Huang X., Teye E., Gu H., Dai H., Yao L. (2014): A nondestructive method for fish freshness determination with electronic tongue combined with linear and non-linear multivariate algorithms. Czech J. Food Sci., 32: 532-537.Electronic tongue coupled with linear and non-linear multivariate algorithms was attempted to address the drawbacks of fish freshness detection. Parabramis pekinensis fish samples stored at 4°C were used. Total volatile basic nitrogen (TVB-N) and total viable count (TVC) of the samples were measured. Fisher liner discriminant analysis (Fisher LDA) and support vector machine (SVM) were applied comparatively to classify the samples stored at different days. The results revealed that SVM model was better than Fisher LDA model with a higher identification rate of 97.22% in the prediction set. Partial least square (PLS) and support vector regression (SVR) were applied comparatively to predict the TVB-N and TVC values. The quantitative models were evaluated by the root mean square error of prediction (RMSEP) and the correlation coefficient in the prediction set (R pre ). The results revealed that SVR model was superior to PLS model with RMSEP = 5.65 mg/100 g, R pre = 0.9491 for TVB-N prediction and RMSEP = 0.73 log CFU/g, R pre = 0.904 for TVC prediction. This study demonstrated that the electronic tongue together with SVM and SVR has a great potential for a convenient and nondestructive detection of fish freshness.

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Seafood Quality Assessment

Oehlenschläger

2013

Seafood Processing

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Multisensor for fish quality determination

Cited by 248 publications

References 12 publications

A Review on Correlations between Fish Freshness and pH during Cold Storage

A Review on Correlations between Fish Freshness and pH during Cold Storage

A nondestructive method for fish freshness determination with electronic tongue combined with linear and non-linear multivariate algorithms

Seafood Quality Assessment

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