Freshness assessment of gilthead sea bream (Sparus aurata) by machine vision based on gill and eye color changes

Abstract The fish freshness was evaluated using machine vision technique through color changes of eyes and gills of farmed and wild gilthead sea bream ( Sparus aurata ), being employed lightness ( L * ), redness ( a * ), yellowness ( b * ), chroma ( c * ), and total color difference (Δ E ) parameters during fish ice storage. A digital color imaging system, calibrated to provide accurate CIELAB color measurements, was employed to record the visual characteristics of eyes and gills. The region of interest was automatically selected using a computer program developed in MATLAB software. L * , b * , and Δ E of eyes increased with storage time, while c * decreased. The a * parameter of fish eyes did not show clear a trend with storage time. The L * , b * , and Δ E of fish gills increased with storage time, but a * and c * decreased. Regression analysis and artificial neural networks approaches were used to correlate the eyes and gills color parameters with the time of storage and a strong correlation was found between color parameters and storage day. Gills color changes were more precise than those found for eyes in order to evaluate the fish freshness. However, the gills cover should be removed for taking the images and thus, the method is destructive and time-consuming. Therefore, the color parameters of fish eyes can be used as a green, low cost and easy method for fast and on-line assessing of fish freshness in food industry.

[1]  M. Synnes,et al.  Fatty acid and lipid class composition in eyes and brain from teleosts and elasmobranchs. , 2004, Comparative biochemistry and physiology. Part B, Biochemistry & molecular biology.

[2]  F. Toldrá,et al.  Freshness monitoring of sea bream (Sparus aurata) with a potentiometric sensor. , 2008, Food chemistry.

[3]  E. Márquez‐Ríos,et al.  Postmortem changes in cazon fish muscle stored on ice , 2009 .

[4]  M. Richards,et al.  Changes in heme proteins and lipids associated with off-odour of seabass (Lates calcarifer) and red tilapia (Oreochromis mossambicus × O. niloticus) during iced storage , 2010 .

[5]  Lars Helge Stien,et al.  Image analysis as a tool to quantify rigor contraction in pre-rigor-filleted fillets , 2006 .

[6]  Franco Pedreschi,et al.  Color of Salmon Fillets By Computer Vision and Sensory Panel , 2010 .

[7]  R. Schubring Determination of fish freshness by instrumental colour measurement , 1999 .

[8]  A. Imsland,et al.  Exsanguination of turbot and the effect on fillet quality measured mechanically, by sensory evaluation, and with computer vision. , 2007, Journal of food science.

[9]  J. B. Luten,et al.  Colour measurement on skin during storage of wet and frozen fish. , 2003 .

[10]  Bruce A. Welt,et al.  Comparison of Minolta colorimeter and machine vision system in measuring colour of irradiated Atlantic salmon. , 2009 .

[11]  N. Haard,et al.  Control of chemical composition and food quality attributes of cultured fish , 1992 .

[12]  E Misimi,et al.  Quality grading of Atlantic salmon (Salmo salar) by computer vision. , 2008, Journal of food science.

[13]  Mortaza Aghbashlo,et al.  The use of artificial neural network to predict exergetic performance of spray drying process: A preliminary study , 2012 .

[14]  M. Szczepkowski,et al.  A comparison of selected quality features of the tissue and slaughter yield of wild and cultivated pikeperch Sander lucioperca (L.) , 2003 .

[15]  Y. Wang,et al.  Application of atomic force microscopy on rapid determination of microorganisms for food safety. , 2008, Journal of food science.

[16]  Murat O. Balaban,et al.  Quality Evaluation of Raw and Cooked Catfish (Ictalurus punctatus) Using Electronic Nose and Machine Vision , 2001 .

[17]  G. Flick,et al.  Composition of farmed and wild yellow perch (Perca flavescens) , 2006 .

[18]  Murat O. Balaban,et al.  Objective Quality Assessment of Raw Tilapia (Oreochromis niloticus) Fillets Using Electronic Nose and Machine Vision , 2001 .

[19]  S. Kaushik,et al.  Effect of long-term feeding with a plant protein mixture based diet on growth and body/fillet quality traits of large rainbow trout (Oncorhynchus mykiss) , 2004 .

[20]  J. Aguilera,et al.  Computer Vision and Stereoscopy for Estimating Firmness in the Salmon (Salmon salar) Fillets , 2010 .

[21]  Bruce A. Welt,et al.  Correlation between astaxanthin amount and a* value in fresh Atlantic salmon (Salmo salar) muscle during different irradiation doses , 2010 .

[22]  Mortaza Aghbashlo,et al.  Optimization of an Artificial Neural Network Topology for Predicting Drying Kinetics of Carrot Cubes Using Combined Response Surface and Genetic Algorithm , 2011 .

[23]  K. Miyashita,et al.  Handbook of seafood quality, safety and health applications. , 2010 .

[24]  E. Dickinson,et al.  Structural and rheological properties of aerated high sugar systems containing egg albumen , 2006 .

[25]  Achim Kohler,et al.  Sorting salted cod fillets by computer vision , 2002 .

[26]  T. Dinçer,et al.  Comparison of Effects of Slurry Ice and Flake Ice Pretreatments on The Quality of Aquacultured Sea Bream Sparus aurata and Sea Bass Dicentrarchus labrax stored at 4 C , 2007 .

[27]  Harry T. Lawless,et al.  Sensory Evaluation of Food: Principles and Practices , 1998 .

[28]  M. Nunes,et al.  Sensory analysis to assess the freshness of Mediterranean anchovies (Engraulis encrasicholus) stored in ice , 2006 .

[29]  Seyed Saeid Mohtasebi,et al.  Application of machine-vision techniques to fish-quality assessment , 2012 .

[30]  Soleiman Hosseinpour,et al.  Application of computer vision technique for on-line monitoring of shrimp color changes during drying , 2013 .

[31]  S. Aubourg,et al.  Lipid hydrolysis and oxidation in farmed gilthead seabream (Sparus aurata) slaughtered and chilled under different icing conditions , 2010 .

[32]  Bruce A. Welt,et al.  Effect of high pressure processing and cooking treatment on the quality of Atlantic salmon , 2009 .

[33]  Alberto García,et al.  Quality analysis of tuna meat using an automated color inspection system , 2006 .

[34]  Ø. Lie Flesh quality – the role of nutrition , 2001 .

[35]  R. S. Rasmussen Quality of farmed salmonids with emphasis on proximate composition, yield and sensory characteristics , 2001 .

[36]  E Misimi,et al.  Atlantic salmon skin and fillet color changes effected by perimortem handling stress, rigor mortis, and ice storage. , 2008, Journal of food science.

[37]  José Miguel Aguilera,et al.  An application of image analysis to dehydration of apple discs , 2005 .

[38]  Jean Ponce,et al.  Computer Vision: A Modern Approach , 2002 .

[39]  E Misimi,et al.  Computer vision-based sorting of Atlantic salmon (Salmo salar) fillets according to their color level. , 2007, Journal of food science.

[40]  Eric A. Decker,et al.  The effect of metal ions on lipid oxidation, colour and physicochemical properties of cuttlefish (Sepia pharaonis) subjected to multiple freeze–thaw cycles , 2006 .

[41]  Da-Wen Sun,et al.  Improving quality inspection of food products by computer vision: a review , 2004 .

[42]  M. O. Balaban,et al.  COMPARISON OF A COLORIMETER WITH A MACHINE VISION SYSTEM IN MEASURING COLOR OF GULF OF MEXICO STURGEON FILLETS , 2006 .

[43]  Mahmoud Omid,et al.  Prediction of Energy and Exergy of Carrot Cubes in a Fluidized Bed Dryer by Artificial Neural Networks , 2011 .

[44]  Brown,et al.  Evaluation of fish-meal free diets for rainbow trout, Oncorhynchus mykiss , 1998 .

[45]  Murat O. Balaban,et al.  Evaluation of Color Parameters in a Machine Vision Analysis of Carbon Monoxide-Treated Fish—Part I , 2005 .

[46]  R. Chou,et al.  Substituting fish meal with soybean meal in diets of juvenile cobia Rachycentron canadum , 2004 .

[47]  T. Dinçer,et al.  Effect of ungutting on microbiological, chemical and sensory properties of aquacultured sea bream (Sparus aurata) and sea bass (Dicentrarchus labrax) stored in ice , 2006 .

[48]  P. Masniyom Deterioration and shelf-life extension of fish and fishery products by modified atmosphere packaging , 2011 .

[49]  D. Mery,et al.  Color measurement in L ¿ a ¿ b ¿ units from RGB digital images , 2006 .

[50]  M. Garrido,et al.  Sensory, physical, chemical and microbiological changes in aquacultured meagre (Argyrosomus regius) fillets during ice storage , 2009 .

[51]  Antonella Macagnano,et al.  Multisensor for fish quality determination , 2004 .

[52]  T. Dinçer,et al.  Effects of Using Slurry Ice During Transportation on the Microbiological, Chemical, and Sensory Assessments of Aquacultured Sea Bass (Dicentrarchus Labrax) Stored at 4°C , 2006, Critical reviews in food science and nutrition.

[53]  M. de la Guardia,et al.  Green Analytical Chemistry , 2008 .