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Mont-Saint-Aignan, France

Balaban M.O.,University of Alaska Fairbanks | Chombeau M.,Esitpa, School of Agricultural Engineering | Cirban D.,Izmir Institute of Technology | Gumus B.,Akdeniz University
Journal of Food Science | Year: 2010

Determining the size and quality attributes of fish by machine vision is gaining acceptance and increasing use in the seafood industry. Objectivity, speed, and record keeping are advantages in using this method. The objective of this work was to develop the mathematical correlations to predict the weight of whole Alaskan Pollock (Theragra chalcogramma) based on its view area from a camera. One hundred and sixty whole Pollock were obtained fresh, within 2 d after catch from a Kodiak, Alaska, processing plant. The fish were first weighed, then placed in a light box equipped with a Nikon D200 digital camera. A reference square of known surface area was placed by the fish. The obtained image was analyzed to calculate the view area of each fish. The following equations were used to fit the view area (X) compared with weight (Y) data: linear, power, and 2nd-order polynomial. The power fit (Y = A·X B) gave the highest R 2 for the fit (0.99). The effect of fins and tail on the accuracy of the weight prediction using view area were evaluated. Removing fins and tails did not improve prediction accuracy. Machine vision can accurately predict the weight of whole Pollock. © 2010 Institute of Food Technologists ®. Source


Bouzanquet Q.,Esitpa, School of Agricultural Engineering | Bouzanquet Q.,Charles Sturt University | Barril C.,Charles Sturt University | Clark A.C.,Charles Sturt University | And 3 more authors.
Journal of Agricultural and Food Chemistry | Year: 2012

This study characterizes a novel glutathione-substituted dihydroxyphenyl compound formed during the oxidation of white wine and model wine solutions, which may contribute to the synergistic role of glutathione and hydroxycinnamic acids in delaying oxidative coloration. The critical components for the formation of the compound were found to be hydroxycinnamic acids and glutathione, while ascorbic acid enabled the product to accumulate to higher concentrations. The presence of the wine components important in other wine oxidation mechanisms, (+)-catechin, ethanol and/or tartaric acid, was not essential for the formation of this new compound. Via LC-MS/MS, HR-MS and 1H NMR (1D and 2D NMR) analyses, the major isomer of the compound formed from glutathione and caffeic acid was found to be 4-[(E)-2 2-(S)-glutathionyl ethenyl]-catechol (GEC). Equivalent products were also confirmed via LC-MS/MS for other hydroxycinnamic acids (i.e., ferulic and coumaric acids). Only trace amounts of GEC were formed with the quinic ester of caffeic acid (i.e., chlorogenic acid), and no equivalent product was found for cinnamic acid. GEC was detected in a variety of white wines supplemented with glutathione and caffeic acid. A radical mechanism for the formation of the styrene-glutathione derivatives is proposed. © 2012 American Chemical Society. Source


Dupont L.,University Paris Est Creteil | Gresille Y.,University Paris Est Creteil | Richard B.,CNRS Biodiversity Studies Laboratory | Richard B.,Esitpa, School of Agricultural Engineering | And 3 more authors.
Biological Journal of the Linnean Society | Year: 2015

The limited dispersal ability of earthworms is expected to result in marked genetic isolation by distance and remarkable spatial patterns of genetic variation. To test this hypothesis, we investigated, using microsatellite loci, the spatial genetic structure of two earthworm species, Allolobophora chlorotica and Aporrectodea icterica, in two plots of less than 1ha where a total of 282 individuals were collected. We used spatial autocorrelation statistics, partial Mantel tests of isolation-by-distance (IBD) and isolation-by-resistance (IBR), and Bayesian test of clustering to explore recent patterns involved in the observed genetic structure. For A.icterica, a low signal of genetic structure was detected, which may be explained by an important dispersal capacity and/or by the low polymorphism of the microsatellite loci. For A.chlorotica, a weak, but significant, pattern of IBD associated with positive autocorrelation was observed in one of the plots. In the other plot, which had been recently ploughed, two genetically differentiated clusters were identified. These results suggest a spatial neighbourhood structure in A.chlorotica, with neighbour individuals that tend to be more genetically similar to one another, and also highlight that habitat perturbation as a result of human activities may deeply alter the genetic structure of earthworm species, even at a very small scale. © 2015 The Linnean Society of London, Biological Journal of the Linnean Society, 2015, 114, 335-347. Source


Balaban M.O.,University of Alaska Fairbanks | Chombeau M.,Esitpa, School of Agricultural Engineering | Gumus B.,Akdeniz University | Cirban D.,Izmir Institute of Technology
Journal of Aquatic Food Product Technology | Year: 2011

The objective of this study was to develop two methods to predict the volume of whole Alaska pollock and to compare the results with the experimentally measured volumes. One hundred fifty-five whole pollock, obtained from a Kodiak processor, were individually immersed in a graduated cylinder equipped with an outflow tube to catch the displaced water as a result of immersion. The weight of the water was recorded. Then the fish were placed in a light box equipped with a digital video camera, and the side view and top view recorded (2 images for each fish). A reference square of known surface area was placed by the fish. A cubic spline method to predict volume by integration of cross-sectional area slices based on the top and side views and an empirical equation using dimensional (length L, width W, depth D) measurements at three locations of the fish image were developed. The R 2 value for the correlation between the L × W × D versus measured volume was 0.987. The best R 2 for the correlation of the predicted volume by the cubic spline method versus the measured volume was 0.99. Image analysis can be used reliably to predict the volume of whole Alaska pollock. © Taylor & Francis Group, LLC. Source


Balaban M.O.,University of Auckland | Chombeau M.,Esitpa, School of Agricultural Engineering | Gumus B.,Akdeniz University | Crban D.,Izmir Institute of Technology
Journal of Aquatic Food Product Technology | Year: 2012

Roe is an important product of the Alaska pollock (Theragra chalcogramma) industry. About 31% of the value for all pollock products comes from roe, yet roe is 5% of the weight of the fish. Currently, the size (weight), color, and maturity of the roe are subjectively evaluated. The objective of this study was to develop methods to predict the weight of Alaska pollock roe based on its view area from a camera and to differentiate between single and double roes. One hundred and forty-two pollock roes were picked from a processing line in a Kodiak, AK plant. Each roe was weighed, placed in a light box equipped with a digital video camera, images were taken at two different angles from one side, then turned over and presented at two different angles again (four images for each roe). A reference square of known surface area was placed by the roe. The following equations were used to fit the view area (X) versus weight (Y) data: linear, power, and second-order polynomial. Error rates for the classification of roes by weight decreased significantly when weight prediction equations for single and double roes were developed separately. A turn angle method, a box method, and a modified box method were tested to differentiate single and double roes by image analysis. Machine vision can accurately determine the weight of pollock roe. Practical Application Abstract: An image analysis method to accurately determine if pollock roe is a single or a double was developed. Then view area versus weight correlations were found for single and double roes that reduced incorrect weight classification rates to half that of human graders. © 2012 Copyright Taylor and Francis Group, LLC. Source

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