Classification of fresh Atlantic salmon (Salmo salar L.) fillets stored under different atmospheres by hyperspectral imaging

Journal of Food Engineering 109 (2012) 482–489

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Classification of fresh Atlantic salmon (Salmo salar L.) fillets stored under different atmospheres by hyperspectral imaging Izumi Sone a,⇑, Ragnar L. Olsen b, Agnar H. Sivertsen a, Guro Eilertsen a, Karsten Heia a a b

Nofima, P.O. Box 6122, N-9291 Tromsø, Norway Norwegian College of Fishery Science, University of Tromsø, N-9037 Tromsø, Norway

a r t i c l e

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Article history: Received 11 May 2011 Received in revised form 23 September 2011 Accepted 2 November 2011 Available online 11 November 2011 Keywords: Hyperspectral Imaging Salmon Packaging Storage Colour

a b s t r a c t Hyperspectral imaging (HSI) was used to investigate spectroscopic changes in fresh salmon stored under different atmospheres (air, 60% CO2/40% N2 and 90% vacuum) and to determine whether HSI can classify fillets by the type of packaging. Hyperspectral images of samples kept at 4 °C were acquired and bacterial growth and lipid oxidation were measured. Principal component analysis was applied to study spectral development of samples during storage and K nearest-neighbour classifier was used for the classification of fillets by packaging type. Partial least squares regression was run to reduce the number of wavelengths included in the classification model. The results demonstrated that spectral variations could be observed in the different packaging atmospheres primarily at the wavelengths 606 and 636 nm. Using HSI, successful classification of fillets according to the packaging used (>88%) was achieved and this was largely dependent on spectral characteristics at the wavelengths 606 and 636 nm, possibly due to the different oxidation states of the haem proteins in the muscles. Ó 2011 Elsevier Ltd. All rights reserved.

1. Introduction Fresh fish and fishery products are highly perishable (Olafsdóttir et al., 1997). Fish deteriorates during storage as a result of autolysis as well as via the activities of microorganisms (Huss, 1988). The loss of quality at an early stage of fresh fish storage is caused by endogenous enzymes changing biochemical and physical properties through breakdown of nucleotides and structural components of tissues (Aubourg et al., 2007; Delbarre-Ladrat et al., 2006). As storage time proceeds, the number of microorganisms may increase to levels of 107–108 cfu/g. Microbial enzymes and metabolites will eventually cause detectable organoleptic changes characterised by unpleasant odours and flavours as well as textural changes and discolouration (Gram and Dalgaard, 2002; Olafsdottir et al., 2005). To control and prolong freshness, several packaging technologies have been developed for fresh fish and fishery products. Carbon dioxide (CO2) is the most important gas used to replace air due to its bacteriostatic properties. For fatty fish such as salmon, air replacement or vacuum packaging is also useful as it reduces oxidation of the polyunsaturated fatty acids during prolonged storage (Sivertsvik et al., 2002). The colour changes seen during storage may vary according to the packaging used ⇑ Corresponding author. Tel.: +47 77 62 90 14; fax: +47 77 62 90 00. E-mail addresses: izumi.sone@nofima.no (I. Sone), [email protected] (R.L. Olsen), agnar.holten.sivertsen@nofima.no (A.H. Sivertsen), guro.eilertsen@ nofima.no (G. Eilertsen), karsten.heia@nofima.no (K. Heia). 0260-8774/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.jfoodeng.2011.11.001

(Choubert and Baccaunaud, 2006; Hansen et al., 2009; Torrieri et al., 2006). The types of spoilage bacteria limiting the shelf life may also vary with packaging method (Dalgaard et al., 1993). Modern food safety and quality control require rapid and nondestructive methods for monitoring in industrial online production. Use of spectroscopy including hyperspectral imaging systems has been extensively studied and implemented as an alternative to conventional analytical methods which are destructive and timeconsuming. Unlike the traditional spectroscopic methods where spectral data are obtained by placing a probe on a single spot, hyperspectral imaging (HSI) has the advantage of acquiring spectral responses at each pixel of the entire image of the sample, allowing both spectral and spatial analysis (ElMasry et al., 2007). Hyperspectral imaging systems have been used in detection of the external defects in apples (ElMasry et al., 2009; Mehl et al., 2004), citrus fruits (Gómez-Sanchis et al., 2008; Qin et al., 2009), mushrooms (Gowen et al., 2009), poultry (Park et al., 2006) and Atlantic cod (Gadus morhua) (Heia et al., 2007; Stormo et al., 2007). The technology may be applied to determine other quality parameters, such as tenderness of beef (Naganathan et al., 2008), marbling level and the colour of pork meat (Qiao et al., 2007a,b), peach firmness (Lu and Peng, 2006) as well as the moisture content of strawberries (ElMasry et al., 2007) and mushrooms (Taghizadeh et al., 2009). Imaging spectroscopy has also been shown to have potential in the estimation of fat and water distribution in fish fillets (ElMasry and Wold, 2008). Gowen et al. (2008) used HSI to investigate changes in moisture content, colour and texture during

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the storage of sliced mushrooms. Peng et al. (2011) have shown that HSI may be a useful method of predicting microbial growth (total viable count) in beef. In addition, freshness defined as the number of storage days, has recently been estimated in sliced chicken breast (Grau et al., 2010) as well as in cod (Sivertsen et al., 2010) by HSI. Spectral variations that may arise during storage as a result of different packaging methods can be captured by spectroscopy. Taghizadeh et al. (2010) used HSI to demonstrate the effects of different packaging films on the shelf life of mushrooms while Ammor et al. (2009) found that minced beef samples could be differentiated according to the type of packaging by Fourier transform infrared spectroscopy. Recently, Ottestad et al. (2011) used visible/ near infrared spectroscopy to show packaging-dependent changes after six days of storage in fresh salmon and mackerel fillets. The aims of the current work were to use HSI to study spectral changes in fresh salmon fillets stored under different atmospheres and to determine whether HSI can be applied to classify fillets by the type of packaging. 2. Materials and methods 2.1. Sample preparation Farmed Atlantic salmon (Salmo salar L.) were filleted pre-rigor at a commercial fish farm (Lerøy Aurora, Skjervøy, Norway) and arrived at Nofima (Tromsø, Norway) within 6 h post slaughter. The fillets (mean weight 1.60 ± 0.17 kg) were stored on ice during transport and the temperature inside the storage area was maintained at 1 °C. Upon arrival, the loin part of each fillet was cut into skin-on pieces of mean weight 254 ± 7.2 g. Samples were randomly divided into three groups and individually packaged using one of three methods; (1) traditional overwrap packaging (‘‘AIR’’), (2) modified atmosphere with the gas mixture of 60% CO2 and 40% N2 (Yara Praxair, Oslo, Norway) and gas/product ratio 3:1 (‘‘MAP’’), and (3) 90% vacuum (‘‘VAC’’). The AIR and MAP packages were MAPETÒ trays with oxygen transmission rate (OTR) = 100–160 cm3/m2 at 23 °C/0% RH. The volume of each tray was 1025 mL (R. Færch plast AS, Holstebro, Denmark). The vacuum bags were made of 20 lm PA/70 lm PE with OTR = 50 cm3/m2 at 23 °C/75% RH. The size of each bag was 200  270 mm (Maske group AS, Vinterbro, Norway). Each tray and vacuum pouch contained a liquid absorbing pad (Dri-LocÒ absorbent pads, Sealed Air Corp., Epernon Cedex, France) placed as described by Hansen et al. (2009). The AIR packages were wrapped with plastic film with low barrier properties (OTR = 7000 cm3/m2 at 23 °C/0% RH) (Maske group AS). For MAP, air was first evacuated and the gas mixture was introduced into the packages followed by heat sealing (lidding film: TOPSEALÒ PET MAP PB 52, OTR = <3.0 cm3/m2 at 23 °C/0% RH, R. Færch plast AS) on a tray packaging machine (Webomatic Semiautomatic Tray Sealer TL 300, Bochum, Germany). Following packaging, the samples were kept at 4 ± 0.3 °C and evaluated on day 0 (i.e. 12 h after slaughter, 3–4 h after packaging), and at 2, 4, 6, 8, 10, 12, 14 and 16 days post mortem. The exception was the AIR packages which showed apparent spoilage (i.e. unpleasant odour) on day 10 and the sampling was terminated on day 14. At each time point, 6 replicates of each packaging method were analysed. The CO2 and O2 levels inside the MAP packages were measured at each sampling by a CheckMate-3 headspace analyzer (PBI Dansensor, Ringsted, Denmark).

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Bacto Peptone (w/v) (Becton, Dickinson & Company, MD, USA) in a lab blender (Interscience, Saint Nom la Bretèche, France) for 2 min to obtain a 1:5 dilution. Total bacterial count (TBC) was determined on iron agar (Iron Agar Lyngby, CM 964, Oxoid, Basingstoke, UK) using the spread plate method followed by incubation at 12 °C for 4 days. The mean of duplicate measurements was expressed as log10 of colony forming units per gram of fish muscle (log cfu/g). Lipid oxidation measured as thiobarbituric acid-reactive substances (TBARS) values were determined according to Sivertsen et al. (2006). 2.3. Hyperspectral interactance imaging Following the microbiological analysis, a hyperspectral image in the interactance mode was obtained for each sample as described by Sivertsen et al. (2010). The imaging system (Fig. 1) consisted of an imaging spectrometer (VNIR-640, Norsk Elektro Optikk, N-1497, Norway), two lines of custom made fibre optical light with focusing acryl lenses, a white diffuse conveyer belt and two black aluminium screens for light baffling. The conveyer belt ran at the standard industrial speed of 40 cm/s. The spectrometer was placed 1030 mm above the conveyer belt and had a focal distance of 1000 mm and depth of field of 25 mm. Three 150 W (21VDC) halogen lamps each comprised of a 200 mm long fibre optic light line were situated on both sides of the imaging area. The fibre lines were positioned 150 mm above the conveyer belt and the width of each light line projected onto the belt was 10 mm. The spectrophotometer had a field of view of 0.5  320 mm, which was 20 mm apart from and ran parallel to the centre of the projected light lines. The light in this region was recorded in one frame by the CCD in the spectrometer and represented as 64 spectra, each with 64 spectral variables. Individual spectra represented light intensity from a spatial area of 0.5  1.0 mm in the region of 400–1100 nm, with a spectral resolution of about 10 nm. Each sample was scanned line by line at 400 frames per s while moving through the spectrophotometer field of view. The data acquired was recorded as a hyperspectral image Ri(k, x, y) consisting of successive frames, F(k, x). At the start of each sampling day, a Teflon target (300  300  25 mm) was scanned and used for calibrating the imaging system. One hundred successive frames recorded from the Teflon target were used to obtain the average reference frame Ra(k, x) and the interactance image was calculated as I(k, x, y) = Ri(k, x, y)/Ra(k, x). The interactance images were then exported to Interactive Data Language (IDL) 7.1 (ITT Visual Information Solutions, Boulder, USA).

2.2. Bacterial plate counting and lipid oxidation Samples of 10 g were aseptically removed from one side of each salmon fillet and homogenised with 0.9% NaCl (w/v) and 0.1%

Fig. 1. Interactance setup for hyperspectral imaging from Sivertsen et al. (2010).

I. Sone et al. / Journal of Food Engineering 109 (2012) 482–489

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2.2 ± 0.4 3.4 ± 0.1 4.8 ± 0.4 6.5 ± 0.3 8.3 ± 0.3 9.2 ± 0.5 9.2 ± 0.2 9.3 ± 0.1

2.5 ± 0.2 2.7 ± 0.6 2.8 ± 0.3 3.1 ± 0.2 3.9 ± 0.2 5.3 ± 0.4 5.7 ± 0.4 7.0 ± 0.5 7.3 ± 0.4

2.3 ± 0.1 2.8 ± 0.5 3.5 ± 0.4 4.4 ± 0.5 5.8 ± 0.2 6.9 ± 0.3 7.4 ± 0.2 7.7 ± 0.1 8.0 ± 0.3

TBARS (nmol/g) 0 2 4 6 8 10 12 14 16

2.5 ± 0.7 3.0 ± 0.4 2.5 ± 0.5 3.6 ± 0.5 4.5 ± 0.6 6.9 ± 1.3 6.2 ± 0.7 5.9 ± 2.9

2.6 ± 0.8 3.0 ± 0.6 3.1 ± 0.3 3.0 ± 0.4 3.4 ± 0.5 3.0 ± 0.1 3.4 ± 0.3 3.5 ± 0.9 3.4 ± 0.7

2.3 ± 0.6 3.2 ± 0.3 2.7 ± 0.5 3.0 ± 0.6 3.2 ± 0.3 2.9 ± 0.4 3.0 ± 0.3 2.7 ± 0.5 3.3 ± 1.4

2.4. Processing of hyperspectral data On the interactance image of each sample, a region of interest (ROI) was defined in IDL. The ROI was selected to include as much area as possible of the salmon fillet, while avoiding possible interference from the edge of the samples and the area of the incision acquired for the microbiological analysis. From the defined region, non-overlapping circular areas consisting of 81 pixels (40 mm2) were randomly selected and a mean spectrum was calculated from the spectra in each area. Spectral pre-treatment in the form of Standard Normal Variate (SNV) was performed on the obtained spectra using Unscrambler version 9.8 (CAMO, Oslo, Norway) (Sivertsen et al., 2010). 2.5. Classification Principal component analysis (PCA) was developed in Unscrambler to investigate changes occurring in the spectral characteristics of samples stored under different atmospheres. Classification was performed in IDL using the K nearest-neighbour classifier (Knn) (Theodoridis and Koutroumbas, 1998) with the Euclidian distance and three neighbours. Following the pre-treatment by SNV, 90% of the samples in each group were randomly selected and used to create a prototype to classify the remaining 10% of each group by the type of atmosphere packaging used during storage. Classification by Knn was performed excluding day 0 from the prototype and the test set, since no difference between the groups was expected on that day. The mean and standard deviation of the correct classification rate was obtained by running Knn 500 times. In addition, Fisher transformation was applied to the SNV pre-treated data in IDL (Theodoridis and Koutroumbas, 1998) and tested for the classification by Knn. In order to reduce the number of features (wavelengths) used for the classification, partial least squares regression (PLS) was developed in Unscrambler. Two of the three groups of samples were selected each time and included in PLS (i.e. AIR and MAP, AIR and VAC and MAP and VAC). The response variable for the AIR samples was defined as +1 while a value of 1 was given to the response variable for MAP and VAC when running PLS with AIR. In PLS with MAP and VAC, each MAP sample was assigned a y value of +1 and the VAC samples 1. Samples from days 0 and 2 were excluded. The weighed beta coefficients obtained by divid-

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Table 1 The mean values of total bacterial count (TBC) and lipid oxidation (TBARS) ± standard deviation for the AIR, MAP and VAC samples.

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Fig. 2. Mean spectra of the AIR (solid), MAP (dotted) and VAC (dashed) samples on day 0 (a) and day 4 (b). The interactance spectra were natural log transformed to the absorbance A(k, x, y) = ln I(k, x, y) and pre-treated by SNV.

ing each variable (wavelength) by its standard deviation were used to identify relevant wavelengths for separating the groups. 3. Results and discussion 3.1. Spoilage of the samples Spoilage patterns of fillets stored under different atmospheres varied during storage, as shown by the total bacterial count (TBC) and lipid oxidation (TBARS) (Table 1). The number of microorganisms increased rapidly in the AIR samples and TBC was determined to be 8.3 log cfu/g on day 8, indicating spoilage (Gram and Dalgaard, 2002). The MAP and VAC samples had approximately 4 and 2 log cfu/g lower TBC at this time of storage. Lipid oxidation increased for the AIR samples during storage while the other two groups showed little change in TBARS confirming the reduced exposure to oxygen in the MAP and VAC samples. The O2 content in the MAP packages remained below 0.1% (0.05 ± 0.02%) throughout the storage period. 3.2. Spectral characteristics The peak centred at 500 nm in the interactance spectra (Fig. 2a) is probably due to astaxanthin absorption (Rønsholdt and McLean, 2001) and the shoulder at 606 and 754 nm as well as the peak around 981 nm are associated with the absorption by water (Pope and Fry, 1997; Sivertsen et al., 2010). Little difference can be seen

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Fig. 3a. PCA score plots on days 0, 2, 4, 6 and 8. The AIR, MAP and VAC samples are shown as square, filled circle and triangle, respectively. PCA was run including all samples from the entire storage period, but each plot shows only those belonging to the respective storage day.

ently during storage. Moreover, the largest spectral variations in the different packaging atmospheres appeared primarily at the wavelengths 606 and 636 nm.

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Fig. 3b. PCA loading weights on day 8. The explained variance was 51% (the first PC in dotted line) and 31% (the second PC in solid line).

between the mean spectra of the AIR, MAP and VAC samples on day 0 (Fig. 2a), but the spectra of the three groups are clearly different on day 4 (Fig. 2b). The major differences in the three mean spectra on day 4 are observed at wavelengths centred at 606 and 636 nm. Using PCA (Fig. 3a) samples stored in air could be distinguished from MAP and VAC on day 4, although changes in spectral characteristics appeared on day 2 possibly due to the differences in biochemical or physical changes occurring in the samples (Sone et al., 2011). The distinction between the MAP and VAC samples also became more apparent on days 6 and 8. The AIR, MAP and VAC samples are separated along the second principal component (PC2) on days 4, 6 and 8 (Fig. 3a). The largest spectral variations in the direction of PC2 occur at 606 and 636 nm where the peak centred at 606 nm is negatively correlated with that at 636 nm (Fig. 3b). The results demonstrated that spectral characteristics of salmon fillets stored under different atmospheres developed differ-

Classification by Knn was performed using the SNV pre-treated spectra with and without the Fisher transformation. When all of the 64 spectral variables were included in the classification and the Fisher transformation was not used, the rate of correct classification was 75.7 ± 5.5%. The day 2 samples were then excluded from the classification and Knn was run again to see whether the classification performance improved, as the distinction between the three groups was not yet clear at this storage time (Fig. 3a). As a result the classification rate increased to 79.4 ± 5.1%. When the SNV pre-treated spectra were Fisher transformed, Knn was initially able to classify 72.6 ± 5.6% of the test samples and the classification improved to 75.2 ± 5.5% when the day 2 samples were excluded. To reduce the number of wavelengths included in the classification model, different sets of wavelengths with high beta coefficients were tested for the classification by Knn. The best classification result was achieved when using five single wavelengths at 606, 636, 665, 705, and 764 nm (Figs. 4a–c) and Knn was run without the Fisher transformation. The rate of correct classification was 82.1 ± 4.5% and it improved to 88.3 ± 4.5% when excluding day 2. Fisher transformation followed by Knn gave the correct classification rate of 70.9 ± 5.3% and the classification accuracy improved to 78.6 ± 5.5% after excluding day 2. The two wavelengths at 606 and 636 nm could alone correctly classify 69.4 ± 5.9% of the test samples when classification was performed without the Fisher transformation and day 2. The results obtained established the potential for HSI to classify fresh salmon fillets by packaging type. Moreover, the significance of spectral changes occurring at the wavelengths at 606 and 636 nm for the classification has been demonstrated.

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Fig. 4b. The weighed beta coefficients for the first PC in PLS with the assigned reference value +1 for AIR and

3.4. Packaging-dependent spectral changes Four of the five wavelengths selected for the classification (606, 636, 665, 705, and 764 nm) fall in the visible region of the spectrum. The visible region has previously been reported to contain important variables for detecting and predicting quality changes during storage (Liu et al., 2004; Nilsen and Esaiassen, 2005; Nilsen et al., 2002; Sivertsen et al., 2010). The results in this study indicate that changes occurring in spectral characteristics in the visible region also contributed greatly to the classification of fresh salmon fillets by packaging type. Sivertsen et al. (2010) suggested that oxidation of the haem pigments such as haemoglobin (Hb) and myoglobin (Mb) may be detected and explain most spectral variation in the visible region of the spectrum during storage of fresh and frozen cod. Intracellular Mb is usually responsible for the colour of muscle based foods while Hb in the blood may be easily lost during processing (Hui et al., 2006; Pérez-Alvarez and Fernández-López, 2006). Possible effects of Mb oxidation on colour have been investigated exten-

1 for VAC.

sively for meat and poultry as well as for fish such as tuna, sardine and mackerel (Chaijan et al., 2005; Lopez-Galvez et al., 1995; Mancini and Hunt, 2005; Nakamura et al., 2007; Saucier et al., 2000). However, Richards and Hultin (2002) found that the amount of residual Hb in rainbow trout was more substantial than Mb. Several studies have also shown that Hb may affect the colour of fish muscle through oxidation during storage (Richards et al., 2002; Wetterskog and Undeland, 2004). For astaxanthin-pigmented fish like salmon, it has been assumed that due to the anaerobic nature of fish light muscle, the amount of the haem proteins in the muscle is small and absorption is low compared to absorption by astaxanthin. However, recent studies have suggested that they may contribute to the colour changes of fresh salmon during storage. Bjørlykke et al. (2011) observed a significant increase in redness of CO-treated salmon fillets at 10 days post mortem, presumably as a result of the cherry-red colour of haemoglobin bound to CO (carboxyhaemoglobin). Visible/near infrared spectra of fresh salmon and mackerel obtained after 6 days of storage in carbon monoxide, vacuum and air

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showed packaging-dependent changes that may be attributed to the haem pigments in different oxidation states (Ottestad et al., 2011). In addition, in this study it is possible that the haem proteins in the samples may have reacted differently depending on the atmospheres and influenced spectral development of salmon fillets during storage. As a result different spectral features may have appeared in the samples stored under different atmospheres and this may have permitted the successful classification of fillets by packaging type. The line plot on day 4 (Fig. 2b), the PCA loading on day 8 (Fig. 3b) as well as the results in the classification give a strong indication that such packaging-dependent spectral variations in the samples may have appeared primarily at the wavelengths at 606 and 636 nm. Based on the PCA loading (Fig. 3b) and the weighed beta coefficients in PLS (Figs. 4a–c) the two wavelengths at 606 and 636 nm are negatively correlated (Figs. 4a–c). A similar pattern of negative correlation between the two wavelengths was also observed in PLS developed to predict freshness of air stored cod (Sivertsen et al., 2010). This suggests that spectral characteristics occurring at the two wavelengths could not be related to the chemistry of astaxanthin. Absorption at the wavelengths around 636 nm has been associated with the oxidised form of Hb (methaemoglobin; metHb) (Olsen and Elvevoll, 2011; Zijlstra and Buursma, 1997) and the oxidised form of Mb (metmyoglobin; metMb) (Brown et al., 1962; Millar et al., 1996). An increase in the absorption intensity at this wavelength was also reported during storage of tuna (Thunnus thynnus and T. obesus) (Viriyarattanasak et al., 2008). Changes in the absorption characteristics of air stored cod (Sivertsen et al., 2010), fresh salmon and mackerel under modified atmosphere (Ottestad et al., 2011) have been observed at the wavelength 606 nm. Absorption at 606 nm does not correspond well with that of the haem proteins. Sivertsen et al. (2010) suggested that this may be related to a greater amount of oxygen bound to haemoglobin in fresher samples. Oxygen-bound Hb has a lower absorption at around 600 nm. Consequently the water absorption shoulder at 606 nm may become more visible. Ottestad et al. (2011) observed that the absorption intensity at this wavelength was dependent on the packaging method and represented a large part of the spectral variations during storage. The authors speculated that spectral changes occurring at this wavelength could be linked to a breakdown product of haem with an intact porphyrin-like structure. The results of their work suggest that spectral variations observed at 606 nm may reflect structural and

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physicochemical changes occurring in the haem proteins as a result of the oxidation during storage. In the interactance spectra (Fig. 2b), the absorption at 636 nm is greater for the AIR samples than for the VAC and MAP samples on day 4, which may have reflected the more extensive formation of oxidised haem proteins in the AIR samples compared to the other two groups. At the time of packaging, the Hb and Mb of salmon fillets may have been in constant interconversion where Hb and Mb were being oxygenated and deoxygenated again during reversible oxygen binding in air and eventually oxidised to metHb and metMb. The oxidised haem can be reduced back to the deoxy forms through enzyme-mediated reactions (Shikama, 1998). However, this ability decays with storage due to lack of reduced cofactors while the oxidation persists, progressively replacing the deoxyand oxy-Hb and -Mb with their met forms. With time, the brown met forms of haem become dominant and may lead to colour changes (Chaijan et al., 2005; Wetterskog and Undeland, 2004). The lipid oxidation and the rapid bacterial growth observed in the AIR samples (Table 1) may also explain the increase in the absorption intensity at 636 nm on day 4 (Fig. 2b). The primary and secondary byproducts of lipid oxidation have been shown to accelerate oxidation of the haem pigments (Faustman et al., 2010; Lee et al., 2003; Maestre et al., 2009). Aerobic microorganisms found dominantly in air stored samples may also reduce the oxygen partial pressure on the surface by depleting oxygen through their metabolic activities (Chan et al., 1998; Robach and Costilow, 1961). Such conditions may induce an increased concentration of the unstable deoxy-species and eventually accelerate oxidation (Shikama, 1998). Similarly, the low oxygen partial pressure in the vacuum bags (10% air, i.e. 2% oxygen at the time of packaging) may also have promoted the production of metHb and metMb in the VAC samples compared to the anaerobic MAP packaging. The air left in the VAC samples may have been converted to CO2 during storage (Lopez-Lorenzo et al., 1980), but the oxidation-induced discolouration has been reported in beef and lamb with an oxygen concentration as low as 0.15% in the presence of CO2 (Penney and Bell, 1993).

4. Conclusions Using HSI, this study demonstrated that spectra of fresh salmon fillets stored in air, in 60% CO2/40% N2 and in 90% vacuum devel-

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