Non-destructive Visible/NIR Spectroscopy for Differentiation of Fresh and Frozen-thawed Fish

Nondestructive visible/near‐infrared (NIR) spectroscopy was evaluated to investigate whether fish has been frozen‐thawed. Fresh or frozen‐thawed red sea bream Pagrus major (n= 108) were scanned using a NIRSystems 6500 spectrophotometer equipped with a surface interactance fiber‐optic accessory then discriminated by soft independent modeling of class analogy (SIMCA) and linear discriminant analysis (LDA) based on principal component analysis (PCA) scores. The major effect of freeze‐thawing treatment involves a gross change in total reflectance after freezing and thawing; this arises from changes in light scatter presumably arising from alterations in the physical structure of at least the surface layer of fish. Untreated original absorbance spectra achieved much better (100%) classification accuracy for the prediction samples while the same figures for multiplicative scatter correction (MSC) treated spectra are considerably worse, indicating that scattering is the major information that makes classification work. No incorrect type of classification at all and also there are no samples classified to both groups either. This faster technique has the potential to differentiate fresh and frozen‐thawed fish and could be applied for online or at‐line processing control.     

Differentiation of Frozen and Unfrozen Beef Using Near-Infrared Spectroscopy

Freezing and thawing affects the quality of meat. The present paper focuses on using near-infrared (NIR) diffuse reflectance spectroscopy to detect whether beef has been frozen and thawed. Intact beef and drip or centrifuged meat juice of M longissimus dorsi slices from 40 cattle were used as samples. The meat juices were analysed using dry extract spectroscopy by infrared reflection (DESIR). From centrifuged juice 80 samples were classified 100% correctly, using crossvalidation, into frozen or unfrozen beef by the K nearest neighbours method. This was obtained by high-order principal components from 400–2500 nm spectra. Other multivariate techniques, smaller wavelength ranges and detecting refrozen, thawed beef also gave results between 90 and 100%. Analyses of drip loss, exudative properties, water-holding capacity and dry matter of meat juice supported the interpretation of the NIR measurements. The results showed that NIR might be used as a screening method to differentiate unfrozen and frozen beef. © 1997 SCI.     

Near‐infrared reflectance spectroscopy for determining end‐point temperature of heated fish and shellfish meats

Attempts have been made to assess the end‐point temperature (EPT) of heated fish and shellfish meats by near‐infrared (NIR) reflectance spectroscopy. Since the presence of water affects NIR spectra, the influence of the water content of samples on the performance of NIR spectroscopy for determining EPT was also evaluated. Blue marlin (Makaira mazara), skipjack (Katsuwonus pelamis), red sea bream (Pagrus major), kuruma prawn (Penaeus japonicus) and scallop (Patinopecten yessoensis) meats were heat‐treated at different temperatures (5 °C intervals between 60 and 100 °C). NIR spectra were measured at 2 nm intervals between 1100 and 2500 nm. A stepwise multiple linear regression method was used to develop a calibration curve. Changes in NIR reflectance spectra upon heat treatment were related to the heating temperature. Moreover, the interference from the variation in water content on the prediction of EPT was eliminated by selecting appropriate wavelengths. Plotting of NIR‐predicted temperatures determined from d² log(1/R) at four specific wavelengths against the actual EPT revealed a promising linear relationship with correlation coefficients between 0.94 and 0.98. In the temperature range 60–100 °C, NIR reflectance spectroscopy was able to detect EPT of heated fish and shellfish meats with a prediction error of 1.9–3.1%. © 2002 Society of Chemical Industry     

Utilisation of a rapid technique based on front-face fluorescence spectroscopy for differentiating between fresh and frozen–thawed fish fillets

The potential of front-face fluorescence spectroscopy combined with chemometric tools was investigated to differentiate frozen–thawed from fresh fish. A total of 24 fish fillets, i.e., 12 fresh samples and 12 frozen–thawed samples, were investigated. Regarding the frozen–thawed samples, two speeds of freezing and thawing were tested (fast and slow) and for each condition, three whiting fillets were analysed. The fluorescence emission spectra of tryptophan (excitation: 290 nm, emission: 305–400 nm) and nicotinamide adenine dinucleotide (NADH) (excitation: 340 nm, emission: 360–570 nm) were recorded directly on samples. In a first step, the principal component analysis (PCA) was applied separately to the tryptophan or NADH fluorescence spectra. From the NADH spectra, PCA results showed a good discrimination between fresh and frozen–thawed fish samples. But it was not the case with the tryptophan fluorescence spectra. In a second step, factorial discriminant analysis (FDA) was applied to the first five principal components (PCs) of the PCA performed on the two data sets. Considering tryptophan fluorescence spectra, correct classification was observed for 62.5% and 70.8% of the calibration and validation spectra, respectively. A better classification was obtained from NADH fluorescence spectra since 100% correct classifications were obtained for the calibration and validation spectra. It was concluded that NADH fluorescence spectra may be considered as a promising probe for the reliable differentiation between frozen–thawed and fresh fish.     

Application of Visible and Near Infrared Hyperspectral Imaging to Differentiate Between Fresh and Frozen–Thawed Fish Fillets

The potential of visible and near infrared (VIS/NIR) hyperspectral imaging was investigated as a rapid and nondestructive technique to determine whether fish has been frozen–thawed. A total of 108 halibut (Psetta maxima) fillets were studied, including 48 fresh and 60 frozen–thawed (F-T) samples. Regarding the F-T samples, two speeds of freezing (fast and slow) were tested. The hyperspectral images of fillets were captured using a pushbroom hyperspectral imaging system in the spectral region of 380 to 1,030 nm. All images were calibrated for reflectance, followed by the minimum noise fraction rotation to reduce the noise. A region-of-interest (ROI) at the image center was selected, and the average spectral data were generated from the ROI image. Dimension reduction was carried out on the ROI image by principal component analysis. The first three principal components (PCs) explained over 98 % of variances of all spectral bands. Gray-level co-occurrence matrix analysis was implemented on the three PC images to extract 36 textural feature variables in total. Least squares-support vector machine classification models were developed to differentiate between fresh and F-T fish based on (1) spectral variables; (2) textural variables; (3) combined spectral and textural variables, respectively. Satisfactory average correct classification rate of 97.22 % for the prediction samples based on (3) was achieved, which was superior to the results based on (1) or (2). The results turned worse when different freezing rates were taken into consideration to classify three groups of fish. The overall results indicate that VIS/NIR hyperspectral imaging technique is promising for the reliable differentiation between fresh and F-T fish.     

Study of Fourier transform near infrared (FT‐NIR) spectra of ghee (anhydrous milk fat)

Ghee is chemically highly complex in nature. The authentication and characterisation of edible fats and oils by routine chemical methods are highly laborious and time‐consuming. Fourier transform near infrared (FT‐NIR) spectroscopy has emerged as the predominant analytical tool in the study of edible fats/oils. In order to assign absorption bands in the infrared (IR) spectrum, spectra of cow and buffalo ghee samples were acquired in the NIR region (10 000–4000 cm^?1). In the FT‐NIR spectrum, a total of nine peaks were obtained for cow and buffalo ghee, with almost equal intensity of absorption. The intensity of absorbance was higher for cow ghee compared to buffalo ghee.     

Preliminary study on the use of near‐infrared reflectance spectroscopy to assess nitrogen content of undried wheat plants

Near‐infrared reflectance (NIR) spectroscopy combined with chemometrics was used to assess nitrogen (N) and dry matter content (DM) and chlorophyll in whole‐wheat plant (Triticum aestivum L). Whole‐wheat plant samples (n = 245) were analysed by reference method and by visible and NIR spectroscopy, in fresh (n = 182) and dry (n = 63) presentations, respectively. Calibration equations were developed using partial least squares (PLS) and validated using full cross‐validation (leave‐one‐out method). Coefficient of determination in calibration (R²_CAL) and the standard error of cross‐validation (SECV) for N content in fresh sample presentation, after second derivative, were 0.89 (SECV: 0.64%), 0.86 (SECV: 0.66%) and 0.82 (SECV: 0.74%) using the visible + NIR, NIR and visible wavelength regions, respectively. Dry sample presentation gave better R²_CAL and SECV for N compared with fresh presentation (R²_CAL > 0.90, SECV < 0.20%) using visible + NIR. The results demonstrated that NIR is a suitable method to assess N concentration in wheat plant using fresh samples (unground and undried). Copyright © 2006 Society of Chemical Industry     

Study on the electric conduction properties of fresh and frozen–thawed grass carp (Ctenopharyngodon idellus) and tilapia(Oreochromis niloticus)

Electric conduction properties of fresh and frozen–thawed grass carp (Ctenopharyngodon idellus) and tilapia (Oreochromis niloticus) were studied by measuring their impedances under different frequencies. The impedances varied as frequency changed. Although impedances of both fresh and frozen–thawed fish decreased as frequency increased from 1 to 20 kHz, change ratio of impedance (Q value) of fresh fish was evidently higher than that of frozen–thawed fish. The Q values of fresh grass carp and tilapia on the 1st, 3rd, 6th, 8th, 10th days were 60.53%, 52.24%, 35.47%, 26.86%, 21.17% and 73.13%, 52.70%, 41.06%, 39.28%, 36.31%, while frozen–thawed grass carp and tilapia were 9.65%, 11.21%, 9.58%, 8.89%, 9.13% and 18.26%, 12.80%, 13.46%, 12.16%, 12.91%, respectively. Electric conduction is a rapid, easy to use, portable and cost‐effective method for in situ analysis at practical level. Therefore, it is feasible to identify fresh and frozen–thawed fish according to the change ratio of their impedances.     

CLASSIFICATION OF CHINESE RICE WINE WITH DIFFERENT MARKED AGES BASED ON NEAR INFRARED SPECTROSCOPY

The feasibility of near infrared (NIR) spectroscopy for discrimination between Chinese rice wine with different marked ages (1, 3 and 5 years) was presented in this research. NIR spectra were collected in transmission mode in the wavelength range of 800–2500 nm. Discriminant models were developed based on discriminant analysis (DA) together with raw and second derivative spectra. The calibration result for raw spectra was better than that for second derivative spectra. The percentage of samples correctly classified for raw and second derivative spectra was 100 and 78.4%, respectively. In validation analysis, the percentage of samples correctly classified was 94.4%. For 1‐, 3‐ and 5‐year‐old sample groups, the percentage of samples correctly classified was 88.3, 100 and 100%, respectively. The results demonstrated that NIR spectroscopy could be used as a rapid and reliable method for classification of Chinese rice wine with different marked ages.     

Protein content determination in Brassica oleracea species using FT‐NIR technique and PLS regression

Six fresh and one frozen vegetable cultivar groups possessing remarkably different morphology from the same Brassica oleracea species, including broccoli, Brussels sprouts, curly cabbage, white cabbage, red cabbage, cauliflower and white kohlrabi, were chosen to set up a Fourier transform near‐infrared spectroscopy (FT‐NIR)‐based method for the quantification of protein content. Sample preparation was based on lyophilisation and homogenisation. Calibration was set up with the help of the Kjeldahl method for the quantification of protein content in the range of 12.9–32.5 m/m%. Calibration model was developed using the spectral regions 1136–1334 and 1639–1836 nm, with partial least squares regression. This model was checked by cross‐validation. The performance of the final FT‐NIR estimation model was evaluated by root mean square of cross‐validation, root‐mean‐square error of estimation and the determination coefficient (R²). The final estimation function for the protein determination was characterised with the predictive error of 0.76 m/m% and R² value of 98.81.     

Effect of freezing/thawing conditions and long‐term frozen storage on the quality of mashed potatoes

The effects of freezing temperature (−80, −40 or −24 °C) and thawing mode (microwave or overnight at 4 °C) on quality parameters of mashed potatoes made from tubers (cv Kennebec) and from potato flakes were examined, as was the effect of long‐term frozen storage on the quality of mashed potatoes. Mashed potatoes were tested for texture profile analysis (TPA) and cone penetration, oscillatory and steady rheometry, colour, dry matter, Brix and sensory analyses. In natural mashed potatoes, TPA hardness and oscillatory parameters showed that processing resulted in a softer product than the fresh control. The parameters were lower in the samples thawed at 4 °C than in those thawed by microwave at all the freezing temperatures used, which may be ascribed to gelatinisation of the starch released from damaged cells. Differences from the freshly prepared product decreased when the samples were frozen at −80 °C and thawed by microwave. No difference was found in sensory acceptability between samples frozen at −80 and −40 °C, which probably reflects the panellists' mixed preferences for air‐thawed versus microwave‐thawed samples. Increasing the time in frozen storage led to a natural mash with a firmer texture, higher L*/b* value and Brix; nonetheless, panellists found the samples at 0, 3 and 12 months of frozen storage equally acceptable. In commercial mash, penetration and oscillatory parameters showed that processing made for a firmer product than the fresh control, probably owing to retrogradation of gelatinised starch. Thawing mode had a significant effect on parameters, which were lower in the samples thawed at 4 °C. The structure and quality of commercial mash was more detrimentally affected by freezing and, therefore, we would not recommend either freezing or frozen storage of this mashed potato in the used conditions. Natural mash made from Kennebec potatoes should be frozen quickly and thawed by microwave in the conditions described to obtain a product more similar to that freshly made. If the samples are frozen by air blasting at −40 °C, the product can withstand frozen storage for one year. Copyright © 2005 Society of Chemical Industry     

Frozen herring as raw material for spice‐salting

One batch of herring (Clupea harengus) was spice‐salted fresh and as thawed after 32 days of frozen storage at −24 °C. After salting, samples of both groups were sent to participating laboratories in Iceland, Denmark, Norway, Germany and England. The herring was kept at 5 ± 1 °C and sampled three times during a 26 week storage period. The development of taste and texture characteristics (determined by sensory evaluation and instrumental texture measurements), formation of low‐molecular‐weight nitrogen compounds and changes in proteolytic activity were followed in both groups. The sensory evaluation results showed that thawed salted herring ripened in a similar manner to herring salted fresh, but at a faster rate. Instrumental texture analysis showed a faster rate of tenderising in thawed salted herring. Proteolytic activity measured as general activity and with specific synthetic substrates was higher in the thawed salted herring. The formation of trichloroacetic acid‐soluble nitrogen and free amino acids was faster in the previously frozen herring. The results show an accelerated but similar rate of ripening in thawed spice‐salted herring in comparison with fresh salted herring. © 2000 Society of Chemical Industry     

Freshness Assessment of Thawed and Chilled Cod Fillets Packed in Modified Atmosphere Using Near-infrared Spectroscopy

Near-infrared reflectance (NIR) spectra was recorded of 105 samples of cod mince prepared from chill stored thawed cod fillets of varying quality in modified atmosphere packaging (MAP). Traditional chemical, physical, microbiological and sensory quality methods developed for assessing fresh fish products were determined on the same cod fillets. The purpose was to evaluate the potential of NIR spectroscopy for estimating (i) frozen storage temperature, (ii) frozen storage period and (iii) chill storage period of thawed-chilled MAP Barents Sea cod fillets. Furthermore, the potential for measuring of selected quality attributes as drip loss, water holding capacity and content of dimethylamine by NIR was evaluated. The results of the investigation were presented using multivariate modelling methods such as partial least-squares regression (PLSR) and discriminant partial least-squares regression (DPLSR). Systematic differences in the NIR measurements on minced cod fillets were primarily due to the chill storage duration (days at 2°C) on thawed-chilled MAP fillets. PLSR models based on wavelengths selected by a new Jack-knife method resulted in a correlation coefficient of 0.90 between measured and predicted duration of chill storage period (days at 2°C). The root-mean-square error of cross-validation (RMSECV) was 3.4 d at 2°C. NIR measurements provided promising results for evaluation of freshness for thawed-chilled MAP cod fillets completing the traditionally quality methods. However, it is necessary to study the effect of e.g. sample preparation, season, fishing ground and cod size together with more sophisticated pre-treatments of NIR spectra before the NIR method can be integrated as a method for evaluation of thawed-chilled MAP cod fillets.     

Non‐destructive measurement of grapevine water potential using near infrared spectroscopy

Background and Aims: Near infrared (NIR) spectroscopy techniques are not only used for a variety of physical and chemical analyses in the food industry, but also in remote sensing studies as tools to predict plant water status. In this study, NIR spectroscopy was evaluated as a method to estimate water potential of grapevines. Methods and Results: Cabernet Sauvignon, Chardonnay and Shiraz leaves were scanned using an Integrated Spectronic (300–1100 nm) or an ASD FieldSpec^® 3 (Analytical Spectral Devices, Boulder, Colorado, USA) (350–1850 nm) spectrophotometer and then measured to obtain midday leaf water potential using a pressure chamber. On the same shoot, the leaf adjacent the one used for midday leaf water potential measurement was used to measure midday stem water potential. Calibrations were built and NIR showed good prediction ability (standard error in cross validation (SECV) <0.24 MPa) for stem water potential for each of the three grapevine varieties. The best calibration was obtained for the prediction of stem water potential in Shiraz (R = 0.92 and a SECV = 0.09 MPa). Conclusion: Differences in the NIR spectra were related to the leaf surface from which the spectra were collected, and this had an effect on the accuracy of the calibration results for water potential. We demonstrated that NIR can be used as a simple and rapid method to detect grapevine water status. Significance of the Study: Grapevine water potential can be measured using NIR spectroscopy. The advantages of this new approach are speed and low cost of analysis. It may be possible for NIR to be used as a non‐destructive, in‐field tool for irrigation scheduling.     

Comparison of methods of differentiating between fresh and frozen–thawed fish or fillets

Freezing is an efficient way of storing fish. Objectively though, it is very hard to determine whether a fish has been previously frozen. Following an appraisal of various methods, we selected a physical determination (torrymeter), a physiological examination (eye lens) and three enzymatic assays (α‐glucosidase, β‐N‐acetylglucosaminidase and β‐hydroxyacyl‐CoA‐dehydrogenase) and applied them to three species: plaice (Pleuronectes platessa), whiting (Merlangus merlangus) and mackerel (Scomber scombrus). We also compared the results obtained following slow and rapid freezing and investigated how spoilage affects the torrymeter measurements and α‐glucosidase assay values. For whole fish the physical method using the torrymeter is a reliable indicator. For fish fillets we recommend the enzymatic method using the α‐glucosidase assay, which should be accompanied by measurement of the freshness to avoid confusing a frozen–thawed fish and a fish in an advanced stage of spoilage. The values noted for fresh and thawed whiting and plaice indicated cut‐off values of 0.15 for whiting and 0.5 for plaice, above which it can be asserted that the sample had been frozen. © 2002 Society of Chemical Industry     

Rapid Estimation of Potato Tuber Quality by Near‐Infrared Spectroscopy

Starch and protein parameters of potato tubers were estimated by near‐infrared (NIR) spectroscopy measurements of the crude potato mash. Calibration was carried out with a condensed data set of original 1481 individual samples from a varying number of varieties and breeding lines, grown at eight locations over a three‐years period. Validation of the models was performed with an independent data set (n = 133). Starch content of potato tubers was determined with the official under‐water weighting procedure of the EU, and could be predicted with 90% confidence. The NIR model of phosphorus content of starch had a prediction confidence of 53%. Total protein content could be predicted, too (62% confidence), whereas the amount of coagulable protein was not predictable (R² = 0.25). Despite the different qualification levels of the models, guiding to concrete prediction tools or to a very rough estimation graduating from “low” to “high”, the NIR technique enables potato starch processing plants to optimise both potato starch quality and processing efficiency.     

Quality evaluation of frozen guava and yellow passion fruit pulps by NIR spectroscopy and chemometrics

The present study investigated the application of near infrared spectroscopy as a green, quick, and efficient alternative to analytical methods currently used to evaluate the quality (moisture, total sugars, acidity, soluble solids, pH and ascorbic acid) of frozen guava and passion fruit pulps. Fifty samples were analyzed by near infrared spectroscopy (NIR) and reference methods. Partial least square regression (PLSR) was used to develop calibration models to relate the NIR spectra and the reference values. Reference methods indicated adulteration by water addition in 58% of guava pulp samples and 44% of yellow passion fruit pulp samples. The PLS models produced lower values of root mean squares error of calibration (RMSEC), root mean squares error of prediction (RMSEP), and coefficient of determination above 0.7. Moisture and total sugars presented the best calibration models (RMSEP of 0.240 and 0.269, respectively, for guava pulp; RMSEP of 0.401 and 0.413, respectively, for passion fruit pulp) which enables the application of these models to determine adulteration in guava and yellow passion fruit pulp by water or sugar addition. The models constructed for calibration of quality parameters of frozen fruit pulps in this study indicate that NIR spectroscopy coupled with the multivariate calibration technique could be applied to determine the quality of guava and yellow passion fruit pulp.     

Near‐infrared spectroscopy and data analysis for predicting milk powder quality attributes

Near‐infrared (NIR) spectroscopy is a rapid analytical method for food products. In this study, NIR spectroscopy, data pretreatment techniques and multivariate data analysis were used to predict fine particle size fraction, dispersibility and bulk density of various milk powder samples, which are believed to have a significant impact on milk powder quality. Predictive models using partial least‐squares (PLS) regression were developed using NIR spectra and milk powder physical and functional properties, and it was concluded that the PLS models predicted milk powder quality with an accuracy of 88‐90 per cent.     

Using Wavelet Textural Features of Visible and Near Infrared Hyperspectral Image to Differentiate Between Fresh and Frozen–Thawed Pork

In this study, wavelet textural analysis was applied to hyperspectral images in the visible and near-infrared (VIS/NIR) region (400–1,000 nm) for differentiation between fresh and frozen–thawed pork. The spectral data of acquired hyperspectral images were analyzed using partial least squares (PLS) regression and five wavelengths (462, 488, 611, 629, and 678 nm) were selected as the feature wavelengths by the regression coefficients from the PLS model. The fourth-order daubechies wavelet (“db4”) was used to serve as the wavelet mother function for wavelet textural extraction of the feature images at the above selected feature wavelengths with the wavelet decomposition level from 1 to 4. Four textural features were calculated in the horizontal, vertical, and diagonal orientations at each level. Forty-eight textural features were extracted from each feature image and used to differentiate between fresh and frozen–thawed pork samples by least-squares support vector machine (LS-SVM) model. Wavelet texture extracted from all five feature images at first decomposition level was identified as optimal wavelet texture combination, resulting in the highest classification accuracy for the LS-SVM models (98.48 % for the training set and 93.18 % for the testing set). Based on the texture combination, the quality attributes of pork meat could be predicted with correlation coefficients of calibration (r _c ) of 0.982 and 0.913, and correlation coefficients of prediction (r _p ) of 0.845 and 0.711 for pH and thawing loss, respectively. The results showed the possibility of developing a fast and reliable hyperspectral system for discrimination between fresh and frozen–thawed pork samples based on wavelet texture in the VIS/NIR wavelength range.     

Color stability of frozen whole tilapia exposed to pre‐mortem treatment with carbon monoxide

BACKGROUND: Color of muscle foods plays a major role in consumer perception of meat quality. Carbon monoxide (CO) has been successfully used for improving color of packaged meat and fish products. In this study, we wanted to investigate pre‐mortem treatment of live tilapia using 100% CO for its ability to improve the color of frozen whole tilapia. We compared untreated and CO‐treated whole, gutted tilapia, frozen for 2 and 4 months at ? 20 °C. Frozen tilapia samples were thawed overnight at 4 °C, filleted and analyzed for their color, heme peak wavelength and CO concentration. RESULTS: Euthanasia using CO significantly increased redness (a* value) and lightness (L* value) of tilapia white and red muscle. Frozen storage significantly (P < 0.05) decreased redness of both CO‐treated and untreated tilapia. However, even after 4 months of frozen storage, a*‐value of CO‐treated tilapia was similar to fresh untreated tilapia fillets. Heme peak wavelengths of CO‐euthanized tilapia were higher than in untreated tilapia and there was no significant (P > 0.05) decrease in heme peak wavelengths of CO‐treated tilapia white and red muscle during frozen storage. The CO content of frozen euthanized tilapia fillets was significantly (P > 0.05) higher than in untreated fillets. In general, red muscle tissue of euthanized tilapia had a higher concentration of CO than white muscle. CONCLUSION: Color stability of tilapia fillets was significantly improved by pre‐mortem CO treatment. The color of CO‐treated fillets was retained during frozen storage compared to untreated fillets. Hence, pre‐mortem CO treatment could be used as a new method for improving color of tilapia. Copyright © 2008 Society of Chemical Industry