Raman spectroscopy and NIR hyperspectral imaging for in-line estimation of fatty acid features in salmon fillets.

Raman spectroscopy was compared with near infrared (NIR) hyperspectral imaging for determination of fat composition (%EPA + DHA) in salmon fillets at short exposure times. Fillets were measured in movement for both methods. Salmon were acquired from several different farming locations in Norway with different feeding regimes, representing a realistic variation of salmon in the market. For Raman, we investigated three manual scanning strategies; i) line scan of loin, ii) line scan of belly and iii) sinusoidal scan of belly at exposure times of 2s and 4s. NIR images were acquired while the fillets moved on a conveyor belt at 40 cm/s, which corresponds to an acquisition time of 1s for a 40 cm long fillet. For NIR images, three different regions of interest (ROI) were investigated including the i) whole fillet, ii) belly segment, and iii) loin segment. For both Raman and NIR measurements, we investigated an untrimmed and trimmed version of the fillets, both relevant for industrial in-line evaluation. For the trimmed fillets, a fat rich deposition layer in the belly was removed. The %EPA + DHA models were validated by cross validation (N = 51) and using an independent test set (N = 20) which was acquired in a different season. Both Raman and NIR showed promising results and high performances in the cross validation, with R2CV = 0.96 for Raman at 2s exposure and R2CV = 0.97 for NIR. High performances were obtained also for the test set, but while Raman had low and stable biases for the test set, the biases were high and varied for the NIR measurements. Analysis of variance on the squared test set residuals showed that performance for Raman measurements were significantly higher than NIR at 1% significance level (p = 0.000013) when slope-and-bias errors were not corrected, but not significant when residuals were slope-and-bias corrected (p = 0.28). This indicated that NIR was more sensitive to matrix effects. For Raman, signal-to-noise ratio was the main limitation and there were indications that Raman was close to a critical sample exposure time at the 2s signal accumulation.

Raman and near Infrared Spectroscopy for Quantification of Fatty Acids in Muscle Tissue-A Salmon Case Study.

The aim of the present study was to critically evaluate the potential of using NIR and Raman spectroscopy for prediction of fatty acid features and single fatty acids in salmon muscle. The study was based on 618 homogenized salmon muscle samples acquired from Atlantic salmon representing a one year-class nucleus, fed the same high fish oil feed. NIR and Raman spectra were used to make regression models for fatty acid features and single fatty acids measured by gas chromatography. The predictive performance of both NIR and Raman was good for most fatty acids, with R2 above 0.6. Overall, Raman performed marginally better than NIR, and since the Raman models generally required fewer components than respective NIR models to reach high and optimal performance, Raman is likely more robust for measuring fatty acids compared to NIR. The fatty acids of the salmon samples co-varied to a large extent, a feature that was exacerbated by the overlapping peaks in NIR and Raman spectra. Thus, the fatty acid related variation of the spectroscopic data of the present study can be explained by only a few independent principal components. For the Raman spectra, this variation was dominated by functional groups originating from long-chain polyunsaturated FAs like EPA and DHA. By exploring the independent EPA and DHA Raman models, spectral signatures similar to the respective pure fatty acids could be seen. This proves the potential of Raman spectroscopy for single fatty acid prediction in muscle tissue.

Optimization of Instrument Design for In-Line Monitoring of Dry Matter Content in Single Potatoes by NIR Interaction Spectroscopy.

Dry matter (DM) content is one of the most important quality features of potatoes. It defines the physical properties of the potatoes and determines what kind of product the potatoes can be used for. This paper presents the results obtained by a novel prototype NIR (near-infrared) instrument designed to measure DM content in single potatoes in process. The instrument is based on interaction measurements to measure deeper into the potatoes. It measures rapidly, up to 50 measurements per second, allowing several moving potatoes to be measured per second. The instrument also enables several interactance distances to be recorded for each measurement. The instrument was calibrated based on three different potato varieties and the calibration measurements were done in a process plant, making the calibration model suitable for in-line use. A good calibration for DM was obtained by partial least squares regression (RMSECV = 0.78% DM, R2 = 0.91). The instrument was tested in-line in the process plant and several batches of potatoes were monitored for the estimation of the DM distribution per batch. Accuracy of DM determination as function of measurement position on the potato was studied, and results indicate that NIR scans along the center part of the potatoes give slightly better results compared to scans taken on either side of the center. Small differences in optical measurement geometry influence the accuracy of the calibration models, underlining the importance of optimizing instrument design for successful measurements.

Assessment of Bulk Composition of Heterogeneous Food Matrices Using Raman Spectroscopy.

Raman spectroscopy (RS) has for decades been considered a promising tool for food analysis, but widespread adoption has been held back by, e.g., high instrument costs and sampling limitations regarding heterogeneous samples. The aim of the present study was to use wide area RS in conjunction with surface scanning to overcome the obstacle of heterogeneity. Four different food matrices were scanned (intact and homogenized pork and by-products from salmon and poultry processing) and the bulk chemical parameters such as fat and protein content were estimated using partial least squares regression (PLSR). The performance of PLSR models from RS was compared with near-infrared spectroscopy (NIRS). Good to excellent results were obtained with PLSR models from RS for estimation of fat content in all food matrices (coefficient of determination for cross-validation (R2CV) from 0.73 to 0.96 and root mean square error of cross-validation (RMSECV) from 0.43% to 2.06%). Poor to very good PLSR models were obtained for estimation of protein content in salmon and poultry by-product using RS (R2CV from 0.56 to 0.92 and RMSECV from 0.85% to 0.94%). The performance of RS was similar to NIRS for all analyses. This work demonstrates the applicability of RS to analyze bulk composition in heterogeneous food matrices and paves way for future applications of RS in routine food analyses.

Prediction of water holding capacity and pH in porcine longissimus lumborum using Raman spectroscopy.

The main purpose of this study was to investigate if Raman spectra recorded at the exact same position as drip loss measurements could improve prediction of drip loss in pork. One ventral and one dorsal cylindrical plug, cut from a standardized slice from Longissimus lumborum, were used to determine drip loss by EZ-DripLoss method and to collect Raman spectra, while ultimate pH was measured at another location. Partial least squares regression models were developed using spectra from each plug individually or averaged spectra from both plugs. The best models used spectra from the ventral plug, resulting in rcv2=0.75, root mean square error of cross-validation (RMSECV) = 1.27% and ratio of prediction to deviation (RPD) =2.0 for EZ-DripLoss and rcv2=0.72, RMSECV = 0.05 and RPD = 2.0 for ultimate pH. Results indicate that Raman spectroscopy can be used for rough screening of drip loss and pH in pork, and that the location chosen for collection of spectra can be very important for successful predictions.

Predicting post-mortem meat quality in porcine longissimus lumborum using Raman, near infrared and fluorescence spectroscopy.

Spectroscopic techniques can provide valuable information about post-mortem meat quality. In the current study, Raman, NIR and fluorescence spectroscopy was used to analyze pH, drip loss and intramuscular fat in pork longissimus lumborum (n = 122) at 4-5 days post-mortem. Results were promising for partial least squares regression (PLSR) from Raman spectroscopy, giving coefficients of determination from cross validation (rcv2) ranging from 0.49 to 0.73 for all attributes examined. Important regions in the PLSR models from Raman spectroscopy were attributed to changes in concentrations of post-mortem metabolites and modifications of protein secondary structure. Near infrared and fluorescence spectroscopy showed limited ability to analyze quality, with rcv2 ranging from 0.06 to 0.57 and 0.04 to 0.18, respectively. This study encourages further research on the subject of Raman spectroscopy as a technique for meat quality analysis.

Analyzing µ-Calpain induced proteolysis in a myofibril model system with vibrational and fluorescence spectroscopy.

Degree of post-mortem proteolysis influences overall meat quality (e.g. tenderness and water holding capacity). Degradation of isolated pork myofibril proteins by µ-Calpain for 0, 15 or 45 min was analyzed using four spectroscopic techniques; Raman, Fourier transform infrared (FT-IR), near infrared (NIR) and fluorescence spectroscopy. Sodium dodecyl sulfate polyacrylamide gel electrophoresis was used to determine degree of proteolysis. The main changes detected by FT-IR and Raman spectroscopy were degradation of protein backbones manifested in the spectra as an increase in terminal carboxylic acid vibrations, a decrease in CN vibration, as well as an increase in skeletal vibrations. A reduction in ß-sheet secondary structures was also detected, while α-helix secondary structure seemed to stay relatively unchanged. NIR and fluorescence were not suited to analyze degree of proteolysis in this model system.

Primary bovine skeletal muscle cells enters apoptosis rapidly via the intrinsic pathway when available oxygen is removed.

Muscle cells undergo changes post-mortem during the process of converting muscle into meat, and this complex process is far from revealed. Recent reports have suggested programmed cell death (apoptosis) to be important in the very early period of converting muscle into meat. The dynamic balance that occurs between anti-apoptotic members, such as Bcl-2, and pro-apoptotic members (Bid, Bim) helps determine whether the cell initiates apoptosis. In this study, we used primary bovine skeletal muscle cells, cultured in monolayers in vitro, to investigate if apoptosis is induced when oxygen is removed from the growth medium. Primary bovine muscle cells were differentiated to form myotubes, and anoxia was induced for 6h. The anoxic conditions significantly increased (P<0.05) the relative gene expression of anti- and pro-apoptotic markers (Aif, Bcl-2, Bid and Bim), and the PARK7 (P<0.05) and Grp75 (Hsp70) protein expressions were transiently increased. The anoxic conditions also led to a loss of mitochondrial membrane potential, which is an early apoptotic event, as well as cytochrome c release from the mitochondria. Finally, reorganization and degradation of cytoskeletal filaments occurred. These results suggest that muscle cells enters apoptosis via the intrinsic pathway rapidly when available oxygen in the muscle diminishes post-mortem.

Analyzing pH-induced changes in a myofibril model system with vibrational and fluorescence spectroscopy.

The decline of pH and ultimate pH in meat postmortem greatly influences meat quality (e.g. water holding capacity). Four spectroscopic techniques, Raman, Fourier transform infrared (FT-IR), near infrared (NIR) and fluorescence spectroscopy, were used to study protein and amino acid modifications to determine pH-related changes in pork myofibril extracts at three different pH-levels, 5.3, 5.8 and 6.3. Protonation of side-chain carboxylic acids of aspartic and glutamic acid and changes in secondary structure, mainly the amide I-III peaks, were the most important features identified by Raman and FT-IR spectroscopy linked to changes in pH. Fluorescence spectroscopy identified tryptophan interaction with the molecular environment as the most important contributor to changes in the spectra. NIR spectroscopy gave no significant contributions to interpreting protein structure related to pH. Results from our study are useful for interpreting spectroscopic data from meat where pH is an important variable.

The combination of glycosaminoglycans and fibrous proteins improves cell proliferation and early differentiation of bovine primary skeletal muscle cells.

Primary muscle cell model systems from farm animals are widely used to acquire knowledge about muscle development, muscle pathologies, overweight issues and tissue regeneration. The morphological properties of a bovine primary muscle cell model system, in addition to cell proliferation and differentiation features, were characterized using immunocytochemistry, western blotting and real-time PCR. We observed a reorganization of the Golgi complex in differentiated cells. The Golgi complex transformed to a highly fragmented network of small stacks of cisternae positioned throughout the myotubes as well as around the nucleus. Different extracellular matrix (ECM) components were used as surface coatings in order to improve cell culture conditions. Our experiments demonstrated improved proliferation and early differentiation for cells grown on surface coatings containing a mixture of both glycosaminoglycans (GAGs) and fibrous proteins. We suggest that GAGs and fibrous proteins mixed together into a composite biomaterial can mimic a natural ECM, and this could improve myogenesis for in vitro cell cultures.