Preliminary investigation of the application of Raman spectroscopy to the prediction of the sensory quality of beef silverside

Feasibility of boar taint classification using a portable Raman device

The feasibility of Raman spectroscopy for boar taint detection and classification was investigated using tainted and untainted backfat samples of 46 boars. For this exploratory study, backfat samples were selected according to their levels of androstenone and skatole as determined by gas chromatography and their sensory score by a trained panel. Raman spectra were collected with a portable device at freshly cut surfaces of frozen-thawed samples. Both inner and outer layers of subcutaneous fat were studied. Their varying level of unsaturation was reflected in the Raman spectra. Partial least squares regression discriminant analysis (PLS-DA) was applied to the spectra together with various pre-processing methods. A model using only spectra obtained at the inner layer resulted in the highest classification accuracy for boar taint (81% of samples correctly classified). The discrimination is shown to reflect differences in the degree of fatty acid saturation between tainted and untainted boars. In conclusion, the findings suggest that with further development Raman spectroscopy may be used to classify boar taint.

Dispersive Raman spectroscopy and multivariate data analysis to detect offal adulteration of thawed beefburgers

Beef offal (i.e., kidney, liver, heart, lung) adulteration of beefburgers was studied using dispersive Raman spectroscopy and multivariate data analysis to explore the potential of these analytical tools for detection of adulterations in comminuted meat products with complex formulations. Adulterated (n = 46) and authentic (n = 36) beefburger samples were produced based on formulations derived using market knowledge and an experimental design. Raman spectral data in the fingerprint range (900-1800 cm(-1)) were examined using both a classification (partial least-squares discriminant analysis, PLS-DA) and class-modeling (soft independent modeling of class analogy, SIMCA) approach to identify offal-adulterated and authentic beefburgers. PLS-DA models correctly classified 89-100% of authentic and 90-100% of adulterated samples. SIMCA models were developed using either PCA or PLS scores as input data. For authentic beefburgers, they exhibited sensitivity, specificity, and efficiency values of 0.94-1, 0.64-1, and 0.80-0.97, respectively. PLS regression quantitative models were also developed in an attempt to quantify total offal and added fat in these samples. The performance of PLS regression quantitative models for prediction of added fat may be acceptable for screening purposes, with the most accurate model producing a coefficient of determination in prediction of 0.85 and a root-mean-square error of prediction equal to 3.8% w/w.

Predicting tenderness of fresh ovine semimembranosus using Raman spectroscopy

A hand held Raman probe was used to predict shear force (SF) of fresh lamb m. semimembranosus (topside). Eighty muscles were measured at 1 day PM and after a further 4 days ageing (5 days PM). At 1 day PM sarcomere length (SL) and particle size (PS) were measured and at 5 days PM, SF, PS, cooking loss (CL) and pH were also measured. SF values were regressed against Raman spectra using partial least squares regression and against traditional predictors (e.g. SL) using linear regression. The best prediction of SF used spectra at 1 day PM which gave a root mean square error of prediction (RMSEP) of 11.5 N (Null = 13.2) and the squared correlation between observed and cross validated predicted values (R(2)cv) was 0.27. Prediction of SF based on the traditional predictors had smaller R(2) values than using Raman spectra justifying further study on Raman spectroscopy.

Raman spectroscopy in determination of horse meat content in the mixture with other meats

A new method based on FT-Raman measurements that allows to determine the content of horse meat in its mixture with beef has been proposed. In the analysis of the Raman spectra of the meat mixtures, the integral intensity ratios of the 937/1003, 879/1003, 856/1003, 829/1003, and 480/1003cm(-1) pairs of bands have been determined the intensities of which were related to the reference intensity of the band at 1003cm(-1). The reasonable results that show good fitting between the spectroscopic parameters and chemical content of the studied samples have been obtained. The analytical equations between these parameters have been proposed.

Konjac glucomannan-induced changes in thiol/disulphide exchange and gluten conformation upon dough mixing

Effects of konjac glucomannan (KGM) on the changes in gluten upon dough mixing were investigated in this study. Wheat flour was blended with KGM and processed into dough. Farinographic analysis showed that KGM caused a significant increase in water absorption and dough development time to reach maximum consistency. Comparison of electrophoretic protein profile from control dough and KGM-dough revealed that protein fractions were similar in molecular size distribution, but the lability of glutenin aggregates slightly differed. Addition of KGM to gluten induced negative effects on exchange between sulfhydryl groups and disulphide bonds. Fourier transform-Raman spectroscopy indicated that secondary structure of gluten proteins was differentially modified related with water absorption of flours before dough formation. This study reveals that when KGM is added to the dough, conformational behaviours of gluten proteins are changed and the hydroxyl groups of KGM might be involved in the interaction by forming strong intermolecular hydrogen bonding system.

Structural evaluation of myofibrillar proteins during processing of Cantonese sausage by Raman spectroscopy

Structural changes of myofibrillar proteins from raw pork muscle and Cantonese sausage at different processing periods were elucidated using Raman spectroscopy. Fourier deconvolution combined with iterative curve fitting were used to analyze the amide I Raman band. Results from amide I, amide III, and C-C stretching vibrations in 890-1060 cm(-1) showed that α-helix decreased accompanied by an increase in β-sheet structure during the first 18 h, and a rebuilding process of secondary structures was observed at the rest stage due to proteolysis. The hierarchical cluster analysis results of amide I and amide III confirmed this rebuilding process. Changes in a doublet near 850 and 830 cm(-1) suggested that some tyrosine residues became buried in a more hydrophobic environment due to intermolecular interactions. Raman spectra in the 2855-2940 cm(-1) region suggested that the environment of aliphatic side chains might have been changed during the final stage and further confirmed above rebuilding process.

Multiplex analysis of age-related protein and lipid modifications in human Bruch's membrane

Aging of the human retina is characterized by progressive pathology, which can lead to vision loss. This progression is believed to involve reactive metabolic intermediates reacting with constituents of Bruch's membrane, significantly altering its physiochemical nature and function. We aimed to replace a myriad of techniques following these changes with one, Raman spectroscopy. We used multiplexed Raman spectroscopy to analyze the age-related changes in 7 proteins, 3 lipids, and 8 advanced glycation/lipoxidation endproducts (AGEs/ALEs) in 63 postmortem human donors. We provided an important database for Raman spectra from a broad range of AGEs and ALEs, each with a characteristic fingerprint. Many of these adducts were shown for the first time in human Bruch's membrane and are significantly associated with aging. The study also introduced the previously unreported up-regulation of heme during aging of Bruch's membrane, which is associated with AGE/ALE formation. Selection of donors ranged from ages 32 to 92 yr. We demonstrated that Raman spectroscopy can identify and quantify age-related changes in a single nondestructive measurement, with potential to measure age-related changes in vivo. We present the first directly recorded evidence of the key role of heme in AGE/ALE formation.

Raman spectroscopy for monitoring protein structure in muscle food systems

Raman spectroscopy offers structural information about complex solid systems such as muscle food proteins. This spectroscopic technique is a powerful and a non-invasive method for the study of protein changes in secondary structure, mainly quantified, analysing the amide I (1650-1680 cm(- 1)) and amide III (1200-1300 cm(- 1)) regions and C-C stretching band (940 cm(- 1)), as well as modifications in protein local environments (tryptophan residues, tyrosil doublet, aliphatic aminoacids bands) of muscle food systems. Raman spectroscopy has been used to determine structural changes in isolated myofibrillar and connective tissue proteins by the addition of different compounds and by the effect of the conservation process such as freezing and frozen storage. It has been also shown that Raman spectroscopy is particularly useful for monitoring in situ protein structural changes in muscle food during frozen storage. Besides, the possibilities of using protein structural changes of intact muscle to predict the protein functional properties and the sensory attributes of muscle foods have been also investigated. In addition, the application of Raman spectroscopy to study changes in the protein structure during the elaboration of muscle food products has been demonstrated.

Raman spectroscopic evaluation of meat batter structural changes induced by thermal treatment and salt addition

Raman spectroscopy, texture, proximate composition, and water binding analysis were carried out to evaluate the effect of thermal treatment and/or salt addition to meat batter. For this purpose, different meat batters were elaborated: control meat batter (no salt) and meat batters with low (1.0%) and high (2.5%) NaCl content with and without thermal treatment (70 degrees C/30 min). Increase (P < 0.05) in penetration force and hardness upon heating was observed. Results also showed hardness increasing (P < 0.05) as a function of salt addition in heated meat batter. Raman spectroscopy analysis revealed a significant (P < 0.05) decrease in alpha-helix content accompanied by an increase (P < 0.05) in beta-sheets resulting from heating. Significant (P < 0.05) correlations were found between these secondary structural changes in meat proteins and water binding and textural properties of meat batter. In this way, a significant correlation was found between beta-sheets, salt content, hardness, and chewiness in heated samples.

Meat quality assessment using biophysical methods related to meat structure

This paper overviews the biophysical methods developed to gain access to meat structure information. The meat industry needs reliable meat quality information throughout the production process in order to guarantee high-quality meat products for consumers. Fast and non-invasive sensors will shortly be deployed, based on the development of biophysical methods for assessing meat structure. Reliable meat quality information (tenderness, flavour, juiciness, colour) can be provided by a number of different meat structure assessment either by means of mechanical (i.e., Warner-Bratzler shear force), optical (colour measurements, fluorescence) electrical probing or using ultrasonic measurements, electromagnetic waves, NMR, NIR, and so on. These measurements are often used to construct meat structure images that are fusioned and then processed via multi-image analysis, which needs appropriate processing methods. Quality traits related to mechanical properties are often better assessed by methods that take into account the natural anisotropy of meat due to its relatively linear myofibrillar structure. Biophysical methods of assessment can either measure meat component properties directly, or calculate them indirectly by using obvious correlations between one or several biophysical measurements and meat component properties. Taking these calculations and modelling the main relevant biophysical properties involved can help to improve our understanding of meat properties and thus of eating quality.

Preliminary investigations on the effects of ageing and cooking on the Raman spectra of porcine longissimus dorsi

The influence of ageing and cooking on the Raman spectrum of porcine longissimus dorsi was investigated. The rich information contained in the Raman spectrum was highlighted, with numerous changes attributed to changes in the environment and conformations of the myofibrillar proteins. Predictions equations for shear force and cooking loss were developed from the Raman spectra of both raw and cooked pork. Good correlations and standard errors of prediction were obtained for both WB shear force and cooking loss, with the raw and the cooked samples showing almost identical results R(2)=0.77, root mean standard error of prediction (RMSEP)% of mean=12% for shear force; R(2)=0.71, RMSEP% of mean=10% for cooking loss. The Raman spectra were also able to predict the extent of cooking that occurred within the pork (R(2)(val)=0.94, RMSEP% of range=5.5%). Raman spectroscopy has considerable potential as a method for non-destructive and rapid determination of pork quality parameters such as tenderness. Raman spectroscopy may provide a means of determining changes during cooking and the extent to which foods have been cooked.

Revealing covariance structures in fourier transform infrared and Raman microspectroscopy spectra: a study on pork muscle fiber tissue subjected to different processing parameters

The aim of this study was to investigate the correlation patterns between Fourier transform infrared (FT-IR) and Raman microspectroscopic data obtained from pork muscle tissue, which helped to improve the interpretation and band assignment of the observed spectral features. The pork muscle tissue was subjected to different processing factors, including aging, salting, and heat treatment, in order to induce the necessary degree of variation of the spectra. For comparing the information gained from the two spectroscopic techniques with respect to the experimental design, multiblock principal component analysis (MPCA) was utilized for data analysis. The results showed that both FT-IR and Raman spectra were mostly affected by heat treatment, followed by the variation in salt content. Furthermore, it could be observed that IR amide I, II, and III band components appear to be effected to a different degree by brine-salting and heating. FT-IR bands assigned to specific protein secondary structures could be related to different Raman C-C stretching bands. The Raman C-C skeletal stretching bands at 1,031, 1,061, and 1,081 cm(-1) are related to the IR bands indicative of aggregated beta-structures, while the Raman bands at 901 cm(-1) and 934 cm(-1) showed a strong correlation with IR bands assigned to a alpha-helical structures. At the same time, the IR band at 1,610 cm(-1), which formerly was assigned to tyrosine in spectra originating from pork muscle, did not show a correlation to the strong tyrosine doublet at 827 and 852 cm(-1) found in Raman spectra, leading to the conclusion that the IR band at 1,610 cm(-1) found in pork muscle tissue is not originating from tyrosine.

Raman spectra of biological samples: A study of preprocessing methods

In this study preprocessing of Raman spectra of different biological samples has been studied, and their effect on the ability to extract robust and quantitative information has been evaluated. Four data sets of Raman spectra were chosen in order to cover different aspects of biological Raman spectra, and the samples constituted salmon oils, juice samples, salmon meat, and mixtures of fat, protein, and water. A range of frequently used preprocessing methods, as well as combinations of different methods, was evaluated. Different aspects of regression results obtained from partial least squares regression (PLSR) were used as indicators for comparing the effect of different preprocessing methods. The results, as expected, suggest that baseline correction methods should be performed in advance of normalization methods. By performing total intensity normalization after adequate baseline correction, robust calibration models were obtained for all data sets. Combination methods like standard normal variate (SNV), multiplicative signal correction (MSC), and extended multiplicative signal correction (EMSC) in their basic form were not able to handle the baseline features present in several of the data sets, and these methods thus provide no additional benefits compared to the approach of baseline correction in advance of total intensity normalization. EMSC provides additional possibilities that require further investigation.

Application of Fourier transform Raman spectroscopy for prediction of bitterness of peptides

The potential application of Fourier transform (FT) Raman spectroscopy to predict the bitterness of peptides was investigated. FT-Raman spectra were measured for the amino acid Phe and 9 synthetic di-, tri-, and tetra peptides composed of Phe, Gly, and Pro. Partial least squares regression (PLS)-1 analysis was applied to correlate the FT-Raman spectra with bitterness intensity values (R(caf) and log 1/T) reported in the literature. Using full cross-validation, Model 1 based on the single spectral data set for the nine peptides yielded a high correlation coefficient for calibration (R = 0.99), but a low correlation coefficient for prediction (R = 0.56). Two models were constructed using the data sets including replicate spectra for the calibrations and were validated using full cross-validation. Using leave-one-sample-set-out calibrations, Model 2, which was developed with the data for the peptides as well as Phe, yielded a low correlation coefficient (R = 0.533) for the prediction of the bitterness, while Model 3 developed with only the peptide data provided better correlation coefficients (R = 0.807 and 0.724 for R(caf) and log 1/T values, respectively). The correlation coefficients for prediction were 0.975 (R(caf) values) and 0.874 (log 1/T values) for Model 4, which was developed using subtracted spectral data (spectra of peptides with higher R(caf) values minus spectra of peptides with lower R(caf) values). Examination of the PLS regression coefficients at wavenumbers most highly correlated with bitterness revealed the importance of hydrophobicity and peptide length on bitterness. This study indicates the potential of FT-Raman spectroscopy as a useful tool for predicting bitterness of peptides and amino acids.

The potential of Raman spectroscopy for characterisation of the fatty acid unsaturation of salmon

Raman spectroscopy has been evaluated for characterisation of the degree of fatty acid unsaturation (iodine value) of salmon (Salmo salar). The Norwegian Quality Cuts from 50 salmon samples were obtained, and the samples provided an iodine value range of 147.8-170.0 g I2/100 g fat, reflecting a normal variation of farmed salmon. Raman measurements were performed both on different spots of the intact salmon muscle, on ground salmon samples as well as on oil extracts, and partial least squares regression (PLSR) was utilised for calibration. The oil spectra provided better iodine value predictions than the other data sets, and a correlation coefficient of 0.87 with a root mean square error of cross-validation of 2.5 g I2/100 g fat was achieved using only one PLSR component. The ground samples provided comparable results, but at least two PLSR components were needed. Higher prediction errors were obtained from Raman spectra of intact salmon muscle, and this may partly be explained by sampling uncertainties in the relation between Raman measurements and reference analysis. All PLSR models obtained were based on chemically sound regression coefficients, and thus information regarding fatty acid unsaturation is readily available from Raman spectra even in systems with high contents of protein and water. The accuracy, the robustness and the low complexity of the PLSR models obtained suggest Raman spectroscopy as a promising method for rapid in-process control of the degree of unsaturation in salmon samples.

Prediction of adipose tissue composition using raman spectroscopy: Average properties and individual fatty acids

Raman spectroscopy has been used for the first time to predict the FA composition of unextracted adipose tissue of pork, beef, lamb, and chicken. It was found that the bulk unsaturation parameters could be predicted successfully [R2 = 0.97, root mean square error of prediction (RMSEP) = 4.6% of 4 sigma], with cis unsaturation, which accounted for the majority of the unsaturation, giving similar correlations. The combined abundance of all measured PUFA (> or = 2 double bonds per chain) was also well predicted with R2 = 0.97 and RMSEP = 4.0% of 4 sigma. Trans unsaturation was not as well modeled (R2 = 0.52, RMSEP = 18% of 4 sigma); this reduced prediction ability can be attributed to the low levels of trans FA found in adipose tissue (0.035 times the cis unsaturation level). For the individual FA, the average partial least squares (PLS) regression coefficient of the 18 most abundant FA (relative abundances ranging from 0.1 to 38.6% of the total FA content) was R2 = 0.73; the average RMSEP = 11.9% of 4 sigma. Regression coefficients and prediction errors for the five most abundant FA were all better than the average value (in some cases as low as RMSEP = 4.7% of 4 sigma). Cross-correlation between the abundances of the minor FA and more abundant acids could be determined by principal component analysis methods, and the resulting groups of correlated compounds were also well-predicted using PLS. The accuracy of the prediction of individual FA was at least as good as other spectroscopic methods, and the extremely straightforward sampling method meant that very rapid analysis of samples at ambient temperature was easily achieved. This work shows that Raman profiling of hundreds of samples per day is easily achievable with an automated sampling system.

A critical evaluation of Raman spectroscopy for the analysis of lipids: fatty acid methyl esters

The work presented here is aimed at determining the potential and limitations of Raman spectroscopy for fat analysis by carrying out a systematic investigation of C4-C24 FAME. These provide a simple, well-characterized set of compounds in which the effect of making incremental changes can be studied over a wide range of chain lengths and degrees of unsaturation. The effect of temperature on the spectra was investigated over much larger ranges than would normally be encountered in real analytical measurements. It was found that for liquid FAME the best internal standard band was the carbonyl stretching vibration v(C=O), whose position is affected by changes in sample chain length and physical state; in the samples studied here, it was found to lie between 1729 and 1748 cm(-1). Further, molar unsaturation could be correlated with the ratio of the nu(C=O) to either nu(C=C) or delta(H-C=) with R2 > 0.995. Chain length was correlated with the delta(CH2)tw/v(C=O) ratio, (where "tw" indicates twisting) but separate plots for odd- and even-numbered carbon chains were necessary to obtain R2 > 0.99 for liquid samples. Combining the odd- and even-numbered carbon chain data in a single plot reduced the correlation to R2 = 0.94-0.96, depending on the band ratios used. For molal unsaturation the band ratio that correlated linearly with unsaturation (R2 > 0.99) was nu(C=C)/delta(CH2)sc (where "sc" indicates scissoring). Other band ratios show much more complex behavior with changes in chemical and physical structure. This complex behavior results from the fact that the bands do not arise from simple vibrations of small, discrete regions of the molecules but are due to complex motions of large sections of the FAME so that making incremental changes in structure does not necessarily lead to simple incremental changes in spectra.

Study of protein-lipid interactions at the bovine serum albumin/oil interface by Raman microspectroscopy

The interface of 10 or 25% (w/v) bovine serum albumin (BSA), pH 7, buffered solution against mineral or corn oil was studied with a Raman microscope. A gradient of distribution of protein and oil at the interface was observed. The difference spectrum obtained by subtracting the spectrum of mineral or corn oil from that of the BSA/oil interface indicated interactions involving different functional groups of the BSA and the oil molecules. Against mineral oil, the BSA spectrum showed reduced intensity of the tryptophan band at 750 cm(-1) and reduced intensity ratio of the tyrosine doublet at 850-830 cm(-1), indicating changes in the microenvironment of these hydrophobic residues. A negative band at 2850 cm(-1) indicated the involvement of the CH groups in the mineral oil. However, the amide regions, normally assigned to protein secondary structure, were not significantly changed. When the spectrum of BSA was subtracted from the BSA/mineral oil interface spectrum, the resultant difference spectrum showed changes of symmetric and antisymmetric CCC stretches at 980 and 1071 cm(-1), respectively. In contrast, the difference spectrum of BSA/corn oil interface - BSA showed a decrease of CH(2) symmetric stretching at 2850 cm(-1) and a decrease of unsaturated fatty acid hydrocarbon chain stretch at 3010 cm(-1). Raman spectroscopy is a useful tool to study the nature of protein-lipid interactions.