Quantitative determination of saturated-, monounsaturated- and polyunsaturated fatty acids in pork adipose tissue with non-destructive Raman spectroscopy

Development of innovative antioxidant food packaging systems based on natural extracts from food industry waste and Moringa oleifera leaves

Active packaging that prolongs food shelf life, maintaining its quality and safety, is an increasing industrial demand, especially if integrated in a circular economy model. In this study, the fabrication and characterization of sustainable cellulose-based active packaging using food-industry waste and natural extracts as antioxidant agents was assessed. Grape marc, olive pomace and moringa leaf extracts obtained by supercritical fluid, antisolvent and maceration extraction in different solvents were compared for their antioxidant power and phenolic content. Grape and moringa macerates in acetone and methanol, as the most efficient and cost-effective extracts, were incorporated in the packaging as coatings or in-between layers. Both systems showed significant free-radical protection in vitro (antioxidant power 50%) and more than 50% prevention of ground beef lipid peroxidation over 16 days by indirect TBARS and direct in situ Raman microspectroscopy measurements. Therefore, these systems are promising for industrial applications and more sustainable farm-to-fork food production systems.

Molecular insights into quality and authentication of sheep meat from proteomics and metabolomics

Sheep meat (encompassing lamb, hogget and mutton) is an important source of animal protein in many countries, with a unique flavour and sensory profile compared to other red meats. Flavour, colour and texture are the key quality attributes contributing to consumer liking of sheep meat. Over the last decades, various factors from 'farm to fork', including production system (e.g., age, breed, feeding regimes, sex, pre-slaughter stress, and carcass suspension), post-mortem manipulation and processing (e.g., electrical stimulation, ageing, packaging types, and chilled and frozen storage) have been identified as influencing different aspects of sheep meat quality. However conventional meat-quality assessment tools are not able to elucidate the underlying mechanisms and pathways for quality variations. Advances in broad-based analytical techniques have offered opportunities to obtain deeper insights into the molecular changes of sheep meat which may become biomarkers for specific variations in quality traits and meat authenticity. This review provides an overview on how omics techniques, especially proteomics (including peptidomics) and metabolomics (including lipidomics and volatilomics) are applied to elucidate the variations in sheep meat quality, mainly in loin muscles, focusing on colour, texture and flavour, and as tools for authentication. SIGNIFICANCE: From this review, we observed that attempts have been made to utilise proteomics and metabolomics techniques on sheep meat products for elucidating pathways of quality variations due to various factors. For instance, the improvement of colour stability and tenderness could be associated with the changes to glycolysis, energy metabolism and endogenous antioxidant capacity. Several studies identify proteolysis as being important, but potentially conflicting for quality as the enhanced proteolysis improves tenderness and flavour, while reducing colour stability. The use of multiple analytical methods e.g., lipidomics, metabolomics, and volatilomics, detects a wider range of flavour precursors (including both water and lipid soluble compounds) that underlie the possible pathways for sheep meat flavour evolution. The technological advancement in omics (e.g., direct analysis-mass spectrometry) could make analysis of the proteins, lipids and metabolites in sheep meat routine, as well as enhance the confidence in quality determination and molecular-based assurance of meat authenticity.

Raman studies of the adipose tissue: Current state-of-art and future perspectives in diagnostics

The last decades revealed that the adipose tissue shows an unexplored therapeutic potential. In particular, targeting the perivascular adipose tissue (PVAT), that surrounds blood vessels, can prevent cardiovascular pathologies and browning of the adipose tissue can become an effective strategy against obesity. Therefore, new analytical tools are necessary to analyze this tissue. This review reports on the recent developments of various Raman-based techniques for the identification and quantification of the adipose tissue compared to conventional analytical methods. In particular, the emphasis is on analysis of PVAT, investigation of pathological changes of the adipose tissue in model systems and possibilities for its characterization in the clinical context. Overall, the review critically discusses the potential and limitations of Raman techniques in adipose tissue-targeted diagnostics and possible future anti-obesity therapies.

Prediction of fatty acids composition in the rainbow trout Oncorhynchus mykiss by using Raman micro-spectroscopy

The importance of poly-unsaturated fatty acids (PUFAs) in food is crucial for the animal and human development and health. As a complementary strategy to nutrition approaches, genetic selection has been suggested to improve fatty acids (FAs) composition in farmed fish. Gas chromatography (GC) is used as a reference method for the quantification of FAs; nevertheless, the high cost prevents large scale phenotyping as needed in breeding programs. Therefore, a calibration by means of Raman scattering spectrometry has been established in order to predict FA composition of visceral adipose tissue in rainbow trout Onchorhynchus mykiss. FA composition was analyzed by both GC and Raman micro-spectrometry techniques on 268 individuals fed with three different feeds, which have different FA compositions. Among the possible regression methods, the ridge regression method, was found to be efficient to establish calibration models from the GC and spectral data. The best cross-validated R² values were obtained for total PUFAs, omega-6 (Ω-6) and omega-3 (Ω-3) PUFA (0.79, 0.83 and 0.66, respectively). For individual Ω-3 PUFAs, α-linolenic acid (ALA, C18:3), eicosapentaenoic acid (EPA, C20:5) and docosahexenoic acid (DHA, C22:6) were found to have the best R² values (0.82, 0.76 and 0.81, respectively). This study demonstrates that Raman spectroscopy could be used to predict PUFAs with good correlation coefficients on adipocytes, for future on adipocytes physiology or for large scale and high throughput phenotyping in rainbow trout.

Study on crystallization kinetics of dry fractionation products of beef tallow

The dry fractionation beef tallow and their products were analyzed in the dynamic thermodynamic analysis, isothermal analysis and crystallization kinetics analysis in this experiment. Through the dynamic thermodynamic analysis by DSC, the possibility of fine fractionation of beef tallow at 25 °C and 42.9 °C crystallization temperature was obtained. The dynamic thermodynamic analysis of dry fractionation products was carried out, and the linear functions of peak temperature and melting/crystallization rate of beef tallow and its stearic acid mixture were constructed. The crystallization temperature and melting point were obtained by linear function. The isothermal crystallization kinetic model was used to calculate and fit the experimental data by the Avrami model. Beef tallow and its stearic mixture were fitted with the Avrami equation to obtain R 2 ≥ 0.98. This analysis provides an innovative idea and method for thermodynamics and crystallization kinetics of beef tallow.

Genetic architecture and genomic selection of fatty acid composition predicted by Raman spectroscopy in rainbow trout

Background

In response to major challenges regarding the supply and sustainability of marine ingredients in aquafeeds, the aquaculture industry has made a large-scale shift toward plant-based substitutions for fish oil and fish meal. But, this also led to lower levels of healthful n−3 long-chain polyunsaturated fatty acids (PUFAs)—especially eicosapentaenoic (EPA) and docosahexaenoic (DHA) acids—in flesh. One potential solution is to select fish with better abilities to retain or synthesise PUFAs, to increase the efficiency of aquaculture and promote the production of healthier fish products. To this end, we aimed i) to estimate the genetic variability in fatty acid (FA) composition in visceral fat quantified by Raman spectroscopy, with respect to both individual FAs and groups under a feeding regime with limited n-3 PUFAs; ii) to study the genetic and phenotypic correlations between FAs and processing yields- and fat-related traits; iii) to detect QTLs associated with FA composition and identify candidate genes; and iv) to assess the efficiency of genomic selection compared to pedigree-based BLUP selection.

Results

Proportions of the various FAs in fish were indirectly estimated using Raman scattering spectroscopy. Fish were genotyped using the 57 K SNP Axiom™ Trout Genotyping Array. Following quality control, the final analysis contained 29,652 SNPs from 1382 fish. Heritability estimates for traits ranged from 0.03 ± 0.03 (n-3 PUFAs) to 0.24 ± 0.05 (n-6 PUFAs), confirming the potential for genomic selection. n-3 PUFAs are positively correlated to a decrease in fat deposition in the fillet and in the viscera but negatively correlated to body weight. This highlights the potential interest to combine selection on FA and against fat deposition to improve nutritional merit of aquaculture products. Several QTLs were identified for FA composition, containing multiple candidate genes with indirect links to FA metabolism. In particular, one region on Omy1 was associated with n-6 PUFAs, monounsaturated FAs, linoleic acid, and EPA, while a region on Omy7 had effects on n-6 PUFAs, EPA, and linoleic acid. When we compared the effectiveness of breeding programmes based on genomic selection (using a reference population of 1000 individuals related to selection candidates) or on pedigree-based selection, we found that the former yielded increases in selection accuracy of 12 to 120% depending on the FA trait.

Conclusion

This study reveals the polygenic genetic architecture for FA composition in rainbow trout and confirms that genomic selection has potential to improve EPA and DHA proportions in aquaculture species.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08062-7.

Integrated spectral and textural features of hyperspectral imaging for prediction and visualization of stearic acid content in lamb meat

Stearic acid content is an important factor affecting mutton odor. To determine the distribution and content of stearic acid (C18:0) in lamb meat fast and nondestructively, a method integrating spectral and textural data of hyperspectral imaging (900-1700 nm) was proposed in this paper. Firstly, spectral information was obtained and preprocessed. Then, the spectral features were extracted by variable combination population analysis-genetic algorithm (VCPA-GA) and interval variable iterative space shrinking analysis (IVISSA). Subsequently, the prediction models of partial least squares regression (PLSR) and least-squares support vector machines (LSSVMs) were established and compared. The model constructed with SNVD-VCPA-GA-PLSR achieved better performance. To improve the prediction results of the models, the textural features were extracted using a gray-level co-occurrence matrix (GLCM) and fused with spectral features. The optimized model achieved good results, with R_c of 0.8716, RMSEC of 0.0793 g/100 g, RPD_c of 2.398, and R_p of 0.8121 with RMSEP of 0.1481 g/100 g and RPD_p of 1.756. Finally, the spatial distribution of the C18:0 content in lamb meat was visualized using an optimal model. The result indicated that it was feasible to predict and visualize the C18:0 content in lamb meat, providing a way for real-time detection of volatile fatty acid compounds in meat.

Determination of three Unsaturated Fatty Acids in Pressure Ulcer Rats Using A UPLC-MS/MS Method

Background:

The serum levels of Docosahexaenoic Acid (DHA), Eicosapentaenoic Acid (EPA) and Arachidonic Acid (AA) under the state of Pressure Ulcers (PUs) are still unclear.

Introduction:

In order to investigate serum levels of DHA, EPA, and AA in PUs rats, an ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/ MS) method was developed and validated.

Methods:

Chromatographic separation of DHA, EPA, AA was carried out on a BEH C18 column and gradient elute consisted of 5 mM ammonium acetate-0.1% formic acid and acetonitrile. Subsequently, fifty rats were divided into five groups (n=10), four PU groups (A-D) underwent various pressure and release time protocols, with group E as the control. The concentrations of DHA, EPA, AA from five groups were determined by using a validated method.

Results:

The results showed there was good linearity for DHA (327.3/283.4), EPA (301.2/257.0), and AA (303.1/258.9) within 0.05-6.4 μg/mL. In control group, the levels of DHA, AA and EPA were 1.16±0.68, 0.59±0.19 and 0.78±0.21 μg/mL. At the end of modeling, concentrations of DHA, EPA and AA were increased after long and persistent pressure (>8 h). Especially, the level of DHA was significantly higher (P<0.01) than that of control group.

Conclusion:

A stable, rA stable, reliable and accurate UPLC-MS/MS for determination of DHA, EPA, AA in blood was developed. Serum concentrations of DHA, EPA and AA were altered differently after long and persistent pressure (>8 h), and DHA is a remarkable one.eliable and accurate UPLC-MS/MS for determination of DHA, EPA, AA in blood was developed. Serum concentrations of DHA, EPA and AA were altered differently after long and persistent pressure (>8 h), and DHA is a remarkable one.

Label-free Raman mapping of saturated and unsaturated fatty acid uptake, storage, and return toward baseline levels in macrophages

Macrophage uptake and metabolism of fatty acids is involved in a large number of important biological pathways including immune activation and regulation of macrophages, as well as pathological conditions including obesity, atherosclerosis, and others lifestyle diseases. There are few methods available to directly probe both the uptake and later redistribution/metabolism of fatty acids within living cells as well as the potential changes induced within the cells themselves. We use Raman imaging and analysis to evaluate the effects of different fatty acids following their uptake in macrophages. The label-free nature of the methods means that we can evaluate the fatty acid dynamics without modifying endogenous cellular behavior and metabolism.

Development of Meat Products with Healthier Lipid Content: Vibrational Spectroscopy

This review focuses on the importance of developing meat products with healthier lipid content and strategies such as the use of structured lipids to develop these enriched products. The review also conducts a critical analysis of the use of vibrational spectroscopy as a tool to further these developments. Meat and meat products are extensively recognized and consumed in the world. They are an important nutritional contribution in our diet. However, their consumption has also been associated with some negative consequences for health due to some of its components. There are new trends in the design of healthy meat products focusing mainly on improving their composition. From among the different strategies, improving lipid content is the one that has received the most attention. A novel development is the formation of lipid materials based on structured lipids such emulsion gels (EGs) or oil-bulking agents (OBAs) that offer attractive applications in the reformulation of health-enhanced meat products. A deeper interpretation is required of the complicated relationship between the structure of their components and their properties in order to obtain structured lipids and healthier meat products with improved lipid content and acceptable characteristics. To this end, vibrational spectroscopy techniques (Raman and infrared spectroscopy) have been demonstrated to be suitable in the elucidation of the structural characteristics of lipid materials based on structured lipids (EGs or OBAs) and the corresponding reformulated health-enhanced meat products into which these fat replacers have been incorporated. Future research on these structures and how they correlate to certain technological properties could help in selecting the best lipid material to achieve specific technological properties in healthier meat products with improved lipid content.

Raman spectroscopy: A rapid method to assess the effects of pasture feeding on the nutritional quality of butter

The animal diet is a critical variable affecting the composition and functionality of dairy products. As "Grass-Fed" labeling becomes more prominent on the market, rapid and label-free methods for verification of feeding systems are required. This work proposes the use of Raman spectroscopy to study the effects of 3 different experimental cow feeding systems-perennial ryegrass pasture, perennial ryegrass with white clover pasture, and an indoor total mixed ration diet (TMR)-on the nutritional quality of sweet cream butter. The results demonstrate that Raman spectroscopy coupled with multivariate analysis is a promising approach to distinguish butter derived from pasture or conventional TMR feeding systems. A Pearson correlation analysis confirmed high positive correlations between the spectral bin at 1,657 cm^-1, ascribed to the stretching vibrations of C=C bonds, and concentrations of α-linolenic acid and conjugated linolenic acid (CLA) in butter, and in general with the concentration of n-3 and n-3+CLA fatty acids and polyunsaturated fatty acids in the samples. The yellow color indicative of the presence of carotenoids in butter, which has previously been suggested as a biomarker of pasture or "Grass-Fed" feeding, was also positively correlated with the data obtained from the Raman spectra. Raman spectroscopy could also be used to accurately predict indicators of the nutritional quality of butter, such as the thrombogenic index, which showed a strong negative correlation with the spectral bin at 3,023 cm^-1.

Preliminary investigation into the use of Raman spectroscopy for the verification of Australian grass and grain fed beef

Australian grass and grain-fed beef products attract premium prices at sale and several beef processors market beef underwritten by production system claims. This preliminary investigation assessed the feasibility of using Raman spectroscopy to detect differences in the chemical composition of subcutaneous fat from cattle raised in extensive and intensive production systems. Raman spectra, fatty acid composition, β-carotene composition and objective colour measurements were measured on 150 grass and 150 grain-fed cattle. Spectral differences at peaks including 1069 cm^-1, 1127 cm^-1, 1301 cm^-1 and 1445 cm^-1 suggest that Raman spectra is able to detect differences in saturated fatty acids, which were significantly higher in carcases from grain-fed cattle. Differences in spectra at 1658 cm^-1 were observed, however further research is required to investigate the cause of this spectral feature. Overall, this study indicated that Raman spectroscopy is a potential tool for the authentication of beef carcases from grass and grain-fed production systems.

Raman spectroscopy for the differentiation of Arabic coffee genotypes

The objective of this study was to evaluate the ability of Raman spectroscopy to identify the genotype of green coffee beans. Four genotypes of Arabic coffee: one Mundo Novo line (G1) and three Bourbon lines (G2, G3, and G4). The harvest was selected using a wet processing method. Raman spectra of the samples were obtained using a FT-Raman RFS/100 spectrometer in the spectral range of 3500-400 cm^-1. The data were treated using chemometric unsupervised classification tools and supervised analysis. Using the unsupervised analysis (PCA), the apparent tendency of agglomeration between samples G1 and G3 was verified. These differences were present in the spectral bands that are characteristic of fatty acids and kahweol. Based on this information, a classification model to discriminate (PLS-DA) the Mundo Novo and Bourbon samples was utilized. Raman spectroscopy allowed the building of an adequate model to differentiate between coffee genotypes.

Continuous Gradient Temperature Raman Spectroscopy of Fish Oils Provides Detailed Vibrational Analysis and Rapid, Nondestructive Graphical Product Authentication

Background: Gradient temperature Raman spectroscopy (GTRS) applies the continuous temperature gradients utilized in differential scanning calorimetry (DSC) to Raman spectroscopy, providing a new means for rapid high throughput material identification and quality control. Methods: Using 20 Mb three-dimensional data arrays with 0.2 °C increments and first/second derivatives allows complete assignment of solid, liquid and transition state vibrational modes. The entire set or any subset of the any of the contour plots, first derivatives or second derivatives can be utilized to create a graphical standard to quickly authenticate a given source. In addition, a temperature range can be specified that maximizes information content. Results: We compared GTRS and DSC data for five commercial fish oils that are excellent sources of docosahexaenoic acid (DHA; 22:6n-3) and eicosapentaenoic acid (EPA; 20:5n-3). Each product has a unique, distinctive response to the thermal gradient, which graphically and spectroscopically differentiates them. We also present detailed Raman data and full vibrational mode assignments for EPA and DHA. Conclusion: Complex lipids with a variety of fatty acids and isomers have three dimensional structures based mainly on how structurally similar sites pack. Any localized non-uniformity in packing results in discrete “fingerprint” molecular sites due to increased elasticity and decreased torsion.

Advances in Sheep and Goat Meat Products Research

The main goal of this chapter was to review the state of the art in the recent advances in sheep and goat meat products research. Research and innovation have been playing an important role in sheep and goat meat production and meat processing as well as food safety. Special emphasis will be placed on the imaging and spectroscopic methods for predicting body composition, carcass and meat quality. The physicochemical and sensory quality as well as food safety will be referenced to the new sheep and goat meat products. Finally, the future trends in sheep and goat meat products research will be pointed out.

Predicting aged pork quality using a portable Raman device

The utility of Raman spectroscopic signatures of fresh pork loin (1 d & 15 d postmortem) in predicting fresh pork tenderness and slice shear force (SSF) was determined. Partial least square models showed that sensory tenderness and SSF are weakly correlated (R² = 0.2). Raman spectral data were collected in 6 s using a portable Raman spectrometer (RS). A PLS regression model was developed to predict quantitatively the tenderness scores and SSF values from Raman spectral data, with very limited success. It was discovered that the prediction accuracies for day 15 post mortem samples are significantly greater than that for day 1 postmortem samples. Classification models were developed to predict tenderness at two ends of sensory quality as "poor" vs. "good". The accuracies of classification into different quality categories (1st to 4th percentile) are also greater for the day 15 postmortem samples for sensory tenderness (93.5% vs 76.3%) and SSF (92.8% vs 76.1%). RS has the potential to become a rapid on-line screening tool for the pork producers to quickly select meats with superior quality and/or cull poor quality to meet market demand/expectations.

Non-Destructive Spectroscopic Techniques and Multivariate Analysis for Assessment of Fat Quality in Pork and Pork Products: A Review

Fat is one of the most important traits determining the quality of pork. The composition of the fat greatly influences the quality of pork and its processed products, and contribute to defining the overall carcass value. However, establishing an efficient method for assessing fat quality parameters such as fatty acid composition, solid fat content, oxidative stability, iodine value, and fat color, remains a challenge that must be addressed. Conventional methods such as visual inspection, mechanical methods, and chemical methods are used off the production line, which often results in an inaccurate representation of the process because the dynamics are lost due to the time required to perform the analysis. Consequently, rapid, and non-destructive alternative methods are needed. In this paper, the traditional fat quality assessment techniques are discussed with emphasis on spectroscopic techniques as an alternative. Potential spectroscopic techniques include infrared spectroscopy, nuclear magnetic resonance and Raman spectroscopy. Hyperspectral imaging as an emerging advanced spectroscopy-based technology is introduced and discussed for the recent development of assessment for fat quality attributes. All techniques are described in terms of their operating principles and the research advances involving their application for pork fat quality parameters. Future trends for the non-destructive spectroscopic techniques are also discussed.

Continuous gradient temperature Raman spectroscopy from -100 to 40°C yields new molecular models of arachidonic acid and 2-Arachidonoyl-1-stearoyl-sn-glycero-3-phosphocholine

Despite its biochemical importance, a complete Raman analysis of arachidonic acid (AA, 20:4n-6) has never been reported. Gradient temperature Raman spectroscopy (GTRS) applies the temperature gradients utilized in differential scanning calorimetry (DSC) to Raman spectroscopy, providing a straightforward technique to identify molecular rearrangements that occur near and at phase transitions. Herein we utilize the GTRS technique for AA and 1-18:0, 2-20:4n-6 phosphatidyl choline (AAPC) from cryogenic to mammalian body temperatures. 20Mb three-dimensional data arrays with 0.2°C increments and first/second derivatives allowed complete assignment of solid, liquid and transition state vibrational modes. The AA DSC shows a large exothermic peak at -60°C indicating crystallization or a similar major structural change. No exothermic peak of this magnitude was observed in six other unsaturated lipids (DHA, n-3DPA, n-6DPA, LA, ALA, OA). Melting in AA occurs over a large range: (-60 to -35°C): very large frequency offsets and intensity changes correlate with premelting initiating circa -60°C, followed by melting (-37°C). Novel, unique 3D structures for both molecules reveal that AA is not symmetric as a free fatty acid, and it changes significantly when in the sn-2 phospholipid position. Further, different CH and CH₂ sites are unequally elastic and nonequivalent.

Recent advances in rapid and nondestructive determination of fat content and fatty acids composition of muscle foods

Conventional methods for determining fat content and fatty acids (FAs) composition are generally based on the solvent extraction and gas chromatography techniques, respectively, which are time consuming, laborious, destructive to samples and require use of hazard solvents. These disadvantages make them impossible for large-scale detection or being applied to the production line of meat factories. In this context, the great necessity of developing rapid and nondestructive techniques for fat and FAs analyses has been highlighted. Measurement techniques based on near-infrared spectroscopy, Raman spectroscopy, nuclear magnetic resonance and hyperspectral imaging have provided interesting and promising results for fat and FAs prediction in varieties of foods. Thus, the goal of this article is to give an overview of the current research progress in application of the four important techniques for fat and FAs analyses of muscle foods, which consist of pork, beef, lamb, chicken meat, fish and fish oil. The measurement techniques are described in terms of their working principles, features, and application advantages. Research advances for these techniques for specific food are summarized in detail and the factors influencing their modeling results are discussed. Perspectives on the current situation, future trends and challenges associated with the measurement techniques are also discussed.

Raman Spectroscopy of Fish Oil Capsules: Polyunsaturated Fatty Acid Quantitation Plus Detection of Ethyl Esters and Oxidation

Fish oils are the primary dietary source of ω-3 polyunsaturated fatty acids (PUFA), but these compounds are prone to oxidation, and commercial fish oil supplements sometimes contain less PUFA than claimed. These supplements are predominantly sold in softgel capsules. In this work, we show that Fourier transform (FT)-Raman spectra of fish oils (n = 5) and ω-3 PUFA concentrates (n = 6) can be acquired directly through intact softgel (gelatin) capsules. These spectra could be used to rapidly distinguish supplements containing ethyl esters from those containing triacylglyceride oils. Raman spectroscopy calibrated with partial least-squares regression against traditional fatty acid methyl ester analyses by gas chromatography-mass spectrometry could be used to rapidly and nondestructively quantitate PUFA and other fatty acid classes directly though capsules. We also show that FT-Raman spectroscopy can noninvasively detect oxidation with high sensitivity. Oils with peroxide values of as low as 10 mequiv kg^-1, which are on the cusp of falling outside of specification, could be readily distinguished from oils that were within specification (7 mequiv kg^-1).

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.

Prediction of total fatty acid parameters and individual fatty acids in pork backfat using Raman spectroscopy and chemometrics: Understanding the cage of covariance between highly correlated fat parameters

This study investigates how Partial Least Squares regression models for predicting individual fatty acids (FAs) and total FA parameters depend on Raman spectral variation associated with the iodine value in pork backfat. The backfat was sampled from pigs, which were fed with different dietary fat sources and levels. Good correlations between the Raman spectra and the total FA composition parameters and most individual FAs were obtained (R(CV)(2)=0.78-0.90). However, the predictions of the individual FAs are indirect and to a high degree depend on co-variance with the total FA parameters. A new procedure was demonstrated for identifying and characterizing such indirect or non-targeted calibrations. This information is very useful when Raman spectroscopy or other vibrational spectroscopic techniques are used to predict non-targeted quality parameters such as individual FAs as they may lead to inaccurate predictions of future sample if the underlying covariance structure is changed e.g. by new dietary regimes or genotypes.

Complementary analysis of tissue homogenates composition obtained by Vis and NIR laser excitations and Raman spectroscopy

Raman spectroscopy and four excitation lines in the visible (Vis: 488, 532, 633 nm) and near infrared (NIR: 785 nm) were used for biochemical analysis of rat tissue homogenates, i.e. myocardium, brain, liver, lung, intestine, and kidney. The Vis Raman spectra are very similar for some organs (brain/intestines and kidney/liver) and dominated by heme signals when tissues of lung and myocardium were investigated (especially with 532 nm excitation). On the other hand, the NIR Raman spectra are specific for each tissue and more informative than the corresponding ones collected with the Vis excitations. The spectra analyzed without any special pre-processing clearly illustrate different chemical composition of each tissue and give information about main components e.g. lipids or proteins, but also about the content of some specific compounds such as amino acid residues, nucleotides and nucleobases. However, in order to obtain the whole spectral information about tissues complex composition the spectra of Vis and NIR excitations should be collected and analyzed together. A good agreement of data gathered from Raman spectra of the homogenates and those obtained previously from Raman imaging of the tissue cross-sections indicates that the presented here approach can be a method of choice for an investigation of biochemical variation in animal tissues. Moreover, the Raman spectral profile of tissue homogenates is specific enough to be used for an investigation of potential pathological changes the organism undergoes, in particular when supported by the complementary FTIR spectroscopy.

Prediction of intramuscular fat content and major fatty acid groups of lamb M. longissimus lumborum using Raman spectroscopy

A hand held Raman spectroscopic device was used to predict intramuscular fat (IMF) levels and the major fatty acid (FA) groups of fresh intact ovine M. longissimus lumborum (LL). IMF levels were determined using the Soxhlet method, while FA analysis was conducted using a rapid (KOH in water, methanol and sulphuric acid in water) extraction procedure. IMF levels and FA values were regressed against Raman spectra using partial least squares regression and against each other using linear regression. The results indicate that there is potential to predict PUFA (R(2)=0.93) and MUFA (R(2)=0.54) as well as SFA values that had been adjusted for IMF content (R(2)=0.54). However, this potential was significantly reduced when correlations between predicted and observed values were determined by cross validation (R(2)cv=0.21-0.00). Overall, the prediction of major FA groups using Raman spectra was more precise (relative reductions in error of 0.3-40.8%) compared to the null models.

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.

Review: Canadian beef grading – Opportunities to identify carcass and meat quality traits valued by consumers

Aalhus, J. L., López-Campos, Ó., Prieto, N., Rodas-González, A., Dugan, M. E. R., Uttaro, B. and Juárez, M. 2014. Review: Canadian beef grading – Opportunities to identify carcass and meat quality traits valued by consumers. Can. J. Anim. Sci. 94: 545–556. Beef value is in the eye, mouth or mind of the consumer; however, currently, producers are paid on the basis of carcass grade. In general, affluent consumers are becoming more discerning and are willing to pay for both credence and measureable quality differences. The Canadian grading system for youthful carcasses identifies both lean yield and quality attributes, whereas mature carcasses are broadly categorized. Opportunities exist to improve the prediction of lean meat yield and better identify meat quality characteristics in youthful beef, and to obtain additional value from mature carcasses through muscle profiling. Individual carcass identification along with development of database systems like the Beef InfoXchange System (BIXS) will allow a paradigm shift for the industry as traits of economic value can be easily identified to improve marketing value chains. In the near future, developing technologies (e.g., grade cameras, dual energy X-ray absorptiometry, and spectroscopic methods such as near infrared spectroscopy, Raman spectroscopy and hyperspectral imaging) will be successfully implemented on-line to identify a multitude of carcass and quality traits of growing importance to segments of the consuming population.

Determination of omega-3 fatty acids in fish oil supplements using vibrational spectroscopy and chemometric methods

The potential of Fourier transform infrared (FT-IR), near-infrared (NIR), and Raman spectroscopic techniques combined with partial least squares (PLS) regression (PLSR) to predict concentrations of eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), and total omega-3 fatty acids (n-3 FAs) in fish oil supplements was investigated. FT-IR spectroscopy predicted EPA (coefficient of determination (R(2)) of 0.994, standard error of cross-validation (SECV) of 2.90%, and standard error of prediction (SEP) of 2.49%) and DHA (R(2) = 0.983, SECV = 2.89%, and SEP = 2.55%) with six to seven PLS factors, whereas a simpler PLS model with two factors was obtained for total n-3 FAs (R(2) = 0.985, SECV = 2.73%, and SEP = 2.75%). Selected regions in the NIR spectra gave models with good performances and predicted EPA (R(2) = 0.979, SECV = 2.43%, and SEP = 3.11%) and DHA (R(2) = 0.972, SECV = 2.34%, and SEP = 2.60%) with four to six PLS factors. Both the whole and selected NIR regions gave simple models (two PLS factors) with similar results (R(2) = 0.997, SECV = 2.18%, and SEP = 1.60%) for total n-3 FAs. The whole and selected regions of Raman spectra provided models with comparable results and predicted EPA (R(2) = 0.977, SECV = 3.18%, and SEP = 2.73%) and DHA (R(2) = 0.966, SECV = 3.31%, and SEP = 2.56%) with seven to eight PLS factors, whereas a simpler model (three PLS factors) with R(2) = 0.993, SECV = 2.82%, and SEP = 3.27% was obtained for total n-3 FAs. The results demonstrated that FT-IR, NIR, and Raman spectroscopy combined with PLSR can be used as simple, fast, and nondestructive methods for quantitative analysis of EPA, DHA, and total n-3 FAs. FT-IR and NIR spectroscopy, in particular, have the potential to be applied in process industries during production of fish oil supplements.

A novel approach for subsurface through-skin analysis of salmon using spatially offset Raman spectroscopy (SORS)

In the present study, the possibility of employing spatially offset Raman spectroscopy (SORS) in the qualitative and quantitative characterization of quality parameters of salmon through the skin has been explored. A laboratory-based SORS setup comprising an 830 nm laser was employed, and intact samples and model samples made of salmon tissue constituents were used to investigate the penetration of Raman signals through the dark and light part of salmon skin. Intact salmon samples with both dark and light skin were measured at different spatial offsets. When using spatial offsets in the range of 5-6 mm, the results clearly show that information regarding fatty acid composition and carotenoid content could be obtained from both dark and light parts of the skin. Similar information could not be obtained using conventional backscattering Raman spectroscopy. Model samples of ground salmon spiked with either solutions of carotenoids or a range of vegetable oils were also measured, and at a spatial offset of 5 mm, a clear relationship between Raman carotenoid band intensities and carotenoid concentrations in the model samples was revealed. In addition, high correlations for the estimation of iodine values (i.e., fatty acid unsaturation) could be obtained for SORS measurements through light and dark parts of the salmon skin. A crude estimate suggested that information from around 5 mm beneath the surface area of the salmon skin could be obtained. The choice of a laser line in the near-infrared region is a major prerequisite for successful through-skin analysis of salmon. This feasibility study could pave the way for future Raman analysis of intact salmon.

Fluorescence Rejection by Shifted Excitation Raman Difference Spectroscopy at Multiple Wavelengths for the Investigation of Biological Samples

Shifted excitation Raman difference spectroscopy (SERDS) was applied for an effective fluorescence removal in the Raman spectra of meat, fat, connective tissue, and bone from pork and beef. As excitation light sources, microsystem diode lasers emitting at 783 nm, 671 nm, and 488 nm each incorporating two slightly shifted excitation wavelengths with a spectral difference of about 10 cm−1 necessary for SERDS operation were used. The moderate fluorescence interference for 783 nm excitation as well as the increased background level at 671 nm was efficiently rejected using SERDS resulting in a straight horizontal baseline. This allows for identification of all characteristic Raman signals including weak bands which are clearly visible and overlapping signals that are resolved in the SERDS spectra. At 488 nm excitation, the spectra contain an overwhelming fluorescence interference masking nearly all Raman signals of the probed tissue samples. However, the essentially background-free SERDS spectra enable determining the majority of characteristic Raman bands of the samples under investigation. Furthermore, 488 nm excitation reveals prominent carotenoid signals enhanced due to resonance Raman scattering which are present in the beef samples but absent in pork tissue enabling a rapid meat species differentiation.