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

In-line Raman spectroscopy for characterization of an industrial poultry raw material stream

In this work, we evaluated the feasibility of Raman spectroscopy as an in-line raw material characterization tool for industrial process control of the hydrolysis of poultry rest raw material. We established calibrations (N = 59) for fat, protein, ash (proxy for bone) and hydroxyproline (proxy for collagen) in ground poultry rest raw material. Calibrations were established in the laboratory using poultry samples with high compositional variation. Samples were measured using a wide area illumination Raman probe at varying working distance (6 cm, 9 cm, 12 cm) and probe tilt angle (0°, 30°) to mimic expected in-line variations in the measurement situation. These moderate variations did not significantly affect performance for any analytes. The obtained calibrations were tested in-line with continuous measurements of the ground poultry by-product stream at a commercial hydrolysis facility over the course of two days. Measurements were acquired under demanding conditions, e.g. large variations in working distance. Reasonable estimates of compositional trends were obtained. Validation samples (N = 19) were also reasonably well predicted, with RMSEPcorr = [0.14, 1.37, 2.36, 1.51]% for hydroxyproline, protein, fat and ash, respectively. However, there were indications that further calibration development and robustification of pre-processing would be advantageous, particularly with respect to hydroxyproline and protein models. It is the authors' impression that with such efforts, potentially in combination with development of practical measurement setup, the use of Raman spectroscopy as a process control tool for the hydrolysis of poultry rest raw materials is within reach.

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 R2_CV = 0.96 for Raman at 2s exposure and R2_CV = 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.

Pig adipose tissue of two different breeds and locations: morphology and Raman studies

According to the recent data, there are 4–5-local pig breeds left in Russia by now. Livni is among them. This breed is characterized by high fat content. Back fat has been analyzed earlier. We aimed to assess fat morphometrics from other localizations in pigs. Sacral, axillary, and perirenal fat samples from 6-month-old Duroc and Livni pig breeds were analyzed using morphological and Raman-based techniques. Livni adipocytes were characterized by dense packing with a polyhedron-like structure. In Duroc fat, they were more rounded (spherical). A “two-phase” cell disperse was identified in all samples. Fat cells in Livni pigs were bigger than those in the Duroc breed: 70–102%; 15–18 and 26% for sacral, axillary, and perirenal locations. Differences in the intensity of the Raman signal between the samples were found: in the samples of subcutaneous adipose tissue, more intense peaks were observed, which are responsible for unsaturation; the samples of Livni axillary fat were characterized by greater unsaturation than sacral fat. Livni and Duroc adipocytes differ from each other in form and size and the difference depends on location. Pork fat from local breeds is expected to have potentially more health protecting (for animals) and health promoting (for consumers) properties.

Feasibility of In-Line Raman Spectroscopy for Quality Assessment in Food Industry: How Fast Can We Go?

Raman spectroscopy is a viable tool within process analytical technologies due to recent technological advances. In this article, we evaluate the feasibility of Raman spectroscopy for in-line applications in the food industry by estimating the concentration of the fatty acids EPA + DHA in ground salmon samples (n = 63) and residual bone concentration in samples of mechanically recovered ground chicken (n = 66). The samples were measured under industry like conditions: They moved on a conveyor belt through a dark cabinet where they were scanned with a wide area illumination standoff Raman probe. Such a setup should be able to handle relevant industrial conveyor belt speeds, and it was studied how different speeds (i.e., exposure times) influenced the signal-to-noise ratio (SNR) of the Raman spectra as well as the corresponding model performance. For all samples we applied speeds that resulted in 1 s, 2 s, 4 s, and 10 s exposure times. Samples were scanned in both heterogenous and homogenous state. The slowest speed (10 s exposure) yielded prediction errors (RMSECV) of 0.41%EPA + DHA and 0.59% ash for the salmon and chicken data sets, respectively. The more in-line relevant exposure time of 1 s resulted in increased RMSECV values, 0.84% EPA + DHA and 0.84% ash, respectively. The increase in prediction error correlated closely with the decrease in SNR. Further improvements of model performance were possible through different noise reduction strategies. Model performance for homogenous and heterogenous samples was similar, suggesting that the presented Raman scanning approach has the potential to work well also on intact heterogenous foods. The estimation errors obtained at these high speeds are likely acceptable for industrial use, but successful strategies to increase SNR will be key for widespread in-line use in the food industry.

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.

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.

Profiling of Unsaturated Lipids by Raman Spectroscopy Directly on Solid-Phase Microextraction Probes

Lipids play a critical role in cellular signaling, energy storage, and the construction of cellular membranes. In this paper, we propose a novel on-site approach for detecting and differentiating enriched unsaturated lipids based on the direct coupling of SPME probes with Raman spectroscopy. To this end, different SPME particles, namely, hydrophilic-lipophilic balanced (HLB), mixed-mode (C8-SCX), and C18, were embedded in polyacrylonitrile (PAN) and tested for their efficacy as biocompatible coatings. The C18/PAN coating showed less background interference compared to the other sorbent materials during the analysis of unsaturated lipids. In addition, different SPME parameters that influence extraction efficiency, such as extraction temperature, extraction time, and washing solvent, were also investigated. Our results indicate a clear dependence between the Raman band intensity related to the number of double bonds in fatty acids mixture and the number of double bonds in a fatty acid. Our findings further show that Raman spectroscopy is especially useful for the analysis of lipid unsaturation, which is calculated as the ratio of n(C═C)/n(CH₂) using the intensities of the Raman bands at 1655/1445 cm^-1. Furthermore, the developed protocol reveals great SPME activity and high detection ability for several unsaturated lipids in different complex matrixes, such as cod liver oil. Finally, the applicability of this technology was demonstrated via the characterization of cod liver oil and other vegetable oils. Thus, the proposed SPME-Raman spectroscopy approach has a great future potential in food, environmental, clinical, and biological applications.

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 (R²_CV) 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 (R²_CV 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.

Raman and Fluorescence Profiles Modifications of Muscular and Adipose Tissues Exposed to Low Energy X-ray Beams

This work aims to investigate changes induced by low-energy radiation in adipose and muscular tissues employing autofluorescence and Raman spectroscopic techniques. X-ray beams expositions with 25 and 35 kV at 0.11, 1.1, and 2.1 Gy radiation dose levels were applied. Changes in Raman line intensities at specific bands assigned to collagen, proteins, and lipids were observed. Autofluorescent analysis exhibit variations in the collagen and nicotinamide adenine dinucleotide emission (NADH), resulting from the structural modifications, variations on the reduced/oxidized fluorophores equilibrium followed by radiation exposure. Results show that Raman and fluorescence spectroscopy are suitable techniques to evaluate radiation effects on biomolecules even at low radiation doses and energies.

Raman Spectroscopy-Based 3D Analysis of Odontogenic Differentiation of Human Dental Pulp Stem Cell Spheroids

Numerous efforts have been made to establish three-dimensional (3D) cell cultures that mimic the structure, cell composition, and functions of actual tissues and organs in vitro; however, owing to its intrinsic complexity, precise characterization of 3D differentiation remains challenging and often results in high variations in the resulting differentiated spheroids. This study reports a 3D Raman mapping-based analytical method that helps us to identify the crucial factors responsible for inducing variability in differentiated stem cell spheroids. Human dental pulp stem cell spheroids were generated at various cell densities using the hanging drop (HD) and molded parafilm-based (MP) methods and were then further subjected to odontogenic differentiation. Thereafter, the 3D cellular differentiation in these spheroids was analyzed based on three different Raman peaks, namely, 960, 1156/1528, and 2935 cm^-1, which correspond to hydroxyapatite (HA, odontogenic differentiation marker), β-carotene (precursor of HA), and proteins/cellular components (cell reference). By correlating such cell differentiation-related peaks and water/medium peaks (3400 cm^-1), we discovered that the diffusion of the medium containing various nutrients and differentiation factors was crucial in determining the variations in 3D differentiation of stem cell spheroids. Odontogenic differentiation was majorly induced at the outer shell of HD spheroids (up to ∼20 μm), whereas odontogenic differentiation was markedly induced in MP spheroids (up to 40-50 μm). Considering the challenges associated with high variations in spheroid and organoid differentiation, we conclude that the proposed Raman-based 3D analysis plays a pivotal role in stem cell-based regenerative therapy and drug screening.

Evaluating low- mid- and high-level fusion strategies for combining Raman and infrared spectroscopy for quality assessment of red meat

The implementation of Raman and infrared spectroscopy with three data fusion strategies to predict pH and % IMF content of red meat was investigated. Raman and FTIR systems were utilized to assess quality parameters of intact red meat. Quantitative models were built using PLS, with model performances assessed with respect to the determination coefficient (R²), root mean square error and normalized root mean square error (NRMSEP). Results obtained on validation against an independent test set show that the high-level fusion strategy had the best performance in predicting the observed pH; with R_P² and NRMSEP values of 0.73 and 12.9% respectively, whereas low-level fusion strategy showed promise in predicting % IMF (NRMSEP = 8.5%). The fusion of data from more than one technique at low and high level resulted in improvement in the model performances; highlighting the possibility of information enhancement.

Exploration of Principal Component Analysis: Deriving Principal Component Analysis Visually Using Spectra

Spectroscopy rapidly captures a large amount of data that is not directly interpretable. Principal component analysis is widely used to simplify complex spectral datasets into comprehensible information by identifying recurring patterns in the data with minimal loss of information. The linear algebra underpinning principal component analysis is not well understood by many applied analytical scientists and spectroscopists who use principal component analysis. The meaning of features identified through principal component analysis is often unclear. This manuscript traces the journey of the spectra themselves through the operations behind principal component analysis, with each step illustrated by simulated spectra. Principal component analysis relies solely on the information within the spectra, consequently the mathematical model is dependent on the nature of the data itself. The direct links between model and spectra allow concrete spectroscopic explanation of principal component analysis , such as the scores representing "concentration" or "weights". The principal components (loadings) are by definition hidden, repeated and uncorrelated spectral shapes that linearly combine to generate the observed spectra. They can be visualized as subtraction spectra between extreme differences within the dataset. Each PC is shown to be a successive refinement of the estimated spectra, improving the fit between PC reconstructed data and the original data. Understanding the data-led development of a principal component analysis model shows how to interpret application specific chemical meaning of the principal component analysis loadings and how to analyze scores. A critical benefit of principal component analysis is its simplicity and the succinctness of its description of a dataset, making it powerful and flexible.

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.

Rapid discrimination of intact beef, venison and lamb meat using Raman spectroscopy

With increasing demand for fast and reliable techniques for intact meat discrimination, we explore the potential of Raman spectroscopy in combination with three chemometric techniques to discriminate beef, lamb and venison meat samples. Ninety (90) intact red meat samples were measured using Raman spectroscopy, with the acquired spectral data preprocessed using a combination of rubber-band baseline correction, Savitzky-Golay smoothing and standard normal variate transformation. PLSDA and SVM classification were utilized in building classification models for the meat discrimination, whereas PCA was used for exploratory studies. Results obtained using linear and non-linear kernel SVM models yielded sensitivities of over 87 and 90 % respectively, with the corresponding specificities above 88 % on validation against a test set. The PLSDA model yielded over 80 % accuracy in classifying each of the meat specie. PLSDA and SVM classification models in combination with Raman spectroscopy posit an effective technique for red meat discrimination.

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.

Correlation between saturated fatty acid chain-length and intermolecular forces determined with terahertz spectroscopy

We measured crystalline (C-form) saturated fatty acids with even carbon numbers ranging from 12 to 20 using temperature dependent terahertz time-domain spectroscopy (THz-TDS). Absorption features between 0.5 and 3 THz were identified at temperatures from 96 K to 293 K, and a systematic red-shift was obvserved with the increasing carbon chain length. The origins of these absorption bands were uncovered using state-of-the-art ab initio density functional theory (DFT) calculations. Similar vibrational motions in the absorption bands of the different materials highlight the unique role that THz-TDS has for probing weak non-covalent interactions in these materials. Our results showcase the utility of the terahertz region, which is beyond the scope of related vibrational techniques, providing direct evidence of the effect of chain length on the intermolecular interactions of these molecules.

Ultra-low background Raman sensing using a negative-curvature fibre and no distal optics

Measuring Raman spectra through an optical fibre is usually complicated by the high intrinsic Raman scatter of the fibre material. Common solutions such as the use of multiple fibres and distal optics are complex and bulky. We demonstrate the use of single novel hollow-core negative-curvature fibres (NCFs) for Raman and surface-enhanced Raman spectroscopy (SERS) sensing using no distal optics. The background Raman emission from the silica in the NCF was at least 1000× smaller than in a conventional solid fibre, while maintaining the same collection efficiency. We transmitted pump light from a 785-nm laser through the NCF, and we collected back the weak Raman spectra of different distal samples, demonstrating the fibre probe can be used for measurements of weak Raman and SERS signals that would otherwise overlap spectrally with the silica background. The lack of distal optics and consequent small probe diameter (<0.25 mm) enable applications that were not previously possible.

Phosphoric acid and phosphorylation levels are potential biomarkers indicating developmental competence of matured oocytes

We identified biomarkers for mice oocyte maturation in metaphase II in vivo and in situ using Raman spectroscopy.

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.

Analytical Techniques in Lipidomics: State of the Art

Current studies related to lipid identification and determination, or lipidomics in biological samples, are one of the most important issues in modern bioanalytical chemistry. There are many articles dedicated to specific analytical strategies used in lipidomics in various kinds of biological samples. However, in such literature, there is a lack of articles dedicated to a comprehensive review of the actual analytical methodologies used in lipidomics. The aim of this article is to characterize the lipidomics methods used in modern bioanalysis according to the methodological point of view: (1) chromatography/separation methods, (2) spectroscopic methods and (3) mass spectrometry and also hyphenated methods. In the first part, we discussed thin layer chromatography (TLC), high-pressure liquid chromatography (HPLC), gas chromatography (GC) and capillary electrophoresis (CE). The second part includes spectroscopic techniques such as Raman spectroscopy (RS), Fourier transform infrared spectroscopy (FT-IR) and nuclear magnetic resonance (NMR). The third part is a synthetic review of mass spectrometry, matrix-assisted laser desorption/ionization (MALDI), hyphenated methods, which include liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS) and also multidimensional techniques. Other aspects are the possibilities of the application of the described methods in lipidomics studies. Due to the fact that the exploration of new methods of lipidomics analysis and their applications in clinical and medical studies are still challenging for researchers working in life science, we hope that this review article will be very useful for readers.

Non-invasive Quantitative Analysis of Specific Fat Accumulation in Subcutaneous Adipose Tissues using Raman Spectroscopy

Subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and fat beneath the dermis layer were investigated using a ball lens top hollow optical fiber Raman probe (BHRP). Hamsters were fed with trilinolein (TL) and tricaprin (TC) for six weeks and measurements were carried out every two weeks. The BHRP with an 800 μm diameter fused-silica ball lens was able to obtain information on the subcutaneous fat in a totally non-invasive manner. Changes in the concentration of TL and TC during the treatment were analyzed, and the relationship between fat accumulation and dietary fat was studied. It was found that SAT had, in general, a higher degree of unsaturation than VAT. The accumulation rate of TC found in SAT and VAT was 0.52 ± 0.38 and 0.58 ± 0.4%, respectively, while the TL accumulation rate was 4.45 ± 1.6 and 4.37 ± 2.4%, respectively. The results suggest different metabolic pathways for TC, a typical medium-chain fatty acid, and TL, a long-chain unsaturated fatty acid. Raman subsurface spectra were successfully obtained and used to analyze the subcutaneous fat layer. The accumulation rates of TL and TC found in skin fat were 5.01 ± 3.53% and 0.45 ± 0.36%, respectively. The results demonstrate the high feasibility of Raman spectroscopy for non-invasive analysis of adipose tissue.

Wide-field spontaneous Raman spectroscopy imaging system for biological tissue interrogation

Raman spectroscopy has shown great promise as a method to discriminate between cancerous and normal tissue/cells for a range of oncology applications using microscopy and tissue interrogation instruments such as handheld probes and needles. Here we are presenting preliminary steps toward the development of a practical handheld macroscopic Raman spectroscopy instrument, demonstrating its capabilities to discriminate between different biological tissue types during ex vivo porcine experiments. The novel probe design can image a field of view of 25  mm² with a spatial resolution <100  μm and an average spectral resolution of 95  cm^-1, covering the fingerprint region between 450 to 1750  cm^-1. The ability of the system to produce tissue maps based on molecular characteristics is demonstrated using a neural network machine learning technique.

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.

Analysis of the effects of dietary fat on body and skin lipids of hamsters by Raman spectroscopy

Raman spectroscopy has previously been applied for studying lipid metabolism. In this study, a ball lens-installed hollow optical fiber Raman probe (BHRP) was used for the noninvasive measurement of skin lipids in hamsters. Our analysis suggested that multi-unsaturated lipids, once converted into a structure containing conjugated double bonds, were oxidized to form peroxides. These results were applied for analyzing lipid metabolism in adipose and skin tissues in hamsters fed tricaprin, saturated medium-chain triglyceride and trilinolein, unsaturated long-chain triglyceride fat diets. Unsaturated lipids formed conjugated structures in skin tissue but not in adipose tissue. Principal component analysis (PCA) revealed that the dietary fat intake correlated strongly with lipid composition in body and skin tissues. Hence, the present results successfully demonstrate that Raman spectroscopy with a BHRP can be a powerful tool for analyzing lipid metabolism.

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.

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.

In situ Raman spectrometric analysis of crystallinity and crystal polymorphism of fat in porcine adipose tissue

From the adipose tissues of pork carcasses stored in a refrigerator, Raman spectra were observed in situ by a portable Raman spectrometer. The observed Raman spectra, which were almost completely due to fat, showed clear dependence on the refrigeration time and carcass temperature. This dependence reflected an increase in the crystallinity of the fat and a change in the fraction of the β' polymorph. Evidence of changes in the packing order of the aliphatic chains of acylglycerol molecules was obtained, and the changes lasted for a long time after the temperature reached the lowest point (4.3 °C). Possibilities of using Raman spectrometry as a tool for routine monitoring of the conditions of carcasses as well as for research on the improvement of the mechanical strength of the adipose tissue are discussed.

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.

Fluorescence suppression using wavelength modulated Raman spectroscopy in fiber-probe-based tissue analysis

In the field of biomedical optics, Raman spectroscopy is a powerful tool for probing the chemical composition of biological samples. In particular, fiber Raman probes play a crucial role for in vivo and ex vivo tissue analysis. However, the high-fluorescence background typically contributed by the auto fluorescence from both a tissue sample and the fiber-probe interferes strongly with the relatively weak Raman signal. Here we demonstrate the implementation of wavelength-modulated Raman spectroscopy (WMRS) to suppress the fluorescence background while analyzing tissues using fiber Raman probes. We have observed a significant signal-to-noise ratio enhancement in the Raman bands of bone tissue, which have a relatively high fluorescence background. Implementation of WMRS in fiber-probe-based bone tissue study yielded usable Raman spectra in a relatively short acquisition time (∼30  s), notably without any special sample preparation stage. Finally, we have validated its capability to suppress fluorescence on other tissue samples such as adipose tissue derived from four different species.

Fast and minimally invasive determination of the unsaturation index of white fat depots by micro-Raman spectroscopy

In the last 20 years increasing interest has been devoted to the investigation of white adipose tissue (WAT) because hypo- or hyperfunction of WAT is involved in the pathogenesis of obesity and other pathologies. The investigation and discrimination of different characteristics in adipose tissues by means of spectroscopic techniques appears as a topic of current interest, also in view of possible medical-technological applications. The aim of this work was to establish micro-Raman spectroscopy as a tool for the characterization of mammals fat tissue. After preliminary tests aimed at defining a suitable sample preparation protocol, Raman spectra of WAT specimens excised from mice of different ages were recorded in the energy range 750-3,350 cm⁻¹. Quantitative values of the unsaturation index were obtained through the calibration with HR-NMR spectra of lipid extracts. Raman spectroscopy detected a sharp increase in the unsaturation index between 22 and 30 days of age in close correspondence with the weaning of mice (21 days). The present results show that Raman spectroscopy is an inexpensive, fast and robust technique to analyze the unsaturation index of mammals fat tissues that could be routinely used in bioptic samples.

Sclera as a surrogate marker for determining AGE-modifications in Bruch's membrane using a Raman spectroscopy-based index of aging

PURPOSE

Raman spectroscopy is an effective probe of advanced glycation end products (AGEs) in Bruch's membrane. However, because it is the outermost layer of the retina, this extracellular matrix is difficult to analyze in vivo with current technology. The sclera shares many compositional characteristics with Bruch's membrane, but it is much easier to access for in vivo Raman analysis. This study investigated whether sclera could act as a surrogate tissue for Raman-based investigation of pathogenic AGEs in Bruch's membrane.

METHODS

Human sclera and Bruch's membrane were dissected from postmortem eyes (n = 67) across a wide age range (33-92 years) and were probed by Raman spectroscopy. The biochemical composition, AGEs, and their age-related trends were determined from data reduction of the Raman spectra and compared for the two tissues.

RESULTS

Raman microscopy demonstrated that Bruch's membrane and sclera are composed of a similar range of biomolecules but with distinct relative quantities, such as in the heme/collagen and the elastin/collagen ratios. Both tissues accumulated AGEs, and these correlated with chronological age (R(2) = 0.824 and R(2) = 0.717 for sclera and Bruch's membrane, respectively). The sclera accumulated AGE adducts at a lower rate than Bruch's membrane, and the models of overall age-related changes exhibited a lower rate (one-fourth that of Bruch's membrane) but a significant increase with age (P < 0.05).

CONCLUSIONS

The results suggest that the sclera is a viable surrogate marker for estimating AGE accumulation in Bruch's membrane and for reliably predicting chronological age. These findings also suggest that sclera could be a useful target tissue for future patient-based, Raman spectroscopy studies.

Identifying the spatial distribution of vitamin E, pulmonary surfactant and membrane lipids in cells and tissue by confocal Raman microscopy

Every organ compromises of several different cell types. When studying the effects of a chosen compound within this organ or tissue uptake, localisation, metabolism, and the effect itself can be expected to differ between cells. Using the example of Vitamin E in pulmonary tissue we introduce confocal Raman Microscopy as a superior method to localise lipid-soluble compounds within tissues and cells. We describe the analyses of vitamin E, its oxidation products, and metabolites as well as pulmonary surfactant phospholipids in fixed lung tissue sections. Examples of main structural membrane lipids (PC, cholesterol) and an example of a lipid-signalling molecule (ceramide) are also included. Confocal Raman microscopy is a non-destructive optical method of analysing chemical and physical composition of solids, liquids, gases, gels, and solutions. The method is rich in information allowing discrimination of chemically similar molecules (including geometric isomers) and sensitive monitoring of subtle physical interactions. Additionally, Raman spectroscopy is relatively insensitive to water allowing the analysis of aqueous solutions and suspensions typical in biochemistry. In contrast, Raman spectroscopy is sensitive to non-polar molecules making it ideal for lipidomics research.

Raman spectroscopic prediction of the solid fat content of New Zealand anhydrous milk fat

The functionality of anhydrous milk fat (AMF) is determined from solid fat content (SFC) and triacylglycerol (TG) profiles, parameters traditionally measured using nuclear magnetic resonance and high pressure liquid chromatography respectively. Raman spectroscopy coupled with partial least squares (PLS) analysis has been assessed as an alternative method for SFC and TG class quantification. Sample temperature at which the Raman spectra were collected, method of spectral preprocessing and type of PLS analysis were all investigated and found to significantly affect the resulting calibrations (as parameterized by root mean square error of cross validation). Physically heterogeneous AMF samples held at 20 °C were shown to allow reliable SFC predictions on the basis of collected Raman spectra. In contrast to SFC calibrations, physically homogenous samples in a liquid form were ideal for TG class concentration predictions, however, not all TG classes could be reliably predicted.

Determination of omega-6 and omega-3 fatty acids in pork adipose tissue with nondestructive Raman and fourier transform infrared spectroscopy

In order to predict omega-6 and omega-3 fatty acids in the diet of humans, seventy-three pork back fat adipose tissue samples were measured with Raman spectroscopy directly on adipose tissue and on melted fat. Melted fat samples were, in addition, measured with Fourier transform infrared (FT-IR) spectroscopy. Gas chromatography analyses were conducted as the reference analysis. Partial least squares regression (PLSR) was used to calibrate and validate all models predicting omega-3 and omega-6 fatty acids contents from spectra. Omega-6 fatty acids in melted fat measured with FT-IR was predicted with a correlation coefficient (R) of 0.93 and a root mean square error of cross-validation (RMSECV) of 1.61% of the total amount of fatty acids. Raman spectra measured on melted fat gave a prediction of omega-6 fatty acids with R=0.97, and RMSECV=0.99% of total amount of fatty acids. Omega-6 fatty acids were predicted with R=0.94, and RMSECV=1.50% of the total amount of fatty acids using Raman spectra recorded on adipose tissue. For omega-3 fatty acids, the highest R=0.91, and lowest RMSECV=0.23% of the total amount of fatty acids were obtained from Raman spectra acquired on melted fat. FT-IR and Raman spectroscopy may be used as rapid, nondestructive methods to determine omega-6 and omega-3 fatty acids in melted fat. Raman spectroscopy can also be used directly on adipose tissue.