Localisation and identification of polystyrene particles in tissue sections using Raman spectroscopic imaging.

The uptake of microplastic particles (MPP) by organisms is frequently described and poses a potential risk for these organisms and ultimately for humans either through direct uptake or trophic transfer. Currently, the in-situ detection of MPP in organisms is typically based on histological examination of tissue sections after uptake of fluorescently-labelled MPP and is thus not feasible for environmental samples. The alternative approach is purification of MPP from whole organisms or organs by chemical digestion and subsequent spectroscopic detection (FT-IR or Raman). While this approach is feasible for un-labelled particles it goes along with loss of any spatial information related to the location in the tissue. In our study we aimed at providing a workflow for the localisation and identification of non-fluorescent and fluorescent polystyrene (PS) particles (fragments, size range 2-130 µm) in tissue sections of the model organism Eisenia fetida with Raman spectroscopic imaging (RSI). We provide methodological approaches for the preparation of the samples, technical parameters for the RSI measurements and data analysis for PS differentiation in tissue sections. The developed approaches were combined in a workflow for the in-situ analysis of MPP in tissue sections. The spectroscopic analysis requires differentiation of spectra of MPP and interfering compounds, which is challenging given the complexity of tissue. Therefore, a classification algorithm was developed to differentiate PS particles from haem, intestinal contents and surrounding tissue. It allows the differentiation of PS particles from protein in the tissue of E. fetida with an accuracy of 95%. The smallest PS particle detected in the tissue was 2 µm in diameter. We show that it is possible to localise and identify non-fluorescent and fluorescent ingested PS particles directly in tissue sections of E. fetida in the gut lumen and the adjacent tissue.

Preliminary investigation of the use of Raman spectroscopy to predict meat and eating quality traits of beef loins.

A preliminary investigation was conducted to determine the potential for a handheld Raman spectroscopic device to predict sensory traits determined by an untrained consumer panel. Measurement of 45 beef loins (M. longissimus lumborum) was conducted using a 671nm handheld Raman spectroscopic device. Samples were then held frozen until testing by an untrained sensory panel. Sections were also excised to determine shear force values and other indicators of meat quality. Derived models suggest that the Raman spectroscopic device can predict juiciness and tenderness, with correlations between predicted and observed values (ρ) of 0.42 and 0.47, respectively. Spectra indicated that these predictions were characterised by the fatty acid concentration, the hydrophobicity of proteins and the orientation of collagen. However, future research is required to determine the repeatability and robustness of these models on a larger independent data set.

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.

Assessment of tenderness of aged bovine gluteus medius muscles using Raman spectroscopy.

A portable 671 nm Raman system was evaluated as a rapid and non-destructive device for the assessment of beef tenderness using 175 gluteus medius muscles (99 for calibration, 76 for validation) aged at -1 °C and 7 °C for fourteen days. Raman and shear force (SF) measurements were performed with the aged beef. The samples stored at -1 °C showed on average only slightly increased SF values. The correlation of Raman spectra with SF using partial least squares regression yielded cross-validated predictions of SF for both storage temperatures with coefficients of determination R(2)cv=0.33-0.79. Validation with independent samples resulted in predictions with R(2)val=0.33. Using thresholds between 30 and 49N, tough and tender samples could be discriminated with partial least squares discriminant analysis with 70-88% and 59-80% accuracy during cross-validation and validation, respectively. These results demonstrate the principle feasibility to predict the SF and thus toughness of raw, aged gluteus beef cuts with a portable Raman device showing potential for grading beef cuts.

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.

Predicting meat quality traits of ovine m. semimembranosus, both fresh and following freezing and thawing, using a hand held Raman spectroscopic device.

Complementary studies were conducted to determine the potential for a Raman spectroscopic hand held device to predict meat quality traits of fresh lamb m. semimembranosus (topside) after ageing and freezing/thawing. Spectra were collected from 80 fresh muscles at 24h and 5d PM, another 80 muscles were measured at 24h, 5d and following freezing/thawing. Shear force, cooking loss, sarcomere length, colour, particle size, collagen content, pH24, pHu, purge and thaw loss were also measured. Results indicated a potential to predict pHu (R(2)cv=0.59), pH24 (R(2)cv=0.48) and purge (R(2)cv=0.42) using spectra collected 24h PM. L* could be predicted using spectra collected 24h (R(2)cv=0.33) or 5d PM (R(2)cv=0.33). This suggests that Raman spectroscopy is suited to identifying carcases which deviate from the normal metabolic processes and related meat quality traits.

Prediction of pork quality at the slaughter line using a portable Raman device.

Raman spectroscopy is providing a fingerprint of the early postmortem metabolism in meat. In this study, for the first time, Raman spectroscopy is shown to measure and predict quality traits of intact muscles at the slaughtering process. Porcine semimembranosus muscles (N=151) were measured 30-60 min post mortem at the veterinarian line of a commercial abattoir using a prototype handheld Raman device. The Raman spectra were regressed against technologically important quality traits as measured with classic reference methods. Predicting pH35, pH24 and drip loss with PLSR yielded coefficients of determination of 0.75, 0.58 and 0.83 and root mean square errors of cross validation of 0.09, 0.05 and 0.6%, respectively. This is demonstrating the on-line potential of early postmortem Raman spectra to measure pH35 and to predict pH24 and drip loss.

Raman spectroscopy compared against traditional predictors of shear force in lamb m. longissimus lumborum.

A Raman spectroscopic hand held device was used to predict shear force (SF) of 80 fresh lamb m. longissimus lumborum (LL) at 1 and 5days post mortem (PM). Traditional predictors of SF including sarcomere length (SL), particle size (PS), cooking loss (CL), percentage myofibrillar breaks and pH were also measured. SF values were regressed against Raman spectra using partial least squares regression and against the traditional predictors using linear regression. The best prediction of shear force values used spectra at 1day PM to predict shear force at 1day which gave a root mean square error of prediction (RMSEP) of 13.6 (Null=14.0) and the R(2) between observed and cross validated predicted values was 0.06 (R(2)cv). Overall, for fresh LL, the predictability SF, by either the Raman hand held probe or traditional predictors was low.

Predicting tenderness of fresh ovine semimembranosus using Raman spectroscopy.

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

Preliminary investigation on the relationship of Raman spectra of sheep meat with shear force and cooking loss.

A prototype handheld Raman system was used as a rapid non-invasive optical device to measure raw sheep meat to estimate cooked meat tenderness and cooking loss. Raman measurements were conducted on m. longissimus thoracis et lumborum samples from two sheep flocks from two different origins which had been aged for five days at 3-4°C before deep freezing and further analysis. The Raman data of 140 samples were correlated with shear force and cooking loss data using PLS regression. Both sample origins could be discriminated and separate correlation models yielded better correlations than the joint correlation model. For shear force, R(2)=0.79 and R(2)=0.86 were obtained for the two sites. Results for cooking loss were comparable: separate models yielded R(2)=0.79 and R(2)=0.83 for the two sites. The results show the potential usefulness of Raman spectra which can be recorded during meat processing for the prediction of quality traits such as tenderness and cooking loss.

The use of surface-enhanced Raman scattering (SERS) for detection of PAHs in the Gulf of Gdansk (Baltic Sea).

A field operable surface enhanced Raman scattering (SERS) sensor system was applied for the first time under real conditions for the detection of polycyclic aromatic hydrocarbons (PAHs) as markers for petroleum hydrocarbons in the Gulf of Gdansk (Baltic Sea). At six stations, seawater samples were taken, and the sensor system was applied in situ simultaneously. These measurements were compared to the results of conventional GC/MS laboratory analysis of the PAH concentrations in the seawater samples. For a PAH concentration above 150 ng(12PAH)l(-1), there was agreement between the SERS sensor and the GC/MS determinations. A standard addition experiment yielded a PAH concentration of 900 ng l(-1) at the Gdansk Harbor, which was of the same order as the GC/MS determinations of 12PAHs (200 ng(12PAH)l(-1)). The high SERS detection limit for seawater samples is explained by the competition for PAHs between the sensor membrane and particulate matter surfaces. Thus, the SERS sensor can be applied, e.g., as a non-quantitative alarm sensor for relatively high PAH concentrations in heavily polluted waters. The spectral unmixing procedure applied for Gdansk Harbor water confirmed the presence of phenanthrene at the highest concentration ([Phe]=140 ngl(-1)) and of Chr (2.7 ng l(-1)), but it did not detect the other PAHs present in the Gdansk Harbor water, as determined by GC/MS. When compared to the past literature and databases, the SERS spectra indicated the presence of a mixture of molecules consisting of carotenoids, n-alkanes, amines or fatty acids, and benzimidazoles at the coastal station ZN2. The spectra in the offshore direction indicated carboxylic acids. Interpretation of the farthest offshore in situ SERS measurements is difficult, principally due to the limited availability of reference spectra. The detection of the lower PAH concentrations commonly found in Baltic coastal water needs further research and development to obtain better sensitivity of the SERS sensor. However, the high analytical specificity of the SERS sensor also allows the detection of other chemical species that require the development of a SERS/Raman library for specific in situ spectral interpretation.

A prototype hand-held Raman sensor for the in situ characterization of meat quality.

As a tool for the in situ characterization of meat quality, a hand-held Raman sensor head using an excitation wavelength of 671 nm was developed. A microsystem-based external cavity diode laser module was integrated into the sensor head and attached to a Raman probe, which is equipped with lens optics for excitation and signal collection as well as a Raman filter stage for Rayleigh rejection. The Raman signal was guided by an optical fiber to the detection unit, which was in the initial phase a laboratory spectrometer with a charge-coupled device (CCD) detector. The laser and the sensor head were characterized in terms of stability and performance for in situ Raman investigations. Raman spectra of meat were obtained with 35 mW within 5 seconds or less, ensuring short measuring times for the hand-held device. In a series of measurements with raw and packaged pork meat, the Raman sensor head was shown to detect microbial spoilage on the meat surface, even through the packaging foil.

Microsystem light source at 488 nm for shifted excitation resonance Raman difference spectroscopy.

A microsystem light source emitting at 488 nm was tested and applied as a light source for shifted excitation resonance Raman difference spectroscopy (SERRDS). A nonlinear frequency conversion using a distributed feedback (DFB) diode laser emission at 976 nm and a periodically poled lithium niobate (PPLN) waveguide crystal was realized on a micro-optical bench with a footprint of 25 mm x 5 mm. Joint temperature management via the microbench is used for wavelength tuning. Two emission lines at 487.61 nm and 487.91 nm are used for the SERRDS experiments. The Raman spectra of the test sample polystyrene demonstrate that a laser bandpass filter did not need to be implemented. Resonance Raman spectra of Tartrazine (FD&C Yellow 5, E 102) in distilled water are presented to demonstrate the suitability of this light source for SERRDS in, e.g., food safety control.

Microsystem 671 nm light source for shifted excitation Raman difference spectroscopy.

We present a compact wavelength stabilized diode laser system at 671 nm on a micro-optical bench as a light source for shifted excitation Raman difference spectroscopy (SERDS). The laser system consists of two broad-area gain media in separate laser cavities using two reflection Bragg gratings with slightly different center wavelengths. A spectral width below 100 pm and a constant wavelength shift of 0.57 +/- 0.06 nm is obtained up to output powers of 250 mW. The suitability of this light source for SERDS is demonstrated using Raman spectra of ethanol with increasing concentrations of Cresyl Violet as the fluorescent contaminant.

Detection of PAHs in seawater using surface-enhanced Raman scattering (SERS).

The laboratory characterization of a field-operable surface-enhanced Raman scattering sensor (SERS optode) is presented for the detection of aromatic hydrocarbons in seawater. The sensor has been developed for deployment with a robust underwater spectrograph. To meet the demands of the harsh seawater application, sol-gel derived SERS substrates were used. The calibration curves of six PAHs were determined to be of Langmuir adsorption isotherm type with limits of detection ranging from the microg l(-1) to ng l(-1) level. The experimentally determined adsorption constants varied strongly with the molecular weight of the analytes and correlated with their solubility. A mixture of five PAHs dissolved in seawater was investigated to demonstrate the utility of this method for screening. Emphasis was put on the interference from suspended particulate matter (SPM). The Raman measurement with backscattering configuration was shown to be immune against turbidities up to 1000 NTU. The physico-chemical interference arising from adsorption by the sediment was measured on-line by adding sediment to a PAH-spiked solution. According to the calibration curve, the PAH concentration decrease corresponded to more than 98% of the analyte being scavenged by the sediment.