Klavs Martin Sørensen

An On-Line Near-Infrared (NIR) Transmission Method for Determining Depth Profiles of Fatty Acid Composition and Iodine Value in Porcine Adipose Fat Tissue:

The present work describes a measurement method using spatially resolved near-infrared (NIR) spectroscopy to determine porcine carcass fat quality as a function of the distance to the skin by estimating its iodine value (IV). The new method is capable of performing on-line carcass grading at full production speed (approximately 1000 carcasses per hour). The method is demonstrated in an experiment where 35 carcasses were sampled at an abattoir, selected from three feeding groups. The NIR transmission instrument was applied on the loin of each carcass, and a parallel reference sample was removed and processed into 1.8 mm thick disks, representing a depth-of-fat profile from the loin. The disks were analyzed for fatty acid composition using gas chromatography (GC) and for IV. A principal component analysis (PCA) of the obtained GC reference values clearly showed that the feeding regimes can be differentiated. Using interval partial least squares (iPLS) regression, a model was produced that can predict the IV of the fat at a given measured depth with a root mean square error of cross-validation (RMSECV) of 1.44. The results show how the IV varies as a function of feeding regime and as a function of fat depth. The maximum variation found within a single depth profile was 10.1 IV from the skin to the innermost part of the fat layers. In the sample material investigated the average span in IV between the average values of the two porcine backfat layers was 6.4 IV (the maximum difference was 8.6 IV). The new method can provide the abattoir with new chemical information about fat quality and production quality that will open new possibilities of meat/carcass grading and product development.

Measurement of Boar Taint in Porcine Fat Using a High-Throughput Gas Chromatography–Mass Spectrometry Protocol

This work outlines an optimized gas chromatrography-mass spectrometry (GC-MS) based protocol for screening of the presence of the three boar-taint-producing compounds indole, skatole (3-methylindole), and androstenone (5α-androst-16-en-3-one) in porcine fat. The study shows that an accuracy suitable for sample screening can be achieved even when speed and ease of sample handling is prioritized and without the use of internal standards. The method provides levels of detection of 82 ng/g for indole, 97 ng/g for skatole, and 623 ng/g for androstenone (in a 2 g natural backfat matrix). A least-squares approach of predicting the sample analyte mass from instrument response is shown to have prediction errors (root-mean-square error) of 96 ng/g for indole, 94 ng/g for skatole, and 331.3 ng/g for androstenone. The method is intended for discrimination of samples in risk groups, and a scheme is proposed to turn the GC-MS response of the boar-taint analytes into risk classes.

Near-Infrared Spectroscopy Using a Supercontinuum Laser: Application to Long Wavelength Transmission Spectra of Barley Endosperm and Oil

The supercontinuum laser is a new type of light source, which combines the collimation and intensity of a laser with the broad spectral region of a lamp. Using such a source therefore makes it possible to focus the light onto small sample areas without losing intensity and thus facilitate either rapid or high-intensity measurements. Single seed transmission analysis in the long wavelength (LW) near-infrared (NIR) region is one area that might benefit from a brighter light source such as the supercontinuum laser. This study is aimed at building an experimental spectrometer consisting of a supercontinuum laser source and a dispersive monochromator in order to investigate its capability to measure the barley endosperm using transmission experiments in the LW NIR region. So far, barley and wheat seeds have only been studied using NIR transmission in the short wavelength region up to 1100 nm. However, the region in the range of 2260–2380 nm has previously shown to be particularly useful in differentiating barley phenotypes using NIR spectroscopy in reflectance mode. In the present study, 350 seeds (consisting of 70 seeds from each of five barley genotypes) in 1 mm slices were measured by NIR transmission in the range of 2235–2381 nm and oils from the same five barley genotypes were measured in a cuvette with a 1 mm path length in the range of 2003–2497 nm. The spectra of the barley seeds could be classified according to genotypes by principal component analysis; and spectral covariances with reference analysis of moisture, β-glucan, starch, protein and lipid were established. The spectral variations of the barley oils were compared to the fatty acid compositions as measured using gas chromotography–mass spectrometry (GC-MS).

Three-dimensional images of porcine carcass fat quality using spatially resolved near infrared spectroscopy

Introduction I nspired by increasing industrial demands for grading fat quality and the increasing availability of low-cost solid-state NIR spectrometers, the Danish company Carometec A/S teamed up with the University of Copenhagen and the Danish National Advanced Technology Foundation to develop an effective on-line NIR spectrometer for quick, cheap and accurate prediction of carcass fat quality early after slaughter. This article reports a novel experiment in which the easy and quick capabilities of the equipment for measurement of fat quality were exploited to map the topological variance in fat composition (iodine value) on a series of slaughter carcasses at an industrial abattoir. The article presents, for the first time, an analysis of the variability of the fat quality expressed by the iodine value across the entire carcass.

Cool-Climate Red Wines—Chemical Composition and Comparison of Two Protocols for 1H–NMR Analysis

This study investigates the metabolome of 26 experimental cool-climate wines made from 22 grape varieties using two different protocols for wine analysis by proton nuclear magnetic resonance (1H-NMR) spectroscopy. The wine samples were analyzed as-is (wet) and as dried samples. The NMR datasets were preprocessed by alignment and mean centering. No normalization or scaling was performed. The “wet” method preserved the inherent properties of the samples and provided a fast and effective overview of the molecular composition of the wines. The “dried” method yielded a slightly better sensitivity towards a broader range of the compounds present in wines. A total of 27 metabolites including amino acids, organic acids, sugars, and alkaloids were identified in the 1H-NMR spectra of the wine samples. Principal component analysis was performed on both NMR datasets evidencing well-defined molecular fingerprints for ‘Baco Noir’, ‘Bolero’, ‘Cabernet Cantor’, ‘Cabernet Cortis’, ‘Don Muscat’, ‘Eszter’, ‘Golubok’, ‘New York Muscat’, ‘Regent’, ‘Rondo’, ‘Triomphe d’Alsace’, ‘Précose Noir’, and ‘Vinoslivy’ wines. Amongst the identified metabolites, lactic acid, succinic acid, acetic acid, gallic acid, glycerol, and methanol were found to drive sample groupings. The 1H-NMR data was compared to the absolute concentration values obtained from a reference Fourier transform infrared method, evidencing a high correlation.

The spatial composition of porcine adipose tissue investigated by multivariate curve resolution of near infrared spectra: Relationships between fat, the degree of unsaturation and water

This study represents a continuation of a previously performed study by Sørensen, et al. (2012) about the use of and development of an online method for determining the iodine number in porcine adipose tissue by the use of near infrared spectroscopy. In the original study, the fat tissue was measured as a function of the depth from the skin and thus represent spatial or 2D near infrared data, and if measured across a porcine carcass it represents 3D data of the pig. These data structures, which were largely ignored in the original publication, are here explored by multivariate curve resolution. The massive amount of near infrared data (11,329 spectra) was unfolded from the true five-way array (carcass × horizontal position × vertical position × depth × spectral data points, 30 × 6 × 15 × 6 × 204) into a two-way matrix (sample × spectra, 11329 × 204) (maintaining spatial data in a separate array) and multivariate curve resolution applied. A two-component multivariate curve resolution model proved to fit the data nearly perfectly (99.69% X variance explained). By concentration the highest component was found to be fat, and the second component was found to be water. Surprisingly, the latter was found to co-vary strongly with the iodine value of the fat (r = −0.83). The resulting multivariate curve resolution model was folded back into its original spatial dimension to produce maps showing distribution of the constituent concentrations in the adipose tissue.

Untargeted GC-MS Metabolomics Reveals Changes in the Metabolite Dynamics of Industrial Scale Batch Fermentations of Streptoccoccus thermophilus Broth

An industrial scale biomass production using batch or fed‐batch fermentations usually optimized by selection of bacterial strains, tuning fermentation media, feeding strategy, and temperature. However, in‐depth investigation of the biomass metabolome during the production may reveal new knowledge for better optimization. In this study, for the first time, the authors investigated seven fermentation batches performed on five Streptoccoccus thermophilus strains during the biomass production at Chr. Hansen (Denmark) in a real life large scale fermentation process. The study is designed to investigate effects of batch fermentation, fermentation time, production line, and yeast extract brands on the biomass metabolome using untargeted GC‐MS metabolomics. Processing of the raw GC‐MS data using PARAFAC2 revealed a total of 90 metabolites out of which 64 are identified. Partitioning of the data variance according to the experimental design was performed using ASCA and revealed that batch and fermentation time effects and their interaction term were the most significant effects. The yeast extract brand had a smaller impact on the biomass metabolome, while the production line showed no effect. This study shows that in‐depth metabolic analysis of fermentation broth provides a new tool for advanced optimization of high‐volume‐low‐cost biomass production by lowering the cost, increase the yield, and augment the product quality.

Investigating Depth Profiles from Porcine Adipose Tissue by HR MAS NMR Spectroscopy

One of the important quality parameters in porcine carcass grading for determining farmer payment and carcass sorting before splitting and cutting is the quality of the fat in the porcine carcass. Therefore, it is of supreme importance to obtain detailed knowledge about the chemical composition of the fat layers. In this study, we have investigated the potential of using high resolution magic angle spinning (HR MAS) NMR to investigate the depth profiles of porcine adipose fat tissue, with the purpose of estimating the variation in fatty acid composition as a function of feeding scheme and of fat layer. The measured spectra resulted in well separated profiles of the fat layers, and the signals associated with the double bonds in the fatty acids present, was used to study the total degree of unsaturation. The standard method for determining the fat quality is obtaining of the iodine value (IV), which measures the degree of unsaturation through the total number of double bonds in the fatty acids. For the possible prediction of the IV in porcine fat by HR MAS NMR spectroscopy using partial least squares regression, the iodine values measured in related studies was used.