Towards on-line cheese monitoring: Exploration of semi-hard cheeses using NIR and 1H NMR spectroscopy.

This study aims to investigate the potential of using advanced spectroscopies for cheese quality monitoring. For this purpose, six semi-hard cheeses manufactured using lactic acid bacteria (LAB) and/or propionic acid bacteria (PAB) were explored using near-infrared spectroscopy (NIRS) and Proton Nuclear Magnetic Resonance (1H NMR) spectroscopy. The spectral data were analyzed using principal component analysis for extraction of possible discriminative patterns in quality parameters. The results show that the green analytical, but primarily bulk-sensitive, NIRS method was able to discriminate the cheese varieties primarily due to differences in the first overtone CH stretching region between 1650 and 1720 nm, in particular by the lactate methylene absorption at 1674 nm. A total of 25 metabolites were identified in the 1H NMR spectra of the cheese extracts, several of which were associated with the LAB and PAB metabolic pathways. PAB-associated metabolites include propionate, acetate, and glutamate, while LAB-associated metabolites include lactate and acetoin among others.

The legacy of terrestrial plant evolution on cell wall fine structure.

The evolution of land flora was an epochal event in the history of planet Earth. The success of plants, and especially flowering plants, in colonizing all but the most hostile environments required multiple mechanisms of adaptation. The mainly polysaccharide-based cell walls of flowering plants, which are indispensable for water transport and structural support, are one of the most important adaptations to life on land. Thus, development of vasculature is regarded as a seminal event in cell wall evolution, but the impact of further refinements and diversification of cell wall compositions and architectures on radiation of flowering plant families is less well understood. We approached this from a glyco-profiling perspective and, using carbohydrate microarrays and monoclonal antibodies, studied the cell walls of 287 plant species selected to represent important evolutionary dichotomies and adaptation to a variety of habitats. The results support the conclusion that radiation of flowering plant families was indeed accompanied by changes in cell wall fine structure and that these changes can obscure earlier evolutionary events. Convergent cell wall adaptations identified by our analyses do not appear to be associated with plants with similar lifestyles but that are taxonomically distantly related. We conclude that cell wall structure is linked to phylogeny more strongly than to habitat or lifestyle and propose that there are many approaches of adaptation to any given ecological niche.

Effects of Water Stress, Defoliation and Crop Thinning on Vitis vinifera L. cv. Solaris Must and Wine Part II: 1H NMR Metabolomics.

Proton nuclear magnetic resonance (1H NMR) metabolomics was employed to investigate the impact of water deficit, defoliation, and crop thinning on the chemical composition of must and wines from the cool-climate white grape variety Solaris. The obtained results show that viticultural practices (defoliation and crop thinning) affected the amino acid and sugar content of Solaris must and thereby the quality of the final wine­mainly in terms of compounds normally related to fruity aroma (i.e., isopentanol), non-sugar sweetness (i.e., proline and glycerol), and alcohol content. The content of tyrosol, a natural phenolic antioxidant with a high bioavailability, was increased in the final wine by a combination of defoliation and crop thinning. The results of the metabolomics analysis performed on the must and wine samples from the water stress experiment showed that short-term water deficit significantly affected the concentration of several flavor-related compounds, including glutamate, butyrate and propanol, of the organic acids lactate and fumarate, and of the phenolic compounds caffeic acid and p-coumaric acid. ANOVA simultaneous component analysis showed that the effect of water deficit accounted for 11% (p < 0.001) and 8% (p < 0.001) of the variability in the metabolite concentrations in must and wines, respectively, while viticultural practices accounted for 38% (p < 0.001) and 30% (p < 0.001) of the metabolite variability in must and wines, respectively.

Effects of Water Stress, Defoliation and Crop Thinning on Vitis vinifera L. cv. Solaris: Part I: Plant Responses, Fruit Development and Fruit Quality.

Viticultural practices and irrigation have a major impact on fruit development and yield, and ultimately on must quality. The effects of water deficit (WD), defoliation (Def), and crop-thinning (CT) on Solaris plants and fruit development, as well as on the chemical composition of grape juice were investigated. WD was induced at three periods during fruit development (pre-veraison, veraison, and ripening) in pot-grown plants, while Def and CT were carried out on field-grown plants. Environmental and vegetative parameters were monitored during the experiments. The bulk chemical composition of the fruits was determined in juice by Fourier Transform-Infrared (FT-IR) spectroscopy throughout fruit ripening and at final harvest. The results showed that WD reduced soil water content and leaf water status. CT significantly reduced yield per vine, but increased cluster size. Mid to late WD reduced soluble solids by 1%. CT increased sugar content in juice, while Def decreased sugar accumulation. Total acids were higher in the juice from the field vines. Yet, CT lowered malic and tartaric acids. Def increased tartaric acid. Ammonia and alpha amino nitrogen were higher in the juice from pot-grown vines, while pH was lowered by Def and raised by CT. It is concluded that Solaris has a remarkable ability to tolerate and recover from WD. CT and Def significantly affected the bulk chemical composition of grapes in terms of total acidity and sugar accumulation, with CT grapes having the highest sugar content and the lowest total acidity and Def the opposite.

On-Line Real-Time Monitoring of a Rapid Enzymatic Oil Degumming Process: A Feasibility Study Using Free-Run Near-Infrared Spectroscopy.

Enzymatic degumming is a well established process in vegetable oil refinement, resulting in higher oil yield and a more stable downstream processing compared to traditional degumming methods using acid and water. During the reaction, phospholipids in the oil are hydrolyzed to free fatty acids and lyso-phospholipids. The process is typically monitored by off-line laboratory measurements of the free fatty acid content in the oil, and there is a demand for an automated on-line monitoring strategy to increase both yield and understanding of the process dynamics. This paper investigates the option of using Near-Infrared spectroscopy (NIRS) to monitor the enzymatic degumming reaction. A new method for balancing spectral noise and keeping the chemical information in the spectra obtained from a rapid changing chemical process is suggested. The effect of a varying measurement averaging window width (0 to 300 s), preprocessing method and variable selection algorithm is evaluated, aiming to obtain the most accurate and robust calibration model for prediction of the free fatty acid content (% (w/w)). The optimal Partial Least Squares (PLS) model includes eight wavelength variables, as found by rPLS (recursive PLS) calibration, and yields an RMSECV (Root Mean Square Error of Cross Validation) of 0.05% (w/w) free fatty acid using five latent variables.

The plasma metabolome of Atlantic salmon as studied by 1H NMR spectroscopy using standard operating procedures: effect of aquaculture location and growth stage.

INTRODUCTION: Metabolomics applications to the aquaculture research are increasing steadily. The use of standardized proton nuclear magnetic resonance (1H NMR) spectroscopy can provide the aquaculture industry with an unbiased, reproducible, and high-throughput screening tool, which can help to diagnose nutritional and disease-related metabolic disorders in farmed fish. OBJECTIVE: Standard operating procedures developed for analysing (human) plasma by 1H NMR were applied to fingerprint the metabolome in plasma samples collected from Atlantic salmon. The aim was to explore the metabolome of salmon plasma in relation to growth stage and sampling site. METHODS: A total of 72 salmon were collected from three aquaculture sites in Norway (Lat. 65, 67, and 70 °N) and over two sampling events (December 2017 and November 2018). Plasma drawn from each salmon was measured by 1H NMR and metabolites were quantified using the SigMa software. The NMR data was analysed by principal component analysis (PCA) and ANOVA-simultaneous component analysis (ASCA). RESULTS: Important metabolic differences were evidenced, with adult salmon having a much higher content of very low-density lipoproteins and cholesterol in their plasma, while smolts displayed significantly higher levels of propylene glycol. Overall, 24% of the metabolite variation was due to the growth stage, whereas 12% of the metabolite variation was related to the aquaculture site and practice (p < 0.001). CONCLUSION: This study provides a baseline investigation of the plasma metabolome of the Atlantic salmon and demonstrates how 1H NMR metabolomics can be used in future investigations for comparing aquaculture practices and their influence on the fish metabolome.

Prediction of α-Lactalbumin and ß-Lactoglobulin Composition of Aqueous Whey Solutions Using Fourier Transform Mid-Infrared Spectroscopy and Near-Infrared Spectroscopy.

Characterization and quantification of individual whey proteins are of crucial importance to many industrial dairy processes. Labor intensive wet-chemical methods are still being used for this purpose, but a rapid quantification method for individual whey proteins is highly desired. This work investigate the utility of Fourier transform mid-infrared spectroscopy and Fourier transform near-infrared spectroscopy for rapid quantification of the two main whey proteins (ß-lactoglobulin and α-lactalbumin) in complex aqueous whey solutions simulating production process streams. MIR and NIR spectra obtained on whey samples with known and varying amounts of the proteins of interest and are used to develop partial least squares prediction models. Selection of informative wavelength regions allowed for prediction of ß-lactoglobulin and α-lactalbumin concentrations with very high precision and accuracy (root mean square error of cross-validation, or RMSECV, of 0.6% and R2 of 0.99 for NIR), demonstrating the potential of being implemented for rapid in-line monitoring of protein composition in industrial whey streams. Two-dimensional MIR-NIR correlation spectroscopy is used to identify the most informative parts of the NIR spectra in relation to protein secondary structure. In addition multivariate curve resolution is applied to the MIR data to resolve mixture spectra and to elucidate the spectral ranges that were most useful in distinguishing between the two whey proteins. The study concludes that NIR spectroscopy has potential for accurate in-line protein quantification and overall secondary protein structure quantification which open new possibilities for in-line industrial applications.

First-principles identification of C-methyl-scyllo-inositol (mytilitol) - A new species-specific metabolite indicator of geographic origin for marine bivalve molluscs (Mytilus and Ruditapes spp.).

This study presents a level-1 identification of the seven carbon (7-C) sugar C-methyl-scyllo-inositol (mytilitol) in mussels and clams (Mytilus and Ruditapes spp., respectively) purchased in Denmark and Italy. For each sample, the hydrophilic extract of the soft tissue was analyzed by proton nuclear magnetic resonance (1H NMR) spectroscopy using a 600 MHz NMR spectrometer. A first tentative identification of mytilitol was carried out by computing a statistical total correlation spectroscopy (STOCY) analysis of the 1H NMR spectra, followed by a level-1 identification based on first-principles methods including chemical synthesis, structure elucidation and standard-addition experiments. Mytilitol was quantified in the 1H NMR spectra and its average relative concentration turned out to be significantly lower in clams than in mussels (p-value < 0.001), with Danish mussels having the highest mytilitol concentration. Principal component analysis (PCA) of the NMR dataset brought further evidence to a species-specific and geographic-dependent content of mytilitol in mussels and clams.

Authentication of cocoa bean shells by near- and mid-infrared spectroscopy and inductively coupled plasma-optical emission spectroscopy.

The aim of this study was to evaluate the efficacy of a multi-analytical approach for origin authentication of cocoa bean shells (CBS). The overall chemical profiles of CBS from different origins were characterized using diffuse reflectance near-infrared spectroscopy (NIRS) and attenuated total reflectance mid-infrared spectroscopy (ATR-FT-IR) for molecular composition identification, as well as inductively coupled plasma-optical emission spectroscopy (ICP-OES) for elemental composition identification. Exploratory chemometric techniques based on Principal Component Analysis (PCA) were applied to each single technique for the identification of systematic patterns related to the geographical origin of samples. A combination of the three techniques proved to be the most promising approach to establish classification models. Partial Least Squares-Discriminant Analysis modelling of fused PCA scores of three independent models was used and compared with single technique models. Improved classification of CBS samples was obtained using the fused model. Satisfactory classification rates were obtained for Central African samples with an accuracy of 0.84.

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.

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, ß-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).

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.