Marc Meurens

Oil and Fat Classification by Selected Bands of Near-Infrared Spectroscopy

One hundred and four edible oil and fat samples from 18 different sources, either vegetable (Brazil nut, coconut, corn, sunflower, walnut, virgin olive, peanut, palm, canola, soybean, sunflower) or animal (tallow and hydrogenated fish), have been analyzed by high-performance gas chromatography (HPGC) and near-infrared spectroscopy (NIRS). Fatty acids were quantified by HPGC. The near-infrared spectral features of the most noteworthy bands were studied and discussed to design a filter-type NIR instrument. An arborescent structure, based on stepwise linear discriminant analysis (SLDA), was built to classify the samples according to their sources. Seven discriminant functions permitted a successive discrimination of saturated fats, corn, soybean, sunflower, canola, peanut, high oleic sunflower, and virgin olive oils. The discriminant functions were based on the absorbance values, between three and five, from the 1700–1800 and 2100–2400 nm regions. Chemical explanations are given in support of the selected wavelengths. The arborescent structure was then checked with a test set, and 90% of the samples were correctly classified.

Monitoring large scale wine fermentations with infrared spectroscopy

Negative effects on wine quality and productivity caused by stuck and sluggish fermentations can be reduced significantly, if such problems are detected early through periodic chemical analysis. Infrared spectroscopy (IR) has been used successfully for monitoring fermentations, since many compounds can be measured quickly from a single sample without prior treatment. Nevertheless, few applications of this technology in large scale winemaking have been reported, and these do not cover the entire fermentation from must to finished wine. In this work, we developed IR calibrations for analyzing the fermenting must at any stage of fermentation. The calibration model was obtained with multivariable partial least squares and proved effective for analyzing Cabernet Sauvignon fermentations for glucose, fructose, glycerol, ethanol, and the organic acids; malic, tartaric, succinic, lactic, acetic, and citric. Upon external validation we found an average relative predictive error of 4.8%. Malic acid showed the largest relative predictive error (8.7%). In addition, external validation found that insufficient data for these calibrations made the analysis of fermenting musts using other grape varieties less reliable.

Phytosterol analysis and characterization in spelt (Triticum aestivum ssp spelta L.) and wheat (T aestivum L.) lipids by LC/APCI-MS

Spelt is still a minor cereal crop, mainly grown in Belgium. It is said to have a better nutritive value than winter wheat. Moreover, interesting functional properties have traditionally been attributed to spelt, such as a cholesterol-lowering effect. However, such properties are not substantiated by scientific evidence. Considering their physiological effects, phytosterols could partly account for spelts properties and have never been studied in this cereal. Phytosterols were analysed by LC/APCI-MS in spelt and winter wheat fine bran, a lipid and fibre-rich milling by-product. Sample preparation was suitable for the determination of glycosylated and free sterols, combined to their released counterparts after saponification. Chromatographic retention times, full mass spectra and MS2 spectra of 12 reference sterols allowed the characterization of phytosterols present in cereal samples.

ATR‐FTIR sensor development for continuous on‐line monitoring of chlorinated aliphatic hydrocarbons in a fixed‐bed bioreactor

This article describes the continuous on-line monitoring of a dechlorination process by a novel attenuated total reflection-Fourier transform infrared (ATR-FTIR) sensor. This optical sensor was developed to measure noninvasively part-per-million (ppm) concentrations of trichloroethylene (TCE), tetrachloroethylene (PCE), and carbon tetrachloride (CT) in the aqueous effluent of a fixed-bed dechlorinating bioreactor, without any prior sample preparation. The sensor was based on an ATR internal reflection element (IRE) coated with an extracting hydrophobic polymer, which prevented water molecules from interacting with the infrared (IR) radiation. The selective diffusion of chlorinated compound molecules from aqueous solution into the polymer made possible their detection by the IR beam. With the exclusion of water the detection limits were lowered, and measurements in the low ppm level became possible. The best extracting polymer was polyisobutylene (PIB) in the form of a 5.8-microm thick film, which afforded a detection limit of 2, 3, and 2. 5 mg/L (ppm) for TCE, PCE, and CT, respectively. Values of the enrichment factors between the polymer coating and the water matrix of these chloro-organics were determined experimentally and were compared individually with predictions obtained from the slopes of absorbance/concentration curves for the three analytes. Before coupling the ATR-FTIR sensor to the dechlorinating bioreactor, preliminary spectra of the chlorinated compounds were acquired on a laboratory scale configuration in stop-flow and flow-through closed-loop modes. In this way, it was possible to study the behavior and direct response of the optical sensor to any arbitrary concentration change of the analytes. Subsequently, the bioreactor was monitored with the infrared sensor coupled permanently to it. The sensor tracked the progression of the analytes spectra over time without perturbing the dechlorinating process. To calibrate the ATR-FTIR sensor, a total of 13 standard mixtures of TCE, PCE and CT at concentrations ranging from 0 to 60 ppm were selected according to a closed symmetrical experimental design derived from a 3(2) full-factorial design. The above range of concentrations chosen for calibration reflected typical values during normal bioreactor operation. Several partial least squares (PLS) calibration models were generated to resolve overlapping absorption bands. The standard error of prediction (SEP) ranged between 0.6 and 1 ppm, with a relative standard error of prediction (RSEP) between 3 and 6% for the three analytes. The accuracy of this ATR-FTIR sensor was checked against gas chromatography (GC) measurements of the chlorocompounds in the bioreactor effluents. The results demonstrate the efficiency of this new sensor for routine continuous on-line monitoring of the dechlorinating bioreactor. This strategy is promising for bioprocess control and optimization.

Breast cancer detection by Fourier transform infrared spectrometry

Fourier transform infrared spectra of 75 biopsies from 55 cases of breast carcinoma were studied in comparison with histo-morphometry. The spectra of carcinomatous tissues are very different from those of normal tissues. There are evident correlations between the intensity of some infrared absorption bands and the volume density of malignant cells measured by optical microscopy [7]. Very high correlation coefficients are observed for phosphate monoester and phosphodiester bands; significant correlation coefficients are also observed for amide I and II bands.

Nutritive evaluation and ingredient prediction of compound feeds for rabbits by near-infrared reflectance spectroscopy (NIRS)

Near-infrared reflectance spectroscopy (MRS) was used to predict the nutritive characteristics of 66 compound rabbit feeds from three countries (Belgium, Spain and Italy) and the main ingredient inclusion rate in 59 of these feeds of known ingredient composition. Principal component analysis (PCA) was performed to classify the compound feeds according to their origin. The coefficient of multiple determination (R-2) for crude protein concentration (CP) was ca. 0.88 in both, calibration and validation with standard errors of calibration (SEC) and prediction (SEP) equal to 7.5 and 7.7 g (kg DM)(-1), respectively. NIRS prediction of gross energy (GE) and digestible energy (DE) concentrations was more precise, with high R-2 (0.90) and low SEP (0.26 and 0.37 MJ (kg DM)(-1), respectively). Satisfactory results were also obtained for both, the dry matter digestibility (DMd) and gross energy digestibility (GEd) prediction. The CP-correlated wavelengths were observed to be associated with the bond vibrations of the protein functional groups, while the wavelengths correlated with GE, DE, DMd and GEd were linked with starch, protein and crude fiber structure. The calibration on absorbance data to estimate the inclusion rate of the main ingredients demonstrated a fair correlation for alfalfa meal, barley and wheat bran, intermediate for sunflower meal and weak for soybean meal. In validation, the precision of the NIRS estimate remained satisfactory for alfalfa and sunflower meal but decreased for barley and wheat bran. The calibration of the spectra transformed in second derivative appeared to improve the quality of estimation by reducing the number of optimal factors from 9-15 to 2-4; moreover, the estimate precision of soybean and sunflower meal inclusions improved (R-2: 0.90 and 0.86, respectively) with the reduction of SEC (13.0 and 12.9 g kg(-1), respectively). In validation, however, the estimate precision for all raw materials became weaker than the degree achieved using absorbance data. PCA on the transformed spectra grouped the compound rabbit feeds according to their country of origin and indicated the possibility of identifying the presence of specific ingredients (i.e. full-fat rapeseed)

Determination of Sugars and Organic Acids in Fruit Juices by FT Mid-IR Investigation of Dry Extract

In an extension of the approach adopted by Meurens et al. for dispersive NIR spectroscopy, the principle of using dry extracts has been applied to FT-IR spectroscopy, to make use of three advantages: the rapidity of Fourier transform spectroscopy, the solvent elimination, and the better peak resolution in the mid-IR region. However, sampling appears more difficult in mid-IR than in NIR spectroscopy. The feasibility of quantitative analysis has, in a first step, been tested on synthetic samples before application to natural fruit juices. The performance of our dry extract method is reported in terms of spectroscopy as well as of multicomponent quantitative analysis of sugars and organic acids in fruit juices.

Identification of Breast Carcinomatous Tissue By Near-infrared Reflectance Spectroscopy

NIR reflectance spectra of 110 cryostat sections of carcinomatous tissue and 114 cryostat sections of normal surrounding fibro-glandular tissue from 10 cases of breast cancer, identified by a classical pathology method, were scanned between 1100 and 2500 nm by a grating spectrometer in reflectance mode. Four wavelength intervals (1208–1242, 1746–1788, 2012–2048 and 2326–2368 nm) were found to be different for normal and carcinomatous tissues. In each interval, the second-derivative spectra of normal tissue showed a similar pattern with several characteristic peaks. In order to test the capacity of NIR spectroscopy in discriminating between normal and carcinomatous breast samples, 104 tissue sections from five additional cases were scanned prior to microscopic examination. The diagnostic prediction of NIR spectroscopy coincided exactly with the histology diagnosis for all the samples. Moreover, the presence of even a minute quantity of cancer infiltration can be detected by NIR spectroscopy, in total accordance with the microscopical observation. Therefore, the results of our experiments allow us to consider that NIR spectroscopy might become, with feasible improvements, an accurate, rapid, and reliable method for detecting breast cancer.

Performance comparison of UV and FT-Raman spectroscopy in the determination of conjugated linoleic acids in cow milk fat.

The determination of conjugated linoleic acids (CLA) in cow milk fat was studied by using UV (210-250 nm) and Fourier transform (FT)-Raman (900-3400 cm (-1)) spectroscopy in order to determine the best spectrophotometric technique for routine analysis of milk fat. A collection of 57 milk fat samples was randomly divided into two sets, a calibration set and a validation set, representing two-thirds and one-third of the samples, respectively. All calculations were performed on the calibration set and then applied to the validation set. The CLA content ranged from 0.56 to 4.70%. A comparison of various spectral pretreatments and different multivariate calibration techniques, such as partial least-squares (PLS) and multiple linear regression (MLR), was done. This paper shows that UV spectroscopy is as reliable as FT-Raman spectroscopy to monitor CLA in cow milk fat. The best calibration for FT-Raman was given by a PLS model of seven factors with a standard error of prediction (SEP) of 0.246. For UV spectroscopy, PLS models were also better than MLR models. The most robust PLS model was constructed with only one factor and with SEP=0.288.

Multivariate determination of sugar powders by attenuated total reflectance infrared spectroscopy

Thanks to what has been achieved by Fourier transformation, infrared analysis can now become a state-of-the-art device in quality control laboratories if we consider its precision and the gain in time it ensures. Moreover, an increasing number of new mathematical regression methods such as partial least-squares (PLS) regression allow multicomponent quantitative analysis in mixtures. Nevertheless, the efficiency of infrared spectrometry as a quantitative analytical method often depends on the choice of an adequate presentation for the sample. For quantitative analysis of powders, sampling appears difficult in the mid-IR. We have developed a method built on three advantages: the rapidity of Fourier transform spectroscopy, fast solvent elimination, and good peak resolution. For enhancing peak intensity on attenuated total reflectance (ATR) spectroscopy we use nondissolving and evaporating liquids. For instance, the analysis of three components (glucose, fructose, and sucrose) can be done with a precision in the range of 4%, whereas the time required to obtain an analysis report is about 5 min.