Combination Of Near-infrared Spectroscopy Research Articles

Water sorption/desorption—near IR and calorimetric study of crystalline and amorphous raffinose

Mass loss at elevated RH is an established method for determining the occurrence of crystallisation of an amorphous material. Through the combination of near infrared spectroscopy and gravimetric vapour sorption, it has been possible to show the transition of raffinose from its spray-dried amorphous form to a crystalline form without this characteristic mass loss. It has also been possible to observe changes in the crystalline material for a period of 30 h subsequent to exposure to elevated relative humidity by near infrared spectroscopy that are not associated with changes in mass, but are related to repacking of hydrate molecules. Drying of the crystalline pentahydrate in the DVS-NIR was seen to show changes in the NIR peak related to –OH. From this, NIR peaks were tentatively ascribed as relating to a penta-, tetra-, tri- and a di-hydrate form, but the sample returned to the amorphous response by the time the water content fell to the equivalent of the monohydrate, indicating that crystallinity had been lost. These observations would be compatible with the hypothesis that lower hydrates of raffinose exist. Due to the absence of mass loss in association with crystallisation, it was found that the enthalpy of crystallisation of amorphous raffinose, as determined by isothermal microcalorimetry, is similar to the enthalpy of fusion determined by differential scanning calorimetry. Finally, it was observed that the early part of the response in the isothermal microcalorimeter was related to mobility of molecules when Tg was above T. This mobility was able to give the bulk morphology of a crystal before the sample developed long range order and crystalline properties.

Characterization of the Sources of Variation Affecting Near-Infrared Spectroscopy Using Chemometric Methods

A rapid assessment of product quality can often be made using a combination of near-infrared spectroscopy (NIR) and multivariate calibration. The robustness of such a method is determined by the sensitivity of the multivariate calibration model to variations in the spectral data. An approach is described that uses a combination of experimental design methodology and principal component analysis to identify the main sources of variation in the spectra and to estimate their influence on the quantitative predictions. This is accomplished by comparing variations in a set of measured, replicate spectra to spectra with simulated variations. The approach was applied to the hydroxyl number determination of polyols by NIR spectroscopy and partial least-squares calibration. The results indicated that the most significant sources of variation were due to a variable cell path length and a variable curved background. Correction for these errors resulted in a 58% reduction in the standard deviation of the hydroxyl number predictions, indicating that a substantial improvement in the method precision is possible.

Noninvasive Assessment of Regional and Temporal Variations in Tissue Oxygenation by Near-Infrared Spectroscopy and Imaging

A combination of near-infrared spectroscopy and discrete wavelength near-infrared imaging is used to noninvasively monitor the forearm during periods of restricted blood outflow (venous outflow restriction) and interrupted blood inflow (ischemia). Multivariate analysis of image and spectral data time courses was used to identify highly correlated spectral and regional domains, while fuzzy C-means clustering of image time courses was used to reveal finer regional heterogeneities in the response of stressed tissues. Localized near-infrared spectroscopy was used to investigate the magnitude of the bulk changes in the tissue optical properties and the variation in tissue oxygenation saturation during venous outflow restriction and complete forearm ischemia. The imaging and spectroscopic analyses revealed highly localized regional variations in tissue oxygen saturation during forearm ischemia as compared to the more diffuse and global response of the forearm during venous outflow restriction.

Quantitative Analysis of Individual Sugars and Acids in Orange Juices by Near-Infrared Spectroscopy of Dry Extract

The combination of near-infrared spectroscopy (near-IR) and multivariate calibration for determination of glucose, fructose, sucrose, and citric and malic acids in orange juices was investigated. The concentrations of these components analyzed by enzymatic assays were considered as references relative to near-IR spectroscopy. Dry extract spectra of 218 orange juice samples were recorded in transmission mode between 1100 and 2500 nm. The original near-IR spectral data could be improved by mathematical pretreatments such as derivative transformations or multiplicative signal correction. Stepwise multiple linear regression (SMLR) and partial least-squares regression (PLSR) were used to create calibration models relating chemical reference values to spectral data. The prediction ability of calibration models is acceptable in comparison with the reference methods. The calibration and validation results provided by PLS-1 calibration models are slightly better than those obtained with SMLR calibration models. Keywords: Sugars; acids; orange juices; near-infrared spectroscopy; multivariate calibration

Near-Infrared Spectroscopy as an Alternative to Biological Testing for Quality Control of Hyaluronan: Comparison of Data Preprocessing Methods for Classification

An alternative method to biological testing on animals has been studied. The method is based on pattern recognition by combination of near-infrared spectroscopy and multivariate classification. The pharmaceutical product under study is based on a high-molecular-weight carbohydrate, Hyaluronan, used as a medical device for eye surgery. The effect of data preprocessing on classification performance of approved and rejected samples was evaluated by use of principal components models for each class. With the use of multiplicative scatter correction techniques, the class discrimination was enhanced 10 times in comparison to uncorrected data. From a leave-one-out procedure including a total of 29 samples, 80% of the samples were classified in agreement with the biological reference data and the remaining 20% were classified as non-members. With the use of partial least-squares discriminant analysis, 90% of the predicted samples were in accordance with the biological assay.