Raman spectroscopic quantification of milk powder constituents

Raman spectroscopy has significant potential for the quantification of food products. Milk powder is an important foodstuff and ingredient that is produced on large scale (over 20 million tonnes per annum). Raman spectroscopy, unlike near- and mid-infrared spectroscopies, has not been used extensively to quantify milk powder constituents. The effect of sample presentation on spectroscopic calibrations of protein and fat for 136 New Zealand milk powders was assessed using Raman spectroscopy. Prediction models were produced to quantify a protein concentration range of 32.19-37.65% w/w for skim milk powder, and a protein concentration range of 23.34-25.02% w/w and a fat concentration range of 26.26-29.68% w/w for whole milk powder (where ratios of prediction to deviation exceeded 2.6 with one exception). The resultant calibrations were not influenced by sample orientation; the sample temperature during data collection did affect the calibrations. Calcium fortification in the form of calcium carbonate was identified within a sub-set of samples, reinforcing the efficacy of Raman spectroscopy for identifying both crystalline and non-crystalline constituents within milk powder.     

Near infrared spectroscopic imaging assessment of cartilage composition: Validation with mid infrared imaging spectroscopy

Disease or injury to articular cartilage results in loss of extracellular matrix components which can lead to the development of osteoarthritis (OA). To better understand the process of disease development, there is a need for evaluation of changes in cartilage composition without the requirement of extensive sample preparation. Near infrared (NIR) spectroscopy is a chemical investigative technique based on molecular vibrations that is increasingly used as an assessment tool for studying cartilage composition. However, the assignment of specific molecular vibrations to absorbance bands in the NIR spectrum of cartilage, which arise from overtones and combinations of primary absorbances in the mid infrared (MIR) spectral region, has been challenging. In contrast, MIR spectroscopic assessment of cartilage is well-established, with many studies validating the assignment of specific bands present in MIR spectra to specific molecular vibrations. In the current study, NIR imaging spectroscopic data were obtained for compositional analysis of tissues that served as an in vitro model of OA. MIR spectroscopic data obtained from the identical tissue regions were used as the gold-standard for collagen and proteoglycan (PG) content. MIR spectroscopy in transmittance mode typically requires a much shorter pathlength through the sample (≤10 microns thick) compared to NIR spectroscopy (millimeters). Thus, this study first addressed the linearity of small absorbance bands in the MIR region with increasing tissue thickness, suitable for obtaining a signal in both the MIR and NIR regions. It was found that the linearity of specific, small MIR absorbance bands attributable to the collagen and PG components of cartilage (at 1336 and 856 cm⁻¹, respectively) are maintained through a thickness of 60 μm, which was also suitable for NIR data collection. MIR and NIR spectral data were then collected from 60 μm thick samples of cartilage degraded with chondroitinase ABC as a model of OA. Partial least squares (PLS) regression using NIR spectra as input predicted the MIR-determined compositional parameters of PG/collagen within 6% of actual values. These results indicate that NIR spectral data can be used to assess molecular changes that occur with cartilage degradation, and further, the data provide a foundation for future clinical studies where NIR fiber optic probes can be used to assess the progression of cartilage degradation.     

Differences in infrared spectroscopic data of connective tissues in transflectance and transmittance modes

Fourier transform infrared imaging spectroscopy (FT-IRIS) has been used extensively to characterize the composition and orientation of macromolecules in thin tissue sections. Earlier and current studies of normal and polarized FT-IRIS data have primarily used tissues sectioned onto infrared transmissive substrates, such as salt windows. Recently, the use of low-emissivity (“low-e”) substrates has become of great interest because of their low cost and favorable infrared optical properties. However, data are collected in transflectance mode when using low-e slides and in transmittance mode using salt windows. In the current study we investigated the comparability of these two modes for assessment of the composition of connective tissues. FT-IRIS data were obtained in transflectance and transmittance modes from serial sections of cartilage, bone and tendon, and from a standard polymer, polymethylmethacrylate. Both non-polarized and polarized FTIR data differed in absorbance, and in some cases peak position, between transflectance and transmittance modes. However, the FT-IRIS analysis of the collagen fibril orientation in cartilage resulted in the expected zonal arrangement of fibrils in both transmittance and transflectance. We conclude that numerical comparison of FT-IRIS-derived parameters of tissue composition should account for substrate type and data collection mode, while analysis of overall tissue architecture may be more invariant between modes.     

Characterisation of non-viable whole barley, wheat and sorghum grains using near-infrared hyperspectral data and chemometrics

Undesired germination of cereal grains diminishes process utility and economic return. Pre-germination, the term used to describe untimely germination, leads to reduced viability of a grain sample. Accurate and rapid identification of non-viable grain is necessary to reduce losses associated with pre-germination. Viability of barley, wheat and sorghum grains was investigated with near-infrared hyperspectral imaging. Principal component analyses applied to cleaned hyperspectral images were able to differentiate between viable and non-viable classes in principal component (PC) five for barley and sorghum and in PC6 for wheat. An OH stretching and deformation combination mode (1,920–1,940 nm) featured in the loading line plots of these PCs; this water-based vibrational mode was a major contributor to the viable/non-viable differentiation. Viable and non-viable classes for partial least squares-discriminant analysis (PLS-DA) were assigned from PC scores that correlated with incubation time. The PLS-DA predictions of the viable proportion correlated well with the viable proportion observed using the tetrazolium test. Partial least squares regression analysis could not be used as a source of contrast in the hyperspectral images due to sampling issues.     

Pharmaceutical polymorphs quantified with transmission Raman spectroscopy

The quantification of polymorphs in dosage forms is important in the pharmaceutical industry. Conventional Raman spectroscopy of solid‐state pharmaceuticals may be used for this, but it has some limitations such as sub‐sampling and fluorescence. These problems can be mitigated through the use of transmission Raman spectroscopy (TRS). The efficacy of TRS measurements for the prediction of polymorph content was evaluated using a ranitidine hydrochloride test system. Four groups of ranitidine hydrochloride‐based samples were prepared: three containing form I and II ranitidine hydrochloride and microcrystalline cellulose (spanning the ranges 0–10%, 90–100% and 0–100% form I fraction of total ranitidine hydrochloride), and a fourth group comprising form I ranitidine hydrochloride (0–10%) spiked commercial formulation. Transmission and conventional Raman spectroscopic measurements were recorded from both capsules and tablets of the four sample groups. Prediction models for polymorph and total ranitidine hydrochloride content were more accurate for the tablet than for the capsule systems. TRS was found to be superior to conventional backscattering Raman spectroscopy in the prediction of polymorph and total ranitidine hydrochloride content. The prediction model calculated for form I content across the 0–100% range was appropriate for process control [ratio of prediction to deviation (RPD) equal to 14.62 and 7.42 for tablets and capsules, respectively]. The 10% range calibrations for both form I and total ranitidine hydrochloride content were sufficient for screening (RPDs greater than 2.6). TRS is an effective tool for polymorph process control within the pharmaceutical industry. Copyright © 2011 John Wiley & Sons, Ltd.     

Rapid and cost-effective evaluation of bacterial viability using fluorescence spectroscopy

A rapid and easy method that takes advantage of an inexpensive and portable fibre-based spectroscopic system (optrode) to determine the ratio of live to dead bacteria is proposed. Mixtures of live and dead Escherichia coli with proportions of live:dead cells varying from 0 to 100% were stained using SYTO 9 and propidium iodide (PI) and measured using the optrode. We demonstrated several approaches to obtaining the proportions of live:dead E. coli in a mixture of both live and dead, from analyses of the fluorescence spectra collected by the optrode. To find a suitable technique for predicting the percentage of live bacteria in a sample, four analysis methods were assessed and compared: SYTO 9:PI fluorescence intensity ratio, an adjusted fluorescence intensity ratio, single-spectrum support vector regression (SVR) and multi-spectra SVR. Of the four analysis methods, multi-spectra SVR obtained the most reliable results and was able to predict the percentage of live bacteria in 10⁸ bacteria/mL samples between c. 7 and 100% live, and in 10⁷ bacteria/mL samples between c. 7 and 73% live. By demonstrating the use of multi-spectra SVR and the optrode to monitor E. coli viability, we raise points of consideration for spectroscopic analysis of SYTO 9 and PI and aim to lay the foundation for future work that uses similar methods for different bacterial species.