A near-infrared spectroscopic method was developed and validated for determining the caffeine concentration of single and intact tablets in a Finnish pharmaceutical product containing 58.82% (m/m) caffeine.The spectral region of interest contained a total of 474 data points. The second derivative of Savitsky-Golay, a standard normal variate, and mean centering were used as spectral preprocessing options. The feasibility study showed nonuniformity of caffeine repartition within each tablet. Thus, spectra were recorded from both faces of the tablets, and the analysis result for a single tablet was reported as the average of both face determinations. Precision of the method was validated because the relative standard deviations from repeatability and intermediate precision tests were below 0.75% (m/m). Accuracy validation proved that the NIR results were not significantly different (P = 0.09, n = 12) from the results obtained with the reference HPLC method. The limit of quantification for caffeine was 13.7% (m/m) in the tablets. The method was found to be unaffected by NIR source replacement, but the repeatability of the results was affected if the sample holder was not placed in the correct position in the light beam. Routine NIR analysis of caffeine in tablet form was found to be more flexible and much faster than that performed with the HPLC method.
Near-infrared (NIR) reflectance spectroscopy was used to develop a fast identification method for Echinacea purpurea dried milled roots. Method development was carried out using a PLS (partial least-squares) algorithm and pretreatment options. The aim of this qualitative analysis was to confirm the identity of E. purpurea and to detect the presence of fraud, i.e., samples adulterated or substituted by Echinacea angustifolia, Echinacea pallida, or Parthenium integrifolium. Specificity was demonstrated by testing a validation set against the method. A total of 10% of the E. purpurea batches (true samples) and 0% of the false samples from that validation set were misidentified by the method. The misidentification was due to the difference in particle size distribution of one E. purpurea batch compared to that of the other samples. Adulterated E. purpurea samples can be detected at a minimum of 10% of adulteration. This study demonstrates that NIR spectroscopy is a good tool for the fast identification of E. purpurea roots if the samples are milled using the same procedure as for the calibration samples. The method is robust with respect to the origin of the samples and can be used routinely by the pharmaceutical industry or herbal suppliers to avoid mislabeling errors or adulteration.
We have studied by Raman and ir spectroscopy the structure of self-associated polyinosinic acid and polyguanylic acid in aqueous solution. The results are consistent with the formation of a four-stranded complex, which melts cooperatively near 60 degrees C in the case of poly(I) in the presence of K+ ions. The conformation of the ribose in both systems is mixed C2'-endo/C3'-endo, giving a structure that is intermediate between the extremes proposed previously from x-ray diffraction studies. Characteristic Raman bands for the C2'-endo ribose conformation in polyribonucleotides are identified. The four-stranded structure of poly(I) appears to be very flexible, with approximately 15% of the tetrameric segments being disrupted and approximately 30% of the ribose units adopting a disordered conformation prior to melting. This disordering process increases to approximately 75% above the melting transition, with the remaining approximately 25% of the ribose units keeping an ordered C2'-endo or C3'-endo conformation.
This work demonstrates the application of partial least squares (PLS) analysis as a discriminant as well as a quantitative tool in the analysis of edible fats and oils by Fourier transform near-infrared (FT-NIR) spectroscopy. Edible fats and oils provided by a processor were used to calibrate a FT-NIR spectrometer to discriminate between four oil formulations and to determine iodine value (IV). Samples were premelted and analyzed in glass vials maintained at 75°C to ensure that the samples remained liquid. PLS calibrations for the prediction of IV were derived for each oil type by using a subset of the samples provided as the PLS training set. For each oil formulation (type), discrimination criteria were established based on the IV range, spectral residual, and PLS factor scores output from the PLS calibration model. It was found that all four oil types could be clearly differentiated from each other, and all the validation samples, including a set of blind validation samples provided by the processor, were correctly classified. The PLS-predicted IV for the validation samples were in good agreement with the gas chromatography IV values provided by the processor. Comparable predictive accuracy was obtained from a calibration derived by combining samples of all four oil types in the training set as well as a global IV calibration supplied by the instrument manufacturer. The results of this study demonstrate that by combining the rapid and convenient analytical capabilities of FT-NIR spectroscopy with the discriminant and predictive power of PLS, one can both identify oil type as well as predict IV with a high degree of confidence. These combined capabilities provide processors with better control over their process.Paper no. J9230 in JAOCS 77, 29-36 (January 2000)KEY WORDS: Discriminant analysis, fats and oils, Fourier transform near-infrared spectroscopy, iodine value, partial least squares, quality control.The application of near-infrared (NIR) spectroscopy in edible oil analysis has predominantly involved its use for the rapid quantitative determination of the oil content in oilseeds, with relatively little work being carried out on the analysis of oils per se. Most work on NIR oil analysis development has focused on classifying and/or discriminating between oil types as well as detecting adulteration, particularly of olive oil. Bewig et al.(1) used a filter-based NIR instrument to differentiate between four types of oils (cottonseed, canola, soybean, and peanut) using discriminant analysis based on Mahalanobis distance principles. Sato (2) used principal component analysis (PCA) to classify vegetable oils using second-derivative NIR spectra, with PCA providing the benefit of using all the spectral data collected rather than only the data at selected wavelengths. Wesley et al. (3,4) worked on olive oil adulteration and demonstrated that it is possible to effectively use NIR spectroscopy in conjunction with PCA to predict both the purity of olive oil and the type of adulterant as well as to quantitate the adulter...
The Raman spectra of highly concentrated solutions of 5'-GMP at neutral and acid pH were recorded in order to better characterize the structure of the self-aggregates formed in these solutions and their melting behavior. Vibrational coupling of the C=O stretching vibrations in tetrameric units at neutral pH is shown to yield a characteristic pattern of two Raman bands at ca. 1730 and 1680 cm-' (1708 and 1664 cm-' in D 2 0 ) , and an iractive mode at 1678 cm-' in D20. From the intensity of the 1730-cm-' band, proportional to tetramer concentration, and that at 1485 cm-', which reflects the stacking of the bases, the thermal stability of the self-associates formed at neutral pH is shown to be higher for stacked tetramers. At acid pH, the melting of the helical aggregates responsible for the formation of a gel is preceded by the freeing of the hydrogen-bonded phosphate groups, accompanied by a change of conformation from C3'-endo to C2'-endo in some of the associated ribose units. Previous spectroscopic results suggesting the formation of tetramers as an intermediate step in the melting of the gel were not reproduced in this study.
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