Spectroscopy spectral calibration

Samola and Urleb [15] reported qualitative and quantitative analysis of OTC using near-infrared (NIR) spectroscopy. Multivariate calibration was performed on NIR spectral data using principle component analysis (PCA), PLS-1, and PCR. 

NIR Diffuse-reflection (Spectral resolution 16 5300-4000 cm ) single-element detector spectroscopy cmspectral calibration range 9050-7450, 7100-5570, ... 

NIR diffuse reflection single-element detector spectroscopy (spectral resolution 16 cm spectral calibration range 9050 - 7450 cm 7100 - 5570 cm... 

NIR diffuse reflection imaging spectroscopy (spectral resolution 24cm spectral calibration range 10417-6017cm... 

Sections on matrix algebra, analytic geometry, experimental design, instrument and system calibration, noise, derivatives and their use in data analysis, linearity and nonlinearity are described. Collaborative laboratory studies, using ANOVA, testing for systematic error, ranking tests for collaborative studies, and efficient comparison of two analytical methods are included. Discussion on topics such as the limitations in analytical accuracy and brief introductions to the statistics of spectral searches and the chemometrics of imaging spectroscopy are included. 

During the upcoming discussion of quantitative calibration methods, a specific example involving NIR transmission spectroscopy of 70 different styrene-butadiene copolymers [52] will be used help illustrate these methods. In this example, complete laboratory NMR analyses of all of the copolymers were available, which for each sample provided the concentrations of the four known chemical components di-butadiene, frani-butadiene, 1,2-butadiene, and styrene. The NIR spectra of these copolymer samples over the spectral range 1570-1850nm are shown in Figure 12.9. 

T. Isaksson and T. Ntes, Selection of samples for calibration in near-infrared spectroscopy. Part II selection based on spectral measurements, Appl Spectrosc., 44, 1152-1158 (1990). 

Near Infrared Reflectance Analysis (NIRA) is in use at over 5000 sites for the analysis of multiple constituents in food and other products. The technology is based upon correlation transform spectroscopy, which combines NIR spectrophotometry and computerized analysis of a "learning set" of samples to obtain calibrations without the need for detailed spectroscopic knowledge of factors being analyzed. The computer can obtain spectral characteristics of the analyte (based upon a correlation with data from an accepted reference analysis) without separation of the sample s constituents. 

The initial role of vibrational spectroscopy is to suggest the types of functional groups that are present. In favorable cases, this can lead on to the detection of particular surface species through the recognition of their more complete spectral patterns. Subsequently, when structural calibration has been achieved or confirmed by diffraction methods, vibrational spectra provide much the most efficient means of exploring the incidence of the various types of adsorbed species on a wide range of surfaces. 

Isaksson, T. and Naes, T., Selection of Samples for Calibration in Near-Infrared Spectroscopy. Part II Selection Based on Spectral Measurements Appl. Spectrosc. 1990, 44, 1152-1158. 

In order to achieve the demanded combination of temporal resolution and accurate yields, FTIR spectroscopy appears a suitable method for collecting data in combination with robust calibrations for quantitative results. Cigarette smoke is known to contain thousands of compounds and the amounts of the vapor phase components in the sidestream smoke are emitted at levels 2-10 times the mainstream amounts [66,67]. In order to utilize vibrational-rotational lines as reported in previous studies [63,64], FT-IR spectra would have to be collected at a spectral resolution of 1 cm 1 or better. Improved temporal resolution of the sidestream concentration profile could only be attained at an equivalent signal-to-noise level by collecting spectra at lower resolution. However, at lower resolution (below 1 cm x) the vibrational-rotational lines would no longer be spectroscopically resolved and accessible to quantification. 

New methods for non-destructive quantitative analysis of additives based on MIR spectra and multivariate calibration have been presented [67, 68], One of the limitations in the determination of additive levels by MIR spectroscopy is encountered in the detection limit of this technique, which is usually above the low concentration of additive present, due to their heavy dilution in the polymer matrix. The samples are thin polymer films with small variations in thickness (due to errors in sample preparation). The differences in thickness cause a shift in spectra and if not eliminated or reduced they may produce non-reliable results. Methods for spectral normalisation become necessary. These methods were reviewed and compared by Karstang et al. [68]. MIR is more specific than UV but the antioxidant content may be too low to give a suitable spectrum [69]. However, this difficulty can be overcome by using an additive-free polymer in the reference beam [67, 68, 69, 70]. On the other hand, UV and MIR have been successfully applied to quantify additives in polymer extracts [71, 72, 66]. 

OLS is a simple, yet powerful explicit calibration technique from which the result can be easily interpreted with little ambiguity. However, the requirement that all spectral components be known reduces the application of OLS to quantitative biological spectroscopy. 

A limiting factor in noninvasive optical technology is variations in the optical properties of samples under investigation that result in spectral distortions44 8 and sampling volume (effective optical path length) variability 49-54 These variations will impact a noninvasive optical technique not only in interpretation of spectral features, but also in the construction and application of a multivariate calibration model if such variations are not accounted for. As a result, correction methods need to be developed and applied before further quantitative analysis. For Raman spectroscopy, relatively few correction methods appear in the literature, and most of them are not readily applicable to biological tissue.55-59... 

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