Near-infrared analysis moisture determination

Near-Infrared Spectroscopy. Near-infrared (NIR) spectroscopy is a technique that has been around for some time but, like NMR spectroscopy, has only recently been improved and developed for on-line applications. Near-infrared analysis (NIRA) is a nondestructive technique that is versatile in the sense that it allows many constituents to be analyzed simultaneously 112, 113). The NIR spectrum of a sample depends upon the anharmonic bond vibrations of the constituent molecules. This condition means that the temperature, moisture content, bonding changes, and concentrations of various components in the sample can be determined simultaneously. In addition, scattering by particles such as sand and clay in the sample also allows (in principle) the determination of particle size distributions by NIRA. Such analyses can be used to determine the size of droplets in oil-water emulsions. 

The optimal moisture content of the dried granulation needs to be determined. High moisture content can result in (1) tablet picking or sticking to tablet punch surfaces and (2) poor chemical stability as a result of hydrolysis. An overdried granulation could result in poor hardness and friability. Moisture content analysis can he performed using the conventional loss-on-drying techniques or such state-of-the-art techniques as near infrared (NIR) spectroscopy. 

The analytical method for moisture determination must be validated before use during process validation studies. There are numerous techniques for moisture analysis that range from physical methods, such as loss on drying, to chemical methods, such as Karl Fisher titration. A comparative review of the conventional techniques are presented in an overview [32], The measurement of residual moisture is lyophilized pharmaceuticals by near-infrared (NIR) spectroscopy has recently been expanded [33]. 

Last and Prebble [51 ] developed a near-infrared reflectance (NIR) method for the determination of moisture in an experimental freeze-dried injection product. NIR spectra were collected through the bases of unopened product vials using a horizontal instrument accessory. The samples in these vials were then used for Karl Fischer analysis to generate a standard curve for the analysis. The NIR data must be correlated with an accepted residual moisture technique in order to yield a meaningful result. This article states that NIR accuracy and precision in this application are not consistent with allowing the use of the current method in anything but a screening role. 

Again, samples for Tg measurement are prepared similarly to those for adsorption study using desiccators. Each desiccator maintained a different relative humidity by using different saturate salts as described previously in the water adsorption study. As a result, different levels of moisture content were achieved for the samples in different desiccators. The driest samples were obtained by keeping them sealed after freeze-drying until sample preparation. The moisture content of each sample was determined by near-infrared content analysis. The near-infrared (NIR) used here is provided by a FOSS Model 5000 Rapid Content Analyzer. 

The degree of the instrumentation of pharmaceutical unit operations has increased. This instrumentation provides information on the state of the process and can be used for both process control and research. A central part of optimizing production is increasing the level of automation. Besides monitoring the process parameters, a number of approaches are being developed for measuring the moisture of the product to determine the end point of the process, and consequently the in-process particle size analysis. A number of publications discuss the on-line moisture measurement and process end point determination using near-infrared (NIR). 

Since the first-ever application of NIR by Hart et al. in 1962 to the determination of moisture in seeds (6), the bibliography of NIRS technology has proliferated until it now numbers over 35,000 entries, many of which describe a very diverse assortment of applications to grains and seeds. The main areas have been composition analysis, analysis for prediction of functionality, and classification by NIR discriminant or classification analysis (NIRCA). Near-infrared spectroscopy has been applied to the analysis of many of the above commodities. Over 30 factors have been successfully predicted in cereals and pulses, and over 20 factors in oleaceous seeds. These applications have recently been comprehensively reviewed by Delwiche (7) and Dyer (8). 

Multivariate modeling is the basis of quantitative analysis by near infrared spectrometry (Topic Ell) to determine moisture or fats in cereals, meat and other foodstuffs. It is particularly applicable to environmental analysis where complex and inter-related variables affect the distributions of a wide range of organic compounds and elements occurring naturally or as pollutants. 

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