Our lab has created several multivariate regression models to predict sample properties from infrared spectra. These models are time consuming to create, and I want to ensure that they can be used on another spectrometer without having to remeasure a bunch of samples. Could you suggest some good methods for doing so? I read an older review article about model transfer, but I imagine some new developments have occurred in the last 10 years.
Note: I know that some methods require standard samples to be measured on the new spectrometer, and methods that do not require this would be preferred.
Dear Zach Baird,
Many remote sensing applications and mineral identification programs have typically used univariate peak ratios or peak recognition software to relate spectral reflectance characteristics to some compositional feature or features present in the sample.Chemometrics is the science of extracting information from chemical systems by data-driven means. Chemometrics is inherently interdisciplinary, using methods frequently employed in core data-analytic disciplines such as multivariate statistics, applied mathematics, and computer science, in order to address problems in chemistry, biochemistry,medicine, biology and chemical engineering. In this way, it mirrors other interdisciplinary fields, such as psychometrics and econometric.
Mid- and Near-Infrared (MIR, NIR) spectra convey characteristic information on material type and sample composition. Intense developments towards more robust and reliable IR spectrometers have made this technique an important chemical analytical method for industrial quality control and in-line process monitoring. New trends in miniaturization of spectrometers facilitate a wide range of possible applications in fields such as food & beverage, healthcare, fuel/media quality control, and environmental analytics. Multivariate data analysis is mandatory for data evaluation of NIR spectra. The development of novel chemometric tools also plays an important role in promoting new applications of IR spectroscopy in the near future.
1. Rapid compositional analysis methods based on near-infrared (NIR) reflectance spectroscopy combined with multivariate statistics are well-established and widely used in agriculture.
2. Rapid compositional analysis methods have been developed for a number of different potential bioenergy feedstocks .
Laser-induced breakdown spectroscopy (LIBS) is an atomic emission technique by focusing a high-power, short-pulse laser on the sample surface to form a plasma and analyzing the emitted spectrum to obtain the chemical composition of the sample. LIBS technology exhibits numerous appealing features that distinguish it from conventional analytical spectrochemical techniques, such as little to no sample preparation and capability to analyze any kind of sample. It has been applied to remote sensing, forensic analysis , ceramic raw materials , wood products , determination of major or minor elements in metal coal analysis and many other fields. Commercial analytical instrument has also been developed to provide LIBS measurement on laboratory bench.
Regards,
Prem Baboo
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