Automated system and method for spectroscopic analysis

A method for generating a modeling equation is provided comprising the steps of

• (a) operating an instrument so as to generate and store a spectral data set of diffuse reflectance, clear transmission, or diffuse transmission spectrum data points over a selected wavelength range, the spectral data set including spectral data for a plurality of samples;
• (b) generating and storing a constituent value for each of the plurality of samples, the constituent value being indicative of an amount of a target substance in its corresponding sample;
• (c) dividing the spectral data set into a calibration subset and a validation subset;
• (d) transforming the spectral data in the calibration subset and the validation subset by applying a plurality of a first mathematical functions to the calibration subset and the validation subset to obtain a plurality of transformed validation data subsets and a plurality of transformed calibration data subsets;
• (e) resolving each transformed calibration data subset in step (d) by at least one of a second mathematical function to generate a plurality of modeling equations;
• and
• (f) identifying the modeling equation which provides the best correlation between the spectral data in the validation subset and the corresponding constituent values in the validation subset.

A computer executable process, operative to control a computer, stored on a computer readable medium, for determining analyzing a set of data on a computer readable medium, the set of data including, for each of a plurality of samples, corresponding spectral data and a corresponding constituent value, the process comprising the steps of:

• dividing the spectral data into a calibration sub-set of spectral data and a validation sub-set of spectral data;
• applying a plurality of data transforms to the spectral data in the validation sub-set and the calibration sub-set;
• applying one or more of a partial least squares, a principal component regression, a neural net, or a multiple linear regression analysis on the transformed and untransformed data sets of the spectral data in the calibration sub-set to obtain a plurality of modeling equations;
• applying the spectral data in the validation sub-set to each of the plurality of modeling equations to obtain corresponding values;
• and processing the values in order to select a best modeling equation for analyzing the spectral data.

An automated method for modeling spectral data, the spectral data generated by one of diffuse reflectance, clear transmission, or diffuse transmission, comprising the steps of

• accessing a set of spectral data, the set of spectral data including, corresponding spectral data for each of a plurality of samples, the spectral data for each of the plurality of samples having associated therewith at least one constituent value, the at least one constituent value being a reference value for a target substance in the sample which is measured by a independent measurement technique;
• applying a plurality of data transforms to the set of spectral data to generate, for each sample, a set of transformed and untransformed calibration data;
• dividing the set of spectral data, with its associated constituent values, into a calibration sub-set and a validation sub-set;
• applying one or more of a partial least squares, a principal component regression, a neural net, or a multiple linear regression analysis on the transformed and untransformed calibration data sub-sets to obtain corresponding modeling equations for predicting the amount of the target substance in a sample;
• identifying a best modeling equation as a function of the correlation between the spectral data in the validation sub-set and the corresponding constituent values in the validation sub-set.