Artificial Neural Networks (ANNs) are non-linear computational tools suitable to a great host of practical application due to their flexibility and adaptability. However, their application to the resolution of chemometric problems is relatively recent (early ‘90s). In this communication, different artificial neural networks architectures are presented and their application to different kinds of...

The objective of this paper is to present a review of different calibration and classification methods for functional data in the context of chemometric applications. In chemometric, it is usual to measure certain parameters in terms of a set of spectrometric curves that are observed in a finite set of points (functional data). Although the predictor variable is clearly functional, this problem...

Heparin is a naturally produced, heterogeneous compound consisting of variably sulfated and acetylated repeating disaccharide units. The structural complexity of heparin complicates efforts to assess the purity of the compound, especially when differentiating between similar glycosaminoglycans. Recently, heparin sodium contaminated with oversulfated chondroitin sulfate A (OSCS) has been associa...

Chemometric analysis of a set of one-dimensional (1D) (1)H nuclear magnetic resonance (NMR) spectral data for heparin sodium active pharmaceutical ingredient (API) samples was employed to distinguish USP-grade heparin samples from those containing oversulfated chondroitin sulfate (OSCS) contaminant and/or unacceptable levels of dermatan sulfate (DS) impurity. Three chemometric pattern recogniti...

Transmembrane proteins play vital roles in maintaining the normal cell physiology. They are also important as potential drug targets. Therefore, there is an immense academic and pharmaceutical interest in these proteins. In our lab, we have tried to use chemometric approach along with other computational and experimental methods towards elucidation of transmembrane protein structures and functi...

The final goal of this work is development new genotypes wheat with better properties compared to the standard set. Prediction optimal descriptors and related production characteristics performed using several statistical chemometrical tools, like correlation analysis, principal component cluster analysis linear discriminant analysis. Optimisation directed towards high food quality.

Laser-induced fluorescence was used to evaluate the classification and quality of Chinese oolong teas and jasmine teas. The fluorescence of four different types of Chinese oolong teas-Guangdong oolong, North Fujian oolong, South Fujian oolong, and Taiwan oolong was recorded and singular value decomposition was used to describe the autofluoresence of the tea samples. Linear discriminant analysis...

This work discusses the determination of the provenance of commercial Torrontés wines from different Argentinean provinces (Mendoza, San Juan, Salta and Rio Negro) by the use of UV-vis spectroscopy and chemometric techniques. In order to find classification models, wines (n = 80) were analyzed using UV-Vis region of the electromagnetic spectrum. Principal component analysis (PCA), linear discri...

In this work, information contained in near infrared (NIR) spectra of honeys with protected geographical indication (PGI) "Mel de Galicia" was processed by means of different chemometric techniques to develop an authentication system for this high quality food product. Honey spectra were obtained in a fast and single way, and they were pretreated by means of standard normal variate transformati...

An efficient, fast and cost-effective method for detecting adulteration in perfumes by UV spectroscopy and multivariate analysis is proposed. Classification of perfumes, either as original or fake, was accomplished with the spectroscopic data using chemometric techniques such as principal component analysis (PCA), soft independent modeling of class analogy (SIMCA) and linear discriminant analys...