Current Analytical Chemistry - Volume 8, Issue 2, 2012

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An investigation was carried out to assess the suitability of an approach based on a metric generalization of the Partial Least Square Regression to identify and discriminate chain dependence relationships between geology, soil properties and grape composition. The study area was Telesina Valley (Campania Region, southern Italy), a foremost vineyard district with the Falanghina grape cultivar. Five geopedological units, with Read More

In a recent study of about 6500 white and red Portuguese wines, a formal method of classification was considered based on 11 key chemical and physical properties. These properties were all deemed as being important for influencing the quality of wine that is produced in the area. In this paper, we explore these physiochemical characteristics and begin by providing a glimpse into understanding the link between these cha Read More

Evaluating the accuracy of classification methods for rating wines based on their physical and chemical characteristics is an important part of the wine industry. An ability to accurately predict the quality of wine based on this information provides vast opportunity for applications in other areas of science. Recently, a method was proposed that utilises data mining techniques for the prediction of the quality of wines based solely o Read More

In this paper we present a four-step procedure for performing a Tucker2 analysis on three-way data in the case a number of observations are missing. The procedure consists of (1) creating multiple complete data sets via multiple imputation of the missing data, (2) analysing these data sets with the Tucker2 model, (3) combining both the row and the column component matrices of these analyses to create centroid soluti Read More

Routinely, the multi-response Partial Least-Squares (PLS) is used in regression and classification problems showing good performances in many applied studies. In this paper, we aim to present PLS via spline functions focusing on supervised classification studies and showing how PLS methods historically belong to L2 boosting family. The theory of the PLS boost models is presented and used in classification studies. As a natural Read More

Bagging and boosting have become increasingly important ensemble methods for combining models in the data mining and machine learning literature. We review the basic ideas of these methods, propose a new robust boosting algorithm based on a non-convex loss function and compare the performance of these methods to both simulated and real data sets with and without contamination.

The analysis of high dimensional dataset is recurrently used in chemometrics where the data are presented in the form of digitized spectra (NIR). Statistical tool, as Discriminant Analysis, is frequently used in this field to classify object in predefined categories. But, by the fact that this kind of dataset presents the number of statistic units relatively small in comparison to the number of variables, the classical Discriminant Analys Read More

In chemistry, multiblock datasets are easily encountered with variables of different natures, or measured at different times for example, here, we use the sequential multiblock regression method GOMCIA-PLS1 to predict quantitative variables from several predictors gathered according to their nature and used simultaneously. In this article, it will be applied to predict a chemical variable from Near Infrared Spectrometry (NIRS) c Read More

This study demonstrated the use of visible-near infrared (vis-NIR) reflectance spectroscopy and partial least squares regression (PLSR) for the effective analysis of important properties of Mediterranean soils from southern Italy. Understanding soil properties is an essential pre-requisite for sustainable land management. Assessment of these properties has long been gained through conventional laboratory analysis, which is Read More

Polycyclic Aromatic Hydrocarbons (PAHs) are a group of carcinogenic contaminants widespread in the environment. PAHs are produced by both anthropogenic and natural processes. Difficulties exist in identifying their origins. This paper reports a practical application of Principal Component Analysis (PCA) and Principal Component Regression (PCR) to identify the pyrolytic, petrogenic and diagenesis sources of PAH pollution in Read More

A continuum approach for canonical correlation analysis based on a single tuning parameter is proposed. One of its noteworthy features is that it is straightforward and simple. It establishes a bridge between unfold Principal Components Analysis and Canonical Correlation Analysis. Interesting properties related to the method of analysis are also discussed. This makes it possible to highlight the rationale behind the continuum ap Read More

Due to the well established difference in the pharmaco/toxicological profile of many amino acid enantiomers, and also for typifying the food quality and origin, the exact knowledge of their presence and relative ratio in foodstuffs, is a matter of growing interest. In this setting, with an interest in identifying the presence of D-amino acids in a selected set of cheese samples, and with the aim to introduce a fast and easily accessible Read More

This paper proposes a hybrid chemometric method named DOSC-WPT-PLS, which is based on partial least squares (PLS) regression combined with direct orthogonal signal correction (DOSC) and wavelet packet transform (WPT) as pre-processing tools for the simultaneous spectrophotometric kinetic determination of Mn (II), Ag (I) and Fe (III). This method combined with kinetic approach is used for the first time and no past refe Read More