Partial least-square methodology

Mancozeb is a dithiocarbamate pesticide with a very low solubility in organic and inorganic solvent. In this work we have developed a solvent free, accurate and fast photoacoustic FTIR-based methodology for Mancozeb determination in commercial fungicides. The proposed procedure was based on the direct measurement of the solid samples in the middle infrared region using a photoacoustic detector. A multivariate calibration approach based on the use of partial least squares (PLS) was employed to determine the pesticide content in commercially available formulations. 

The aim of this researeh eonsists on the development of an analytieal methodology to quantify Ca(OH), eontent in neutralized anliydrite samples, using FT-IR speetroseopy and partial least squares quantitative analysis teehnique. 

Luco, J. M. (1999) Prediction of the brain-blood distribution of a large set of drugs from structurally derived descriptors using partial least squares (PLS) methodology. J. Chem. Info. Comput. Sci. 36, 396-404. 

The advent of personal computers greatly facilitated the application of spectroscopic methods for both quantitative and qualitative analysis. It is no longer necessary to be a spectroscopic expert to use the methods for chemical analyses. Presently, the methodologies are easy and fast and take advantage of all or most of the spectral data. In order to understand the basis for most of the current processing methods, we will address two important techniques principal component analysis (PCA) and partial least squares (PLS). When used for quantitative analysis, PCA is referred to as principal component regression (PCR). We will discuss the two general techniques of PCR and PLS separately, but we also will show the relationship between the two. 

The similarity between a Tucker 1 model of a three-way array X and a PCA model of a two-way array X has already been mentioned in Section 4.1. This similarity is the basis for the most popular three-way regression model, the Tucker 1-PLS model. In the literature this regression method has also been called three-way partial least squares regression [Wold et al. 1987]. This name should be avoided for the Tucker 1 version specifically, because it gives rise to much confusion as to what is multi-way methodology. Even though the Tuckerl version of three-way partial least squares regression is indeed one way to implement a three-way method, it is actually the model that assumes the least three-way structure in the data. 

Although colorimetric methods were the earliest to be used for pesticide analysis [203], competitive spectroscopic methodologies for the determination of these pollutants were not developed until the last decade. The spectroscopic determination of several pesticides in mixtures has been the major hindrance, especially when their analytical characteristics are similar and their signals overlap as a result. Multivariate calibration has proved effective with a view to developing models for qualitative and quantitative prediction from spectroscopic data. Thus, partial least squares (PLS) and principal component regression (PCR) have been used as calibration models for the spectrofluorimetric determination of three pesticides (carbendazim, fuberidazole, and thiabendazole) [204]. A three-dimensional excitation-emission matrix fluorescence method has also been used for this purpose (Table 18.3) [205]. 

A novel methodology for the quantification of Sunset Yellow has been developed using image analysis (RGB histograms) and partial least squares (PLSs) regression [38]. The developed method presented many advantages compared with alternative methodologies... 

The experimental retention factors were determined by reversed-phase high-performance liquid chromatography HPLC). Stepwise multiple linear regression (MLR) and partial least square (PLS) methodology were used to investigate the correlation between the retention factor and a number of molecular descriptors for these compounds. The MLR and PLS equations were found to be useful for the estimation and comparison of retention factors k ) for new synthesized phosphoramidic acid derivatives using the selected molecular descriptors. More details are given in the section on HPLC. 

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