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This tutorial aims at providing guidelines and practical tools to assist with the analysis of hyperspectral images. Topics like hyperspectral image acquisition, image pre-processing, multivariate exploratory analysis, hyperspectral image resolution, classification and final digital image processing will be exposed, and some guidelines given and discussed. Due to the broad character of current applications and the vast number of multivariate methods available, this paper has focused on an industrial chemical framework to explain, in a step-wise manner, how to develop a classification methodology to differentiate between several types of plastics by using Near infrared hyperspectral imaging and Partial Least Squares - Discriminant Analysis. Thus, the reader is guided through every single step and oriented in order to adapt those strategies to the user's case.

Aquaphotomics is a new discipline that provides a framework for understanding changes in the structure of water caused by various perturbations, such as variations in temperature or the addition of solutes, using near infrared spectroscopy (NIRS). One of the main purposes of aquaphotomics is to identify water bands as main coordinates of future absorbance patterns to be used as biomarkers. These bands appear as consequence of perturbations in the NIR spectra. Curve resolution techniques may help to resolve and find new water bands or confirm already known bands. The aim of this study is to investigate the application of multivariate curve resolution-alternating least squares (MCR-ALS) to characterise the effects of various perturbations on the NIR spectra of water in terms of hydrogen bonding. For this purpose, the perturbations created by temperature change and the addition of four solutions of different ionic strength and Lewis acidity were studied (NaCl, KCl, MgCl(2) and AlCl(3), with concentrations ranging from 0.2 to 1 mol L(-1) in steps of 0.2 mol L(-1)). Transmission spectra of all salt solutions and pure water were obtained at temperatures ranging from 28 to 45°C. We have found that three distinct components with varying temperature dependence are present in water perturbed by temperature. The salt solutions studied exhibited similar trends with respect to the temperature perturbation, while the peak locations of their MCR-ALS pure components varied according to the ionic strength of the salt used.

The aim of this paper is to show how it is possible to extract analytical information from images acquired with a flatbed scanner and make use of this information for real time control of a nickel plating process. Digital images of plated steel sheets in a nickel bath are used to follow the process under degradation of specific additives. Dedicated software has been developed for making the obtained results accessible to process operators. This includes obtaining the RGB image, to select the red channel data exclusively, to calculate the histogram of the red channel data and to calculate the mean colour value (MCV) and the standard deviation of the red channel data. MCV is then used by the software to determine the concentration of the additives Supreme Plus Brightner (SPB) and SA-1 (for confidentiality reasons, the chemical contents cannot be further detailed) present in the bath (these two additives degrade and their concentration changes during the process). Finally, the software informs the operator when the bath is generating unsuitable quality plating and suggests the amount of SPB and SA-1 to be added in order to recover the original plating quality.

In this work, the time-dependent conjugation process between a thiolated molecule (with anti-parkinsonian properties) and gold nanoparticles has been monitored and studied by the combined use of fast acquisition Ultra Violet-Visible (UV-Vis) spectra and the ability of Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) technique. From the highly informative kinetic profiles obtained it was possible to extract quantitative and qualitative information of the conjugation process which includes i) time-dependent concentration profiles and pure spectra of species involved on conjugation process, ii) estimation of molecule concentration necessary for the completeness of the conjugation reaction, iii) molecule footprint and iv) free energy of molecule adsorption.

A new treatment of kinetic-enzymatic data, joining the benefits of hard- and soft-modelling methods, is proposed for the kinetic resolution and simultaneous quantification of xanthine oxidase induced oxipurines (hypoxanthine and xanthine) and uric acid in human urine without any further separation. These three analytes show highly overlapped spectral bands in the range of 232–320 nm and urine contains absorbing species in this wavelength range that behave as a constant interference throughout the monitoring of the kinetic experiment. The proposed method allows the determination of the analytes in human urine by simultaneous analysis of the urine sample and a few (even only one) standards of pure analyte mixtures of hypoxanthine and xanthine in aqueous solution. An iterative mixed hard- and soft-modelling multivariate curve resolution (HS-MCR) algorithm, which includes a hard-modelling constraint based on the enzymatic model in the parent multivariate curve resolution-alternating least squares method (MCR-ALS), is applied to a data set formed by the standards and the urine samples. Hard-modelling is applied to the concentration profiles of the three analytes in the standards, whereas soft-modelling on the analytes and the urine in the samples gives the quantitative information. As a result, quantitative information similar in quality to that obtained by separation techniques (HPLC and HPCE) and other chemometric approaches (PLS and N-PLS) is obtained with less experimental effort and a much smaller number of standards in aqueous solution that do not need to contain the interferences present in the samples.

Mixed hard- and soft-modelling multivariate curve resolution (HS-MCR) is applied to study and to monitor complex enzymatic systems. Working under the basis of the soft-modelling technique multivariate curve resolution-alternating least squares (MCR-ALS), a hard constraint is introduced to force some or all concentration profiles to fulfil an enzymatic model. In this way, improvements to the application of pure hard- or pure soft-modelling are achieved. The enzymatic reactions of different mixtures of hypoxanthine, xanthine and uric acid with xanthine oxidase are studied. This is a complex enzymatic process, where uric acid acts as a linear competitive inhibitor. The reactions were monitored with UV–vis spectrophotometry coupled to a stopped-flow module. This work has two aims, both of them focusing on different aspects linked to modelling enzymatic systems using HS-MCR. The first goal is related to the elucidation of the real enzymatic mechanism when one of the chemical substances involved in the process apparently deviates from the mechanism found in the literature. The second one focuses on modelling the enzymatic reaction in the presence of a biological interference, such as human urine. The elucidation of the real mechanism of this enzymatic process and of the behaviour of the involved chemical species in a natural absorbing medium are good examples of situations that can benefit from mixed modelling approaches involving the best of hard- and soft-modelling methodologies.

Desktop flatbed scanners are very well-known devices that can provide digitized information of flat surfaces. They are practically present in most laboratories as a part of the computer support. Several quality levels can be found in the market, but all of them can be considered as tools with a high performance and low cost. The present paper shows how the information obtained with a scanner, from a flat surface, can be used with fine results for exploratory and quantitative purposes through image analysis. It provides cheap analytical measurements for assessment of quality parameters of coated metallic surfaces and monitoring of electrochemical coating bath lives. The samples used were steel sheets nickel-plated in an electrodeposition bath. The quality of the final deposit depends on the bath conditions and, especially, on the concentration of the additives in the bath. Some additives become degraded with the bath life and so is the quality of the plate finish. Analysis of the scanner images can be used to follow the evolution of the metal deposit and the concentration of additives in the bath. Principal component analysis (PCA) is applied to find significant differences in the coating of sheets, to find directions of maximum variability and to identify odd samples. The results found are favorably compared with those obtained by means of specular reflectance (SR), which is here used as a reference technique. Also the concentration of additives SPB and SA-1 along a nickel bath life can be followed using image data handled with algorithms such as partial least squares (PLS) regression and support vector regression (SVR). The quantitative results obtained with these and other algorithms are compared. All this opens new qualitative and quantitative possibilities to flatbed scanners.