M.P. Callao

Resolution of phenol, and its di-hydroxyderivative mixtures by excitation–emission fluorescence using MCR-ALS: Application to the quantitative monitoring of phenol photodegradation

The photodegradation of phenol using TiO(2) as catalyst was studied and monitored by fluorescence excitation-emission matrix (EEM). Hydroquinone, catechol and resorcinol were the dihydroxyderivative intermediates although in lower concentrations than phenol. The data were analyzed using a three-way multivariate curve resolution alternating least squares method (MCR-ALS) and augmented matrices. The procedure was assessed using synthetic samples prepared with a {4,3} Simplex-lattice design that considered a representative range of analyte concentrations. The results were analyzed in terms of overall RMSEP for the overall data set. A detailed study was made of how the analytes behaved at each concentration level and how the concentration of the other species affected the process. The method was used to quantify phenol in photodegradation samples with an overall prediction error of 5.37%. The conversion values were fitted to pseudo first-order kinetics and the apparent rate constant was calculated to be -4.9x10(-4)+/-5.2x10(-5)min(-1).

Sequential injection analysis with second-order treatment for the determination of dyes in the exhaustion process of tanning effluents.

A sequential injection (SI)-DAD spectrophotometric method to control the exhaustion of dyes in a mixture of three dyes from a tanning industry process has been developed. It is based on an interdiffusion process of the sample and reagents which leads to a gradual fall in pH through the channel to the detector recording a data matrix. The aim of this paper is to develop a second-order calibration model that is unaffected by interferents by applying multivariate curve resolution with alternating least squares (MCR-ALS). We obtained a linear calibration in the 5-30mgl(-1) range with a correlation coefficient of 0.999 for each dye with detection limits of 2.6, 3.9 and 2.1mgl(-1) for Acid Red, Acid Brown and Acid Orange, respectively. The simultaneous determination of the three dyes from tanning samples showed a satisfactory precision for the three analytes. The method has been validated comparing the concentration of some spiked samples with the expected concentration using a t-paired test. When we used this method to study the exhaustion of dyes, we found that there were several stages in this process. These data may be the key to optimising the exhaustion process.

Detection of adulterants in grape nectars by attenuated total reflectance Fourier-transform mid-infrared spectroscopy and multivariate classification strategies

There is no any doubt about the importance of food fraud control, as it has implications in food safety and in consumer health. Focusing on fruit beverages, some types of adulterations have been detected more frequently, such as substitution with less expensive fruits. A methodology based on attenuated total reflectance Fourier-transform mid-infrared spectroscopy (ATR-FTIR) and multivariate classification was applied to detect whether grape nectars were adulterated by substitution with apple juice or cashew juice. A total of 126 samples were obtained and analyzed. Two strategies were proposed: one-class and multiclass approaches. Soft independent modeling of class analogy (SIMCA), partial least squares discriminant analysis (PLS-DA) and partial least squares density modeling (PLS-DM) were used to build the models. Among them, PLS-DA presented the best performance with a sensitivity and specificity of nearly 100%. The multiclass strategy was preferred if the adulterants to be studied are known because it provides additional information.

Variable selection for multivariate classification aiming to detect individual adulterants and their blends in grape nectars

During the quality inspection control of fruit beverages, some types of adulterations can be detected, such as the addition or substitution with less expensive fruits. To determine whether grape nectars were adulterated by substitution with apple or cashew juice or by a mixture of both, a methodology based on attenuated total reflectance Fourier transform mid infrared spectroscopy (ATR-FTIR) and multivariate classification methods was proposed. Partial least squares discriminant analysis (PLS-DA) and soft independent modeling of class analogy (SIMCA) models were developed as multi-class methods (classes unadulterated, adulterated with cashew and adulterated with apple) with the full-spectra. PLS-DA presented better performance parameters than SIMCA in the classification of samples with just one adulterant, while poor results were achieved for samples with blends of two adulterants when using both classification methods. Three variable selection methods were tested in order to improve the effectiveness of the classification models: interval partial least squares (iPLS), variable importance in projection scores (VIP scores) and a genetic algorithm (GA). Variable selection methods improved the performance parameters for the SIMCA and PLS-DA methods when they were used to predict samples with only one adulterant. Only PLS-DA coupled with iPLS was able to classify samples with blends of two adulterants, providing sensitivity values between 100% and 83% at 100% specificity for the three studied classes.