Exploratory Analysis of South American Wines Using Artificial Intelligence.

In this work, microwave-induced plasma optical emission spectrometry was applied for multielement determination in South American wine samples. The analytes were determined after acid digestion of 47 samples of Brazilian and Argentinian wines. Then, logistic regression, support vector machine, and decision tree for exploratory analysis and comparison of these algorithms in differentiating red wine samples by region of origin were carried out. All wine samples were classified according to their geographical origin. The quantification limits (mg L-1) were P: 0.06, B: 0.08, K: 0.17, Mn: 0.002, Cr: 0.002, and Al: 0.02. The accuracy of the method was evaluated by analyzing the wine samples by ICP OES for results' comparison. The concentrations in mg L-1 found for each element in wine samples were as follows: Al (< 0.02-1.82), Cr (0.15-0.50), Mn (< 0.002-0.8), P (97-277), B (1.7-11.6), Pb (< 0.06-0.3), Na (8.84-41.57), and K (604-1701), in mg L-1.

Support vector machine and PCA for the exploratory analysis of Salvia officinalis samples treated with growth regulators based in the agronomic parameters and multielement composition.

The objective of this work was to evaluate the influence of different growth regulators on the mineral and total phenolic contents of Salvia officinalis. The samples received the applications of salicylic acid (AS); gibberellic acid (GA3); abscisic acid (ABA) and solution without regulators (control). The exploratory evaluation of the samples was carried out through the Principal Component Analysis (PCA). In addition, has been used supervised learning methods with support vector machine (SVM) algorithms to classify the samples. The phenolic and total flavonoid contents were higher in the plants treated with the regulators. The element found in the highest concentration in Salvia officinalis was N. Plants sprayed with ABA showed higher concentrations of N, K, and Mn; Fe and Al were higher with ABA and gibberellin application, while the application of AS provided the highest accumulation of P. The application of plant regulators improves the nutraceutical properties of Salvia officinalis.

Exploratory analysis in the evaluation of stress due to aluminum presence in Physalis angulata L. and multielement determination by microwave-induced plasma optical emission spectrometry (MIP OES).

The present work aimed to analyze the mineral nutrition of Physalis angulata L. under stress by aluminum in the nutrient solution. The treatments consisted of five different concentrations of aluminum in the nutrient solution (0, 0.04, 0.08, 0.12, and 0.16 mmol L-1) in the AlCl3 form. The plants were exposed to Al for 30 days. Subsequently, nutritional and aluminum analyses were performed on plant tissue. The data were submitted to analysis of variance (p < 0.05), and, in case of significance, the regression study was performed as well as hierarchical cluster analysis (HCA) and principal component analysis (PCA) were used. The formation of four groups occurred, where we can observe the similarity and differences in the treatments between them. The separation of the treatments into groups reflected the heterogeneity of the treatments about the aluminum levels in the nutrient solution, evidencing its phytotoxicity level in Physalis angulata plants. Among the analyzed variables, P, K, Ca, Mg, Fe, Mo, and Zn were the most influential ones demonstrated by principal component analysis (PCA). The stress of 0.16 mmol L-1 of Al increased the phosphorus contents in the stems and roots and the potassium, copper, and molybdenum contents in all parts of the plants. In contrast, Al reduced the levels of calcium, magnesium, iron, and zinc in P. angulata plants. Iron being the micronutrient that showed the largest reduction, followed by zinc in the leaves. The highest levels of aluminum were found in the roots.

D-optimal mixture design for the optimization of extraction induced by emulsion breaking for multielemental determination in edible vegetable oils by microwave-induced plasma optical emission spectrometry.

A sample pretreatment based on an extraction process by emulsion breaking for multi-element determination in edible oils was developed. The determination of eight trace elements (Al, Ba, Cu, Cr, P, Ni, Ti, and Zn) was carried out by microwave-induced plasma optical emission spectrometry (MIP OES) after the extraction procedure. A D-optimal mixture experimental design was used to obtain the best experimental conditions for the extraction induced by emulsion breaking (EIEB). The proportion of HNO3 solution, Triton X-100 solution and sample was evaluated in a multivariate manner. The best recovery efficiency was obtained with 1.0 mL of 30% (v/v) HNO3, 1.0 mL of 30% (w/v) Triton-X 100 and 3.0 mL of the sample. The precisions, established as the relative standard deviation (RSD, %), were better than 2.5% for all analytes. The developed method was applied to the analysis of commercial vegetable oils with low limits of detection and good precision.