Ora-pro-nobis (Pereskia aculeata Mill) is an unconventional food plant (UFP) rich in proteins, vitamins, fibers, and antioxidants. In this study, ora-pro-nobis leaves were investigated as a proof of concept by near-infrared (NIR) spectroscopy concerning the storage time (from collection to 12 days), packaging system: styrofoam-based packaging covered with stretchable polychloride vinyl (PVC) film, and vacuum packaging (nylon/poly), temperature (at room temperature of 20 ºC, and in the refrigerator at 4 ºC), and sanitization condition (washed and without washing). Principal component analysis (PCA) was applied to augmented matrices, showing that unwashed leaves stored in the refrigerator with styrofoam-based packaging covered with PVC film were better preserved over time. Furthermore, it has been suggested that NIR absorptions are related to proteins, carbohydrates, lipids, vitamins, antioxidants, and water from ora-pro-nobis leaves and their physiological reactions over time. By combining NIR spectroscopy and chemometrics, a complete understanding of the shelf life of ora-pro-nobis leaves was achieved.

In recent years, the consumption of organic foods has considerably increased. The basic difference between organic and non-organic food products is the way in which they are produced and processed, and the authenticity of these products is a current trend in food science and analytical chemistry. In this sense, the objective of this work was to propose an analytical methodology based on near-infrared spectroscopy (NIR) coupled with partial least squares with discriminant analysis (PLS-DA) for authentication of organic Origanum vulgare L., a spice known for its characteristic aroma and among the most popular condiments in the world, receiving prominence for its antimicrobial, antioxidant and anti-inflammatory properties. As a result, NIR/PLS-DA was able to promote a rapid and non-destructive analysis in the authentication of organic samples. Important spectral regions for this authentication were highlighted by VIP scores being from 1350 to 1430 nm, and from 1450 to 1480 nm where it is observed absorption due to ROH, ArOH, CONH2, RNH2, CONHR, CH, CH2, and CH3.

Resumo: O objetivo deste trabalho foi avaliar modelos de calibração multivariada para previsão de teores de lipídios totais, proteína bruta e umidade em grãos de soja triturados, com uso da espectroscopia de infravermelho próximo e do método de mínimos quadrados parciais (PLS). Foram utilizadas 300 amostras de grãos de soja trituradas, avaliadas em duplicata, quanto a medidas de referência e espectrais. Os modelos PLS para lipídios totais, proteína bruta e umidade foram validados por meio das figuras de mérito para exatidão e precisão, respectivamente, de 0,75 e 0,67 para lipídios totais, 0,51 e 0,46 para proteína bruta, e 0,97 e 0,99 para umidade. Os modelos PLS desenvolvidos para lipídios totais, proteína bruta e umidade podem ser utilizados como metodologia alternativa para determinação de parâmetros físico-químicos e, portanto, podem ser aplicados no controle de qualidade em indústrias processadoras de soja.

Abstract: The objective of this work was to evaluate multivariate calibration models to predict total lipids, crude protein, and moisture content in grinded soybean grains using near-infrared spectroscopy and partial least squares (PLS). Three hundred samples of grinded soybean, evaluated in duplicate, were used for reference and spectral measurements. The PLS models for total lipids, crude protein, and moisture were validated by figures of merit for accuracy and precision, respectively, of 0.75 and 0.67 for total lipids, 0.51 and 0.46 for crude protein, and 0.97 and 0.99 for moisture. The PLS models developed for total lipids, crude protein, and moisture can be used as an alternative methodology for the determination of physicochemical parameters, and, therefore, they can be applied in quality control in soybean processing industries.

Principal component analysis (PCA) is a chemometric method that allows for the extraction of chemical information that would otherwise be impossible to determine. Teaching chemometrics to undergraduates can contribute to the overall professional development and training of new teachers, whose profiles have been gaining attention due to the current demand for data interpretation. In this study, a didactic experiment involving PCA is proposed. Spectrophotometry was used in the ultraviolet-visible (UV-Vis) region to assess the behavior of anthocyanins extracted from red cabbage at different pH values. The results suggest the possible separation of anthocyanin structures into three distinct groups, according to their chemical characteristics displayed in acid, neutral, and basic media. The objective is to develop educational materials targeted to undergraduate courses, which encompass a larger number of concepts and introduce instrumental techniques currently being employed in both academic research and the industrial sector. Specifically, the proposed experiment introduces concepts related to spectrophotometry in the UV-Vis range and the PCA chemometric method. The materials used are easily accessible, and UV-Vis spectroscopy equipment is less expensive in comparison with other spectroscopy methods.

Multivariate Curve Resolution with Alternating Least Squares (MCR-ALS) is a resolution method that has been efficiently applied in many different fields, such as process analysis, environmental data and, more recently, hyperspectral image analysis. When applied to second order data (or to three-way data) arrays, recovery of the underlying basis vectors in both measurement orders (i.e. signal and concentration orders) from the data matrix can be achieved without ambiguities if the trilinear model constraint is considered during the ALS optimization. This work summarizes different protocols of MCR-ALS application, presenting a case study: near-infrared image spectroscopy.

Anthocyanins are among the most important plant pigments. Due to their potential benefits for human health, there is considerable interest in these natural pigments. Nonetheless, there is great difficulty in finding a technique that could provide the identification of structurally similar compounds and estimate the number and concentration of the species present. A lot of techniques have been tried to find the best methodology to extract information from these systems. In this paper, a review of the most important procedures is given, from the extraction to the identification of anthocyanins in natural extracts.