5-Hydroxymethylfurfural (HMF) can be obtained from the dehydration of monosaccharides present in biomass, which helps add value to the raw material. The present work sought to study the relationship between the parameters of biomass characterization, including the content of reducing sugars, total soluble solids and the mid-infrared (MIR) and near-infrared (NIR) spectra, and the formation of HMF after synthesis. A thorough analysis was conducted in order to evaluate the residual agricultural biomass samples from sugarcane bagasse, corn stover, cassava branch, banana pseudostem and mango fruits after the drying (45 °C maximum) and ball mill grinding pre-processing procedure. HMF synthesis was performed using 0.50 mol L-1 HCl and n-butanol as extracting solvent. The analytical quantification of HMF and furfural (co-product of synthesis) was performed using high-performance liquid chromatography coupled to diode-array detector (HPLC-DAD). The highest efficiency of the synthesis of HMF was observed for the mango fruits (55.0 kg ton-1) and sugarcane bagasse biomass (47.5 kg ton-1) samples. The application of data fusion and principal component analysis (PCA) allowed us to identify the samples with greater potential for HMF synthesis.

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.

A potential eco-friendly method without organic solvents is presented by integrating a chromatographic fingerprint and multivariate control chart based on Q residuals to differentiate grape juices from different farming practices. The sample preparation was only water dilution, and the mobile phase was water acidified with sulfuric acid, which can be readily neutralized before its disposal. The proposed method is shown to be a simple way to distinguish between organic and non-organic grape juices in a non-target way, successfully evaluating an external validation data set, where organic and non-organic samples were correctly assigned. Through the chromatographic profile, it is possible to suggest that one of the species responsible for this distinction may be from the anthocyanins class.

This work shows an alternative methodology based on a portable near-infrared (NIR) spectroscopy coupled to independent components analysis (ICA) in a pseudo-univariate calibration way to determine total anthocyanins (TA) concentration and antioxidant activity (AA) in whole grape juice. To this, the scores proportions more related to TA and AA were plotted against TA and AA obtained by its respective references methodology to build pseudo-univariate calibration models with correlation coefficients of 0.9699 and 0.9814, respectively. From the results, it is possible the suggestion that NIR spectra coupled to ICA enable to overcome interferences using first-order data and work properly when there is enough selectivity for the analyte profile in the sample data.

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.

Tilapia (Oreochromis niloticus) is the most cultivated fish species in Brazil. Studies have shown that fish consumption is related to the prevention of cardiovascular diseases due to its high contents of polyunsaturated fatty acids, as omega-3 (n-3) and omega-6 (n-6). In this sense, a new method to determine omega-3 and omega-6 by near-infrared (NIR) spectroscopy and multivariate calibration based on partial least squares (PLS) was proposed. Spectra of fillets of Nile tilapias packed under vacuum were obtained and compared to the reference method (gas chromatography) used for quantification of fatty acids. The outliers were evaluated in the models that were validated by calculation of the parameters for model performance estimation, showing promising results. The appropriate values achieved for accuracy, limits of detection and quantification, indicate that the NIR/PLS models can be an alternative to chromatography in the determination of omega-3 and omega-6 in fillets of Nile tilapia. Furthermore, the spectra acquisition on the vacuum-packed fillet contributes to the NIR/PLS method in terms of cost and quickness.

Digital images associated with chemometric tools, in a non-destructive approach, have been applied for the evaluation of the Brazilian monovarietal extra virgin olive oil. Independent component analysis (ICA) was employed in the image data evaluation of olive oils produced from distinctive olive varieties, and it was successful in highlighting the natural grouping among the samples based on the color histograms (red, green and blue (RGB) channels). The study’s proposal indicates the ability of accurate separation of the twenty-four samples considering their color. To conclude and support the hypothesis, principal component analysis (PCA) was applied in the visible spectra of the Brazilian monovarietal extra virgin olive oil, to observe the similarities between the samples, and the results are in agreement with those obtained by image analysis coupled with ICA. This method demonstrates the possibility for the characterization of olive oils respecting the principles of Green Chemistry.

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.

Resumo O aumento do volume de resíduos agrícolas e agroindustriais gerados, acompanhados do descarte inadequado dos mesmos é um problema mundial crescente. O aproveitamento desses resíduos é de extrema importância, já que resulta na redução de impactos ambientais, preservação da saúde da população, e permite agregar valor à esses materiais. Uma das formas de aproveitamento está relacionada à capacidade de alguns resíduos serem utilizados como adsorventes alternativos na remoção eficiente de micro-contaminantes em sistemas aquosos. Este trabalho teve como objetivo investigar o uso dos resíduos agrícolas e agroindustriais: palha de milho, palha de trigo, palha de soja e casca de soja para produção de adsorventes alternativos para remoção de ferro (Fe) e manganês (Mn) em água. Para cada resíduo investigado, dois diferentes polímeros foram obtidos para uso como adsorventes, um polímero natural (celulose/lignina) e um polímero modificado com EDTA (ácido etilenodiaminotetraacético). Os adsorventes foram caracterizados por FTIR (espectroscopia de infravermelho por transformada de Fourier) e teor de nitrogênio. Para a avaliação da eficiência dos adsorventes foram realizados testes cinéticos, em regime batelada, e determinação das constantes cinéticas de pseudo-primeira e pseudo-segunda ordem de Lagergren. Os resultados obtidos indicaram que o polímero modificado obtido da casca de soja apresentou maior remoção de Fe (96%) e Mn (88%), em que o modelo cinético de pseudo-segunda ordem apresentou resultados mais aproximados entre os valores de quantidade adsorvida experimentais e os calculados para os dois micro-contaminantes em estudo. De modo geral, a casca de soja modificada mostrou ser um adsorvente alternativo promissor para a remoção de ferro e manganês no tratamento de águas.

Abstract The increase in the volume of agricultural and agroindustrial waste, associated with improper disposal, is a growing worldwide problem. The recovery of those residues is of crucial importance, since it reduces environmental impacts, protects public health, and allows the addition of value to the materials. One of the ways of exploiting adsorbents is related to the capacity of some wastes to be used as alternative adsorbents in the efficient removal of microcontaminants in aqueous systems. This work assessed the use of agricultural and agroindustrial residues: maize straw, wheat straw, soybean straw and soybean hulls for the production of alternative adsorbents to remove iron (Fe) and manganese (Mn) in water. For each residue investigated, two different polymers were obtained for use as adsorbents, a natural polymer (cellulose/lignin) and an EDTA-modified polymer (ethylenediaminetetraacetic acid). The adsorbents were characterized through FTIR (Fourier transform infrared spectroscopy) and nitrogen content. To evaluate the efficiency of the adsorbents, kinetic tests in batch mode and determination of Lagergren pseudo-first and pseudo-second order kinetic constants were performed. The results found that the modified polymer obtained from soybean hulls (SHE) showed increased Fe (96%) and Mn (88%) removal rate, in which the pseudo-second order kinetic model presented closer results between the experimental adsorption rates and the calculated ones for the two microcontaminants under study. In general, the modified soybean hulls proved to be a promising alternative adsorbent for the removal of iron and manganese in water treatment.

In this work the vitamin C was determined in industrialized nectar juices through ultraviolet (UV) spectroscopy and multiproduct multivariate calibration, based on partial least squares (PLS) regression. Since samples with different flavors, sugar content (light or not) were together in the model construction, it can be considered as a multiproduct and, due to the heterogeneity of the samples, it was necessary to optimize the calibration and validation sets by outliers elimination. The model was developed and validated by the evaluation of the figures of merit such as: accuracy, sensitivity, analytical sensitivity, adjust, linearity, relative prediction deviation, limits of detection and quantification, indicating that the multiproduct model developed from UV spectroscopy and PLS regression can be used in the industrial routine analysis as an alternative to titration or other time and reagent consuming methods. Here, it was evidenced that the UV-PLS multiproduct model provides advantages as being free of sample preparation steps, is suitable to be updated in order to measure other parameters, does not generates residues and is feasible to be implemented for on-line monitoring. Furthermore, the application of multivariate calibration in multiproduct models is extremely attractive from the industrial point of view.

Dichromate oxidation and dry combustion analysis were evaluated as reference methods to determine organic carbon in Brazilian soils using near infrared spectroscopy (NIRS) as an alternative. The main objective of this study was to evaluate which of the reference methods could provide a calibration model with higher predictive ability. A total of 161 soil samples obtained from horizons in full profiles (Parque Estadual da Mata Seca, Minas Gerais State, Brazil) were used. Models were mean centered and built from partial least squares. The dichromate oxidation method presented a lower accuracy when compared to dry combustion analysis as reference for NIRS. Figures of merit such as sensitivity, analytical sensitivity, detection and quantification limits, adjust and linearity presented results very similar. A paired t-test was applied to the figures of merit results and with 95% confidence did not show significant differences between the two methods used as reference for NIRS. The non-parametric Mann Whitney test showed that the samples provided with the partial least squares (PLS) model when the reference method was the dichromate oxidation or dry combustion analysis come from the same population, indicating that the reference methods employed for multivariate calibration from NIRS provide the same results practically.

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.

<p>Extra virgin olive oil, virgin olive oil and mixed oil were analyzed by UV-Vis spectroscopy and Multivariate Curve Resolution with Alternating Least Squares (MCR-ALS). When the oils were heated at high temperatures (frying), oxidation products were formed which were harmful to human health and antioxidants present were degraded. The aim of this study was to evaluate tocopherol (an antioxidant present in oils) and the behaviour of oxidation products in different olive oil classes. MCR-ALS results showed that degradation started at 70 ºC for extra virgin olive oil, while tocopherol concentration decreased and oxidation products increased starting at 40 ºC in virgin olive oil. In mixed oil, commercialized as a mixture of 85% soybean oil and 15% olive oil, tocopherol concentration started to decrease and oxidation products increase at 30 ºC. The results suggested that extra virgin olive oil offered more resistance to increasing temperatures, while virgin olive oil and mixed oil were less resistant.</p>

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.

In this work, three freeze-dried (FD) egg products (whole egg (WE), egg yolk (EY) and egg white (EW)) were obtained and the acceptability of confections prepared with each was evaluated. Sensory analyses for confections were performed by hedonic testing with fifty panelists in each evaluation. The studied confections were: Condensed Milk Pudding (P), Quindim (Q) and Meringue (M). The results obtained for confections made with FD egg products were compared with the achieved through other formulations of the same desserts made with fresh (F) or spray-dried (SD) egg products. The sensory analysis results for confections made with FD egg products showed good acceptance by panelists. A principal component analysis of the sensory evaluation data was carried out to identify similarities between the different egg products. The PCA supported the conclusion that FD egg products can substitute their fresh and SD counterparts in dessert formulations with good acceptability while keeping the advantages conferred by the freeze-drying method.