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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 this study, a multivariate 23 experimental design was applied to optimize the operational conditions (seed mass, salt concentration, and pH) to employ Ceratonia siliqua L. (carob) and Moringa oleifera Lam (moringa) as coagulating/flocculating agents for water treatment. Currently, the coagulation stage in water treatment uses aluminium compounds, due to the characteristic reaction to natural alkalinity in raw water, and for its low market value. Considering that aluminium effects on human health are not sufficiently studied to acknowledge its toxicity, and its significant environmental impacts, it is suitable for the studies to search for alternatives to be employed in the water treatment that will be distributed to human consumption. This study was carried out with raw water of high turbidity level, 83.7 NTU. The raw water collected was also characterized according to pH, colour, Total Organic Carbon (TOC), Dissolved Organic Carbon (DOC), and Dissolved Organic Matter (DOM), with values of 6.7, 178 NTU, 6.80, 2.45 and 138.58 mg/L, respectively. The optimized results showed that with 2 g of seed, 0.5 mol L-1 of NaCl, and pH 11.0 In these conditions, moringa coagulant reached 90%, 86%, 6%, 67%, and 81% for turbidity, colour, DOC, TOC, and DOM removal, respectively, whereas the carob coagulant achieved 85%, 76%, 5%, 55.6%, 66.7%, respectively for the same parameters' removal. Both coagulants presented lower sludge formation, 1.1 mL L-1 for moringa coagulant, and 1.1 mL L-1 for carob coagulant. The results could be considered promises, and natural polymers carob and moringa can be suggested as alternatives agents in coagulation/flocculation stages for water treatment.

This study aimed to evaluate the effect of the drying process on Peruvian maca flours. The analysis was done using a non-targeted metabolite profiling approach through principal components analysis (PCA) to evaluate the different ions detected by an ultra-high performance liquid chromatography coupled to a hybrid quadrupole time-of-flight high-resolution mass spectrometer. In this case, only the positive ions were considered. The spectra were acquired after methanolic extraction, and the data was organized in a matrix form. PCA allowed to find out the main substances responsible for differentiating between the drying processes, showing that oven drying mainly influences the amount of amino acids and glucosinolates. It was also possible to note that some macamides were still detectable after oven drying, and the main alkaloids also remained after heating. Therefore, this study offers a feasible method for metabolomics for food authentication.

Currently, many newborns are consuming human milk (HM) donated by nursing mothers, especially those in the neonatal intensive care unit. However, a frequent problem in HM banks is the lack of information about the lactation phase of donated milk (colostrum, transition, or maturity), which makes it more difficult to supply children according to their particular needs. This research aims to develop models based on handheld near-infrared spectroscopy (NIR) coupled with partial least squares with discriminant analysis (PLS-DA) to individually classify HM in its different phases (colostrum—class 1; transition—class 2; mature—class 3). A total of 198 samples were pasteurized before spectra collection. Subsequently, several preprocessing techniques were investigated in NIR spectra using principal component analysis: multiplicative scatter correction (MSC), derivatives, and combinations between them. The NIR spectra preprocessed through MSC were employed in PLS-DA models, where sensitivity and specificity obtained were considered satisfactory for classifying mainly colostrum (87.5% and 90.3%, respectively) and mature (93.8% and 93.8%, respectively) phases. VIP scores showed that for the modeling of the colostrum phase the important regions are related to protein, while for the mature phase the lipids are more important. This plot also confirmed that the transition phase shares properties of the colostrum and mature phases, which probably contributed to its poor classification (rates ranging from 56.3 to 71.9%). Therefore, handheld NIR coupled with PLS-DA is suitable for the classification of HM in different phases of lactation in a low-cost and quick analysis. The proposal can be used in regulated banks to classify samples with unknown lactation phase before supplying them to newborns and can help to provide the ideal HM phase for their needs.

The present study evaluated the potential of near-infrared (NIR) spectroscopy coupled with partial least squares with discriminant analysis (PLS-DA) for the authentication of organic sugars. Portable NIR equipment was employed in the range from 900 to 1650 nm. Three PLS-DA models were built: the first one for discriminating organic sugar from conventional crystal sugar, a second model for discriminating organic sugar from conventional demerara sugar, and the third one for discrimination of organic sugar from conventional brown sugar. The sensitivity and specificity for the PLS-DA models were equal to 1 in all cases, indicating high ability in the authentication of sugars (crystal, demerara, and brown) as organic and conventional ones. The ability of NIR spectroscopy for organic sugar authentication can be assigned to a shift in the absorption bands in the regions of the first, second and third overtones, probably due to the differences in the amount of compounds that present these bonds in the organic and conventional sugars. Thus, it can be suggested that the organic sugar samples had differences in chemical composition which are detected by NIR spectroscopy coupled to the chemometric method PLS-DA, allowing the differentiation of organic samples from conventional ones.

Para que os óleos atinjam qualidade sensorial desejada, eles passam por etapas de refino. A clarificação é uma dessas etapas, em que são usadas argilas clarificantes as quais aderem pigmentos indesejados naturais do óleo, tornando-o visualmente mais atraente para os consumidores. O problema está no descarte incorreto destinado a essas argilas, que são dispostas em aterros sanitários causando danos ao meio ambiente. Da mesma forma, óleos residuais de fritura trazem problemas quando descartados em pias e ralos, comprometendo os lençóis freáticos. Assim, uma solução para esse inconveniente seria a produção de biodiesel, já que este é produzido mediante óleos e gorduras, mesmo em estado de deterioração desde que atingidos os padrões físico-químicos de qualidade. Os objetivos do trabalho foram ativar termicamente a argila residual, purificar o óleo residual nessa argila recuperada e produzir via transesterificação ácida o biodiesel do óleo residual e do óleo purificado. Todas as análises físico-químicas foram realizadas de acordo com metodologias oficiais, e os espectros obtidos por meio do infravermelho próximo (NIR) foram tratados mediante Análise dos Componentes Principais (PCA). Foram realizadas análises físico-químicas após a ativação térmica da argila, obtendo-se resultados de umidade de 1,07%, acidez de 0,16 g ácido oleico.100g-1 e peróxidos 19,01 meq.kg-1. Para os insolúveis em éter não foram obtidos valores significativos, além de, por meio da técnica de NIR, ficar nítida a diferença existente entre a argila residual recuperada e a argila virgem. De posse dos resultados, os valores de acidez no óleo purificado e no óleo residual se mantiveram dentro dos padrões estipulados pela Agência Nacional de Vigilância Sanitária (Anvisa), porém o índice de peróxidos ficou acima dos valores recomendados, evidenciando que o óleo se encontrava em processo de deterioração. Conclui-se que ativar termicamente a argila proveniente do processo industrial com o óleo residual é uma boa alternativa para a sua reutilização, pois contribui para que esse material não seja perdido e possivelmente descartado de forma incorreta, e, ainda, traz vantagens com relação à produção de biocombustível por meio de transesterificação ácida.

Analytical methods based on digital images coupled to chemometric tools are promising alternatives for developing analytical methodologies in determining quality parameters in foods. The total phenolics, monomeric anthocyanins, and tannin content were quantified based on digital images and pseudo-univariate calibration performed from Independent Components Analysis (ICA). Differences between ICA, Principal Component Analysis (PCA), and Multivariate Curve Resolution with Alternating Least Squares (MCR-ALS), highlighting the chosen ICA for this proposal, were explained. In all pseudo-univariate calibration curves, correlation coefficients higher than 0.9 were achieved. The results suggest that digital images coupled with ICA can give applicable pseudo-univariate calibration models to determine bioactive compounds. Even more, the device to obtain an image is cheaper than most analytical instruments. Digital images may have a promising future in developing analytical methodologies for complex samples such as foods from a pseudo-univariate calibration perspective (where a small data set is needed in the calibration step).

In this study, a multivariate

This work aimed to propose a methodology to be used as a fast screening method to detect adulteration in oil capsules using Near Infrared (NIR) spectroscopy through Principal Components Analysis (PCA). The experiment consisted in measuring the NIR spectra from 25 different intact oil capsules from different oil/mixtures and, to provide a trustworthy comparison, the oil capsule internal content was extracted to be evaluated by High-Resolution Gas Chromatography (HRGC). In order to be useful, the proposed methodology demands for a known certified set of samples to be used as a target. The ability to detect adulteration was verified comparing between NIR and GC PCA scores disposal, in which 6 samples did not match. Therefore, the methodology suggests that these 6 samples would be evaluated by HRGC in place of the whole set of 25 samples. Thus, NIR spectroscopy could be used as a fast screening method to indicate which samples should be analyzed by gas chromatography, considering that each coinciding sample, i.e. disposed of in agreement to the HRGC PCA score, is already certified by HRGC regarding on their content.

The olive oil consumption has spread worldwide, increasing the necessity of quality assessment, and so forth, the search for new, alternative, and rapid data interpretation has started, boosting the interest and the use of data fusion that seek for an integration of results from different techniques or methodologies for the same data set. To better understand the storage effects on the Brazilian monovarietal extra virgin olive oil, data fusion was applied in the classical and alternative analysis, highlighting the similarities and differences between the techniques, assisting in the result interpretation. This perspective and strategy bring development to food chemistry analysis.

This research presents the use of near-infrared (NIR) spectroscopy as a fast alternative of conventional methods, suitable for in-line use for quality control in the industrial coffee processing. Chemometric models were constructed from spectra of 217 coffees sampled during the period of 5 months of coffee processing, which demonstrates the viability of the NIR spectroscopy in terms of prediction, since it provides realistic variability in chemometric models. In this work, granulometry, moisture content, color, and the infusion time of commercially roasted coffee beans were evaluated by reference methods, NIR spectroscopy, and partial least squares (PLS). Four models were built using 217 roasted coffee samples, differentiated by type of beverage and roast degree. After the model’s optimization by the outlier evaluation, parameters of merit such as residual prediction deviation, sensitivity, analytical sensitivity, the inverse of analytical sensitivity, limits of detection and quantification, adjust, and linearity were calculated. The models showed predictive capacity and high sensitivity in determining the analyzed ones. All these quality control parameters were predicted with adequate correlation coefficient, which ranged from 0.73 to 0.84 and presented satisfactory performance. The parameters of merit presented promising results, indicating that the prediction models developed for granulometry, color, moisture content, and infusion time can be safely used in the coffee industry as an alternative to reference methods. Moreover, the proposed methodology is sample preparation free, fast, simple, efficient, and suitable for in-line uses.

Thermal rice oil degradation was evaluated by UV–Vis and NIR in three-way arrays assembled with samples, different temperatures, and the absorbance at different wavelengths by applying PARAFAC chemometric method. The loadings matrix of the mode corresponding to the samples (scores) contains the information related to the samples. The loadings on the temperature mode resemble kinetics profiles. These profiles change with the nature of the component responsible for the factor and evolve with the heating temperature. The loadings on the spectral mode reveal the antioxidants γ-oryzanol and tocopherol, and oxidation products are the components responsible for the two factors. The results achieved showed that the antioxidants concentration decreases starting at 70 °C while oxidation products start to increase more pronounced after 90 °C. The proposed method is shown to be a simple and fast way to obtain information about the oxidative stability of rice oils.

Extra-virgin olive oil (EVOO) from Mediterranean were analyzed by Ultraviolet-Visible (UV-Vis) spectroscopy and Independent Component Analysis (ICA). The use of ICA resolution provided information over dienes (primary oxidation compound), polyphenolic compounds, tocopherol, carotenoids and chlorophylls when EVOO was evaluated by UV-Vis spectroscopy. Based on these data, ICA could be used to determine the contribution of chemical compounds to the composition of EVOO produced in different regions from Mediterranean. The results suggest that the combination of UV-Vis measurements and ICA makes possible the EVOO evaluation, and can contribute to suggesting that a foodstuff comes from an alleged origin. The proposed methodology is a low cost, fast and sample preparation free methodology to highlights the EVOO characteristics produced in the Mediterranean region.

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.

Organic food consumption has increased significantly over time. This contributes to the increased demand and price of this kind of food. Among the organic products, cinnamon stands out for its characteristic flavor and bioactive compounds. Thus, the work aimed to verify the potentials of attenuated total reflectance Fourier transform mid-infrared spectroscopy (ATR-FT-MIR) coupled with Parallel Factor Analysis (PARAFAC) for evaluation of cinnamon organic samples. As result, the proposal is feasible in the differentiation of organic cinnamon powder, in which ATR-FT-MIR coupled with PARAFAC showed the differentiation of organic from non-organic ones on the scores mode, the precision at repeatability level on one loading mode, and the spectral region, on the other loading mode, above 2600 cm−1 was related to the differentiation of the organic and non-organic samples.

Meliponine is a honey with particular characteristics; it has a high percentage of humidity, which can favor the development of microorganisms, thereby causing changes in the quality of the product. The objective of this study was to evaluate the microbiological characteristics of meliponine honey produced by different species and marketed in the State of Paraná-Brazil. The sample unit was composed of honey of Tetragonisca angustula (n = 15), Scaptotrigona bipunctata (n = 05), Melipona quadrifasciata quadrifasciata (n = 05) and Melipona bicolor schencki (n = 01). The following microbiological parameters were evaluated: counts of total and thermotolerant coliforms, fungi count and detection of Salmonella spp. Principal component analysis (PCA) was used to evaluate the possible relationships among species, locality and type of microorganism. For microorganisms of the total coliform group, 15.38% of the analyzed samples had values >3 MPN/g. The presence of thermotolerant coliforms was observed in 7.69% of the samples, all of which were T. angustula samples. For fungi counts, 100.00% of the analyzed samples had values within the established range created by the Agricultural Defense Agency of Paraná. The presence of Salmonella spp. was not observed in any of the samples evaluated. The amount of water in the honey is related to the location of the apiary and edaphoclimatic factors. Adoption of good handling practices by beekeepers is indispensable for the safety of the final product. La meliponíne produce una miel diferenciada con características particulares, presenta un alto porcentaje de humedad, lo que puede favorecer el desarrollo de microorganismos provocando cambios en la calidad del producto. El objetivo de este estudio fue evaluar las características microbiológicas de la miel de meliponíne producida por diferentes especies y comercializada en el Estado de Paraná-Brazil. La unidad de muestra estuvo compuesta por miel de Tetragonisca angustula (n = 15), Scaptotrigona bipunctata (n = 05), Melipona quadrifasciata quadrifasciata (n = 05) y Melipona bicolor schencki (n = 01). Se evaluaron parámetros microbiológicos: recuento de coliformes totales y termotolerantes, recuento de hongos y detección de Salmonella spp. Análisis de componentes principales: se utilizó ACP para evaluar las posibles relaciones entre especies, localidad y tipo de microorganismo. Para los microorganismos del grupo de coliformes totales, el 15,38% de las muestras analizadas presentaron valores >3 NMP/g. En el 7.69% de las muestras se observó la presencia de coliformes termotolerantes, siendo todas muestras de T. angustula. Para contar hongos, el 100,00% de las muestras analizadas presentaron valores dentro de lo establecido por la Agencia de Defensa Agropecuaria de Paraná. No se observó presencia de Salmonella spp en ninguna de las muestras evaluadas. Algunas muestras fueron similares según la especie productora y la cantidad de agua en la miel está relacionada con la ubicación del meliponario, debido a factores edafoclimáticos. La adopción de buenas prácticas de manipulación por parte de los productores de miel es fundamental para garantizar la seguridad alimentaria del producto final. Os meliponíneos elaboram um mel diferenciado com características particulares, apresenta elevado percentual de umidade o que pode favorecer o desenvolvimento de microrganismo ocasionando alterações na qualidade do produto. O objetivo deste estudo foi avaliar as características microbiológicas do mel de meliponíneos produzido por diferentes espécies e comercializado no Estado do Paraná-Brasil. A unidade amostral foi composta de mel de Tetragonisca angustula (n=15), Scaptotrigona bipunctata (n=05), Melipona quadrifasciata quadrifasciata (n=05) e Melipona bicolor schencki (n=01). Parâmetros microbiológicos foram avaliados: contagem de coliformes totais e termotolerantes, contagem de fungos e detecção de Salmonella spp. A análise de componentes principais - ACP foi utilizada para avaliar as possíveis relações entre espécie, localidade e tipo de microrganismo. Para microrganismos do grupo coliformes totais, 15,38% das amostras analisadas apresentaram valores >3 NMP/g. Em 7,69% das amostras foi observado a presença de coliformes termotolerantes, sendo todas amostras de T. angustula. Para contagem de fungos, 100,00% das amostras analisadas apresentaram valores dentro do estabelecido pela Agência de Defesa Agropecuária do Paraná. Não foi observado a presença de Salmonella spp em nenhuma das amostras avaliadas. Algumas amostras se assemelharam segundo a espécie produtora e a quantidade de água no mel é relacionada com a localização do meliponário, devido a fatores edafoclimáticos. Adoção de boas práticas de manipulação pelos meliponicultores se tornam indispensáveis para conferir segurança alimentar ao produto final.

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.

Coffee quality is determined by several factors and, in the chemometric domain, the multi-block data analysis methods are valuable to study multiple information describing the same samples. In this industrial study, the Common Dimension (ComDim) multi-block method was applied to evaluate metabolite fingerprints, near-infrared spectra, sensory properties, and quality parameters of coffee blends of different cup and roasting profiles and to search relationships between these multiple data blocks. Data fusion-based Principal Component Analysis was not effective in exploiting multiple data blocks like ComDim. However, when a multi-block was applied to explore the data sets, it was possible to demonstrate relationships between the methods and techniques investigated and the importance of each block or criterion involved in the industrial quality control of coffee. Coffee blends were distinguished based on their qualities and metabolite composition. Blends with high cup quality and lower roasting degrees were generally differentiated from those with opposite characteristics.

The use of chemometric tools is progressing to scientific areas where analytical chemistry is present, such as food science. In analytical food evaluation, oils represent an important field, allowing the exploration of the antioxidant effects of herbs and seeds. However, traditional methodologies have some drawbacks which must be overcome, such as being time-consuming, requiring sample preparation, the use of solvents/reagents, and the generation of toxic waste. The objective of this study is to evaluate the protective effect provided by plant-based substances (directly, or as extracts), including pumpkin seeds, poppy seeds, dehydrated goji berry, and Proven&ccedil, al herbs, against the oxidation of antioxidant-free soybean oil. Synthetic antioxidants tert-butylhydroquinone and butylated hydroxytoluene were also considered. The evaluation was made through thermal degradation of soybean oil at different temperatures, and near-infrared spectroscopy was employed in an n-way mode, coupled with Parallel Factor Analysis (PARAFAC) to extract nontrivial information. The results for PARAFAC indicated that factor 1 shows oxidation product information, while factor 2 presents results regarding the antioxidant effect. The plant-based extract was more effective in improving the frying stability of soybean oil. It was also possible to observe that while the oxidation product concentration increased, the antioxidant concentration decreased as the temperature increased. The proposed method is shown to be a simple and fast way to obtain information on the protective effects of antioxidant additives in edible oils, and has an encouraging potential for use in other applications.

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.

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.

Gluten-free biscuits were developed with the addition of chia seeds (Salvia hispanica L.) and turmeric powder. An experimental design 2(2) were employed in the formulation optimization that promotes better sensory acceptance through acceptance test with a hedonic scale of 9 points. For characterization purposes, the centesimal composition from chia seeds and the turmeric powder were determined. The biscuits were produced from an optimized formulation with and without chia seeds and turmeric powder with microbiological results safe for consumption by evaluation Salmonella sp., positive coagulase Staphylococcus, and Coliforms to 45 °C. The Principal Components Analysis (PCA) was used in the investigation of sensory results (color, flavor, texture, smell, appearance, overall impression). It was also considered the habits of consuming food with/without gluten, purchase intentions, including age and gender. The results show that there is no distinction between the biscuits with the addition of chia seeds and turmeric powder. A statistical test using the confidence ellipse confirms that there no significant difference, at a 95% confidence level, among the sensory results for the biscuits with and without chia seeds and turmeric powder.

This chapter presents the correlation between coffee compounds identified by 1H Nuclear Magnetic Resonance (1H NMR) spectroscopy with psychological attention tests in order to verify which compounds are related to the focus and/or diffuse attention. Psychometric tests applied by a clinical psychologist, before and after coffee intake, were the focus attention AC-vector and the diffuse attention TADIM, and the focus attention TACOM-B and the diffuse attention TEDIF, respectively. Different tests to measure the attention before and after coffee intake were used to avoid learning effects. After AC-vector and TADIM tests, each volunteer consumed a total of 40 mL of coffee with different cup qualities (four different coffee blends – 10 mL per beverage) and indicated the order of preference in relation to the smell. This approach was used to create a greater metabolic variation between the samples tested, allowing to build a robust chemometric model. For each preferred coffee, a 1H NMR spectrum was obtained and a chemometric data treatment based on Partial Least Squares (PLS) regression and Variable Importance in Projection scores (VIP scores) was used to correlate the spectra with the psychological test results and to verify which metabolites of the coffee beverage could be related to the focus or diffuse attention. In general, our results showed that coffee intake attenuated diffuse attention and improved focus attention in most volunteers. The major metabolites that contributed to both diffuse and focus attention were caffeine, trigonelline, chlorogenic acids, acetate, lipids, lactate, γ-quinide, and polysaccharides. Among metabolites exclusively important to focus attention, formate, choline, myo-inositol, citrate, and malate were the most important. Therefore, the 1H NMR profile, in combination with chemometric tools, is interesting to assess the correlation between coffee compounds and human attention.

This article contains data related to the research article entitled “Quantitative assessment of specific defects in roasted ground coffee via infrared-photoacoustic spectroscopy” (Dias et al., 2018) [1] . A method potentially able for assessing the quality of roasted ground coffees is described in the origin paper. Infrared spectroscopy and photoacoustic detection (FTIR-PAS) associated with multivariate calibration were used. The samples were obtained blending whole and healthy coffee beans (C. arabica and C. canephora) with specific blends of defects, named selections, which contain broken, sour, and black beans, skin, woods and healthy beans still not collected. In addition to a reduction in commercial value, the presence of defects compromises the sensory attributes of coffee. On the other hand, selections are commonly found in coffee crops and can be added intentionally to the product. Twenty-five selections were used to obtain a panel of 154 blends. The FTIR-PAS spectra of each sample generated the prediction model of Partial Least Squares Regression parameters, which are also presented here.

Samples of chia seeds (Salvia hispanica L.) were degreased by cold pressing and the residue obtained named degreased chia seeds (DCS) had the antioxidants extract obtained. A 22 experimental design was employed in order to evaluate the factors ethanol concentration and extraction time. The optimized conditions were extraction time 15 min with ethanol 70% where the activity (RSA), evaluated by the DPPH (2,2-diphenyl-1-picryl-hydrazyl) method was 94.76%. For this extract, the total phenolics content was 359.64 mg EGA/100 g. A pseudo-univariate calibration model is proposed as an alternative methodology to determine the %RSA by using the relative concentration from multivariate curve resolution with alternating least squares (MCR-ALS) from near-infrared (NIR) spectra of the antioxidant extract from DCS. The results suggest the possibility of %RSA determination directly from NIR spectra from extracts from DCS by using the multivariate resolution method MCR-ALS.

Chemical analyses and sensory evaluation are the most applied methods for quality control of roasted and ground coffee (RG). However, faster alternatives would be highly valuable. Here, we applied infrared-photoacoustic spectroscopy (FTIR-PAS) on RG powder. Mixtures of specific defective beans were blended with healthy (defect-free) Coffea arabica and Coffea canephora bases in specific ratios, forming different classes of blends. Principal Component Analysis allowed predicting the amount/fraction and nature of the defects in blends while partial Least Squares Discriminant Analysis revealed similarities between blends (=samples). A successful predictive model was obtained using six classes of blends. The model could classify 100% of the samples into four classes. The specificities were higher than 0.9. Application of FTIR-PAS on RG coffee to characterize and classify blends has shown to be an accurate, easy, quick and “green” alternative to current methods.

This work aims to relate near-infrared (NIR) vibration bands to physicochemical (PC) parameters in order to discriminate honey samples. To the study, 14 Jatai weyrauchi honey samples from Roraima State (northern Brazil) and 15 Jatai angustula honey samples from Parana State (southern Brazil) were evaluated by analyzing physicochemical parameters (moisture, pH, acidity, formaldehyde index, ashes, electric conductivity, color, hydroxymethylfurfural, protein, reducing sugars, total reducing sugars and sucrose, viscosity, and water activity), besides being submitted to spectral measurements in the near-infrared range from 900 to 1700 nm. By applying ComDim multiblock analysis, it was possible to simultaneously evaluate the results from NIR spectroscopy and the evaluated PC parameters. This tool allowed to highlight the relation between NIR spectra and PC parameters by producing informative graphs showing the relationship among the samples through the scores, the saliences of the blocks, and the loadings of the variables responsible for the similarities observed in the samples scores. Based on the principal component analysis, it was possible to conclude that the PC parameters can be replaced by NIR spectroscopy in the discrimination of honey samples, improving its evaluation regarding on the speed and decreasing the amount of reagents used for this purpose.

The extra virgin olive oil (EVOO) has a certain oxidation resistance when compared to other vegetable oils without refining process, due to their large composition of monounsaturated fatty acids, antioxidants, and bio-compounds. The main of this research was to evaluate and monitor the behavior of autoxidative processes through the storage time in two packaging systems of different EVOO monovarietals produced in Minas Gerais, Brazil by using ultraviolet and visible spectroscopy (UV–Vis) with multivariate curve resolution with alternating least squares (MCR–ALS). We analyzed six EVOOs produced from different monovarietals (Arbequina, Empeltre, Coratina, Grappolo, Koroneiki, and Maria da Fe), over the course of 1 year, performed the analysis in times 0, 30, 90, 180, and 365 days, and storage in glass bottles and tinplate cans. The UV–Vis spectroscopy coupled with MCR–ALS was a feasible tool to monitor autoxidation processes in EVOO through storage time and in the monitoring of the EVOO quality in different package systems. The glass bottles were a package system that provides more protection for the autoxidation processes with the time for the EVOO from monovarietals Empeltre, Arbequina, and Coratina. In addition, it was possible to make a differentiation between the monovarietal olive oils produced in Brazil by observing the amount of phenolic compounds present in the chemical composition of each oil. Allowing gather information about the formation of oxidative products may correlate with the shelf life of the EVOO.

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 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.

Vitamin C and total acidity were determined in industrialized fruit nectar and soy juices through visible-near infrared (Vis-NIR) spectroscopy and multiproduct, multicomponent, and multivariate calibration, based on partial least squares (PLS2) regression. Since samples with different types, flavors, and sugar content (light or not) were together in the model construction, the samples present higher heterogeneity and it was necessary to optimize the calibration and validation sets by outlier elimination based on leverage and unmodelled residuals in spectral data. The model was developed and validated by the evaluation of the parameters of merit such as accuracy, analytical sensitivity, adjust, linearity, residual prediction deviation, limits of detection, and quantification. The results achieved indicates that the multiproduct, multicomponent, and multivariate calibration model developed from Vis-NIR spectroscopy and PLS2 regression can be used in the industrial routine analysis as an alternative to titration reference methods that are time- and reagent-consuming methods, making the methodology extremely attractive from the industrial point of view.