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Urea is an essential molecule usually detected using spectroscopy, particularly ultraviolet and visible spectroscopy (UV-vis).

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.

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 ºC 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.

The importance of nuclear magnetic resonance (NMR) spectroscopy for the food industry, including the coffee industry, has led to several studies using this analytical tool to assess coffee in different scenarios. In this context, this chapter presents an overview of 1H NMR-based metabolomics analysis used in coffee quality control. Several articles using 1H NMR associated with multivariate data analysis have been published to investigate aspects related to quality, authenticity, sensory quality, production processes, and origin of coffee. In addition, the present review reports the main chemical shifts of the constituents present in the extracts of green and roasted coffee beans. The results presented confirm the potential and versatility of 1H NMR combined with chemometric tools for coffee analysis, playing an important role in distinguishing and identifying the origins, quality, and purity of coffee. Exploratory data analysis, classification, and calibration are the most used chemometric methods in metabolomics applied in the coffee field. The results show the potential of NMR and multivariate data analysis for coffee authentication.

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.

The sensory dataset presents itself multivariate shape that can be evaluated by tools such as parallel factor analysis (PARAFAC), a powerful multivariate tool to obtain more interaction among results. By using PARAFAC, it is possible to assume that sensory analysis results present three dimensions (products x sensory attributes x panelists) with advantages over conventional statistics since it considers the sensory evaluation form of each panelist individually in the analysis. PARAFAC was employed to explore and obtain this interaction to access relevant interpretation of the sensory edible oil results (seed passion fruit oil - SPFO, extra virgin olive oil EVOO, and colza, soybean, sunflower, and corn refined oils) from home use test (HUT). The PARAFAC results show that SPFO was the most similar to the EVOO, while the refined oils were grouped. The achievement is due to sensory attributes which indicate the color as the most important in distinguishing the oils by the panelists, followed by the attributes of appearance, global impression, flavor, and aroma. Concerning panelists, the gender and age were not decisive for the distinction and preference of the edible oils investigated in the study. The PARAFAC is a powerful tool to obtain more interaction among sensory analysis results. With this multivariate tool, the sensory result for each panelist is individually considered and results for age and gender are given as a bonus.

The potential of composts produced from different origin residues to be used in environmentally friendly agriculture is addressed in this work. Seven composts obtained from different raw materials and composting methodologies are compared using elemental, thermal and spectroscopic characterization data. Despite the stabilization of the organic matter in all composts being adequate for agricultural applications, they display distinct elemental and structural compositions. Likewise, the fertilisers have very different effects on lettuce growth. Despite the observed differences, some common features were found, namely a mass loss (TGA) of 25.2 g per mol C, association between groups of elements (Fe, Al, Ni, Co, Cr, Cu and S; Mg, Na, K and P, C, Coxi, N and Pb) and correlations between the amount of carbon nanostructures and the characteristic aromaticity parameters. These results suggest that the tuning of the compost features for specific cultures may be possible for sustainable food production., This work was financially supported by the Interreg VA Spain-Portugal Programme (EU) through the project Res2ValHum (0366_RES2VALHUM_1_P). A.C. Silva acknowledges receipt of a PhD grant (UMINHO/BD/40/2016) financed by the Operational Programme Norte 2020 (through the Project “NORTE-08-5369-FSE-000033”). A. Teixeira acknowledges the grant (Res2ValHum 01/2018) to develop experimental work for 11 months on the project. J. Antelo and S. Fiol are also grateful for the financial support provided by Xunta de Galicia—Consellería de Educación e Ordenación Universitaria de Galicia (Consolidation of Competitive Groups of Investigation; GI-1245, ED431C 2018/12 and CRETUS AGRUP2015/02, ref. 2018-PG10).

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.

In this study, a polymer with characteristics analogous to that of the humic acid was obtained through oxidative polymerization in alkaline medium using para-benzoquinone as precursor, and compared to natural humic acid (HA) extracted from a soil. Complexes of as-prepared synthetic humic acid (SHA) with the Cu2+, Fe3+ and Mn2+ ions were also prepared. Elemental analysis and thermogravimetry were used for comparing the SHA characteristics with those of HA and for evaluating the effect of the metal-type for complexing with SH and SHA. Element analysis showed that SHA presented almost the same atomic constitution of HA, except for or sulfur and nitrogen contents, fact that is expected due to the precursor compounds. TGA curves of HA and SHA are quite similar in spite the thermogravimetic index (TGI) indicates higher aromatic portion in SHA. SHA-metallic ions (SHA-Cu2+, SHA-Fe3+ and SHA-Mn2+) complexes presented different thermal stability as compared among them and with the precursor SHA. The data indicate that the complexation is dependent of metallic ion-type and provokes different rearrangements in the SHA matrix.

One of the traditional residues obtained from pinhão seeds (Araucaria angustifolia (Bertol.) Kuntze) consists of an aqueous extract produced from the cooking process, which presents a significant concentration of phenolic compounds with antioxidant properties. In this work, soy protein isolate (SPI) films with different concentrations of pinhão cooking water extract (EP, 0.5, 1, and 2% wt/wt) were produced and physical properties, microstructure, and antioxidant capacity were investigated. The films were applied as packaging (as sachet-type) for linseed oil, and the oil oxidative stability was evaluated during 10 days under accelerated storage condition (60 °C) by conventional procedures (peroxide index, specific extinction coefficient, and UV-Vis spectrophotometry) and by multivariate curve resolution with alternating least squares (MCR-ALS) chemometric method. The film with EP contributed to the oxidative stability of linseed oil being an interesting alternative of active biodegradable packaging for edible oils. The authors thank the CNPq for the financial support (project no. 420055/2018-5) and scholarship. This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001 (Masters Scholarships). The authors are also grateful to the Foundation for Science and Technology (FCT, Portugal) and FEDER under Programme PT2020 for financial support to CIMO (UID/AGR/00690/2019); national funding by FCT, P.I., through the institutional scientific employment program-contract for M.I. Dias and L. Barros contracts; and to FEDER-Interreg España-Portugal program for financial support through the project 0377_Iberphenol_6_E. info:eu-repo/semantics/publishedVersion

A indústria têxtil consome muita água em seus processos e gera efluentes que podem contaminar os corpos hídricos e afetar a vida aquática. A coagulação e a floculação são técnicas utilizadas no tratamento destes efluentes, e o quiabo pode ser utilizado como auxiliar de floculação. Assim, a partir de planejamento fatorial 23 buscou-se determinar as melhores concentrações, considerando a remoção de cor e geração de lodo como parâmetros. A partir de análise multivariada verificou-se que os melhores resultados de remoção de cor e formação de lodo foram alcançados com níveis inferiores, tanto de corante, quanto de coagulante. Além disso, foi possível concluir que a concentração de quiabo não foi significativa, indicando que é indiferente manter sua concentração no nível inferior ou superior, já que ambas as concentrações contribuem da mesma forma no processo de remoção de cor e formação de lodo.

5-hydroxymethylfurfural (HMF) is considered a platform chemical used for producing industrial purpose carbon-based compounds. During HMF synthesis, the compound furfural (FF) is formed as a byproduct. Using spectrophotometric UV is not feasible because HMF and FF overlap around 280 nm, demanding separation techniques as high-performance liquid chromatography (HPLC). This work aimed at applying a synthetic route for HMF production by using wastes such as sugarcane bagasse and peanut hull, and developing a quantification method of HMF and FF compounds using UV spectra and pseudo-univariate calibration based on multivariate curve resolution with alternating least squares. HMF synthesis was studied using inorganic acids in a closed reflux system followed by a biphasic extraction with n-butanol as an organic solvent. When comparing their respective biomass, sugarcane bagasse provides a higher amount of HMF, reaching levels of 1.65 × 10−2 mol L−1 after the synthesis with HCl at 0.50 mol L−1. Regarding yield, each ton of peanut hull produces 572.6 g of HMF, while each ton of sugarcane bagasse produces 10 kg of HMF. The calibration study using pseudo-univariate calibration models was validated by using the HPLC with relative errors lower than 15%, showing that it is possible quantify HMF and FF in the medium by using UV spectrophotometer.

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.

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).

Coagulation and flocculation are two of the steps in the water treatment process in which chemical coagulants based on iron salts or aluminum are used. In order to replace the aluminum or to reduce the concentration of the metal, several natural alternatives to assist in the coagulation/flocculation process have been evaluated, including the use of Abelmoschus escuentus Moench (okra) as a flocculating agent. To determine the degradation time of the okra solution, spectral measurements were performed on the UV–Vis region. The coagulation/flocculation tests were carried out in a jar test equipment, using aluminum polychoride as a coagulant, 1-mgL−1 okra solution as a flocculation aid, and the alkalinizing hydroxide of calcium. Through the spectral measurements and the test in the jar test, it was possible to verify that the solution of the okra remains stable only until the time of 24 h, and after this time, begins the degradation process of the constituents of the okra that promote the flocculation of it. In addition, satisfactory results were obtained in the treatment of water in 24 h, allowing the use of okra as flocculation aid and aluminum polychloride coagulant, as in effluent color removal, with an efficiency of 91 to 96%, and organic matter removal, with an efficiency of 92 to 93.5%.

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.

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.

Background and Aims The current methods for measuring the anthocyanin concentration (AC) and antioxidant activity (AA) of grape juice have limitations. The objective of this work was therefore to evaluate the application of digital imaging as a simple, fast and low‐cost method for determining AC and AA in juice. Methods and Results The AC and AA of 75 grape juice samples were measured using reference methods and then correlated against digital images of 200 dpi resolution obtained with a scanner, using partial least squares regression. The samples were separated with the Kennard–Stone algorithm into calibration sets (50 samples) and external validation sets (25 samples). The models used for the quantification of AC and AA presented a root mean square error of calibration of 8.8 mg/L and 9.8 μmol and a root mean square error of prediction of 7.5 mg/L and 8.0 μmol, respectively. The correlation coefficients for the adjustment were 0.8479 and 0.9258 for the models in the determination of AC and AA, respectively. Conclusions Digital imaging and multivariate calibration can be used to measure efficiently selected parameters of grape juice composition. Significance of the Study Analytical methods based on digital imaging offer promising alternatives to conventional methods, since they are fast, simple, non‐destructive and employ little or no chemical reagents, thereby reducing analysis costs and facilitating in situ analysis.

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.

In this study, a multivariate

In this work, the quality and rheological parameters such as moisture, ash, color, falling number, gluten, and alveographic indexes (W, P/L, and I/E) were determined in wheat flour samples provided from the industrial process through digital images and multivariate calibration, based on partial least squares (PLS) regression. The models were validated by the evaluation of the figures of merit such as accuracy, the inverse of analytical sensitivity, adjust, linearity, relative prediction deviation, limits of detection, and quantification, indicating that the proposal is feasible and can be used in the industrial routine analysis as an alternative to the methods highly dependent on the analyst perception, and extremally time-consuming.

This study aimed to use chemometrics as a tool to allow for near-infrared (NIR) spectroscopy to detect adulteration in Peruvian maca powder. To adulterate the samples, pure maca powder was mixed with rice flour and rice bran, which are the most employed adulterants, using proportions of 25%, 50%, and 75% of each. After adulteration, the mixtures were submitted to NIR spectroscopy. The spectral data were used to build discriminant models through Partial Least Squares Discriminant Analysis (PLS-DA), and each model was evaluated through permutation tests to check for reliability. It was observed that all samples were discriminated against the pure ones, providing unitary sensitivities and specificities. All the models built were tested by the pairwise Wilcoxon signed-rank test, pairwise signed-rank test, and a randomization t-test, and the results indicated that the permuted and un-permuted models were not similar. The results indicated that NIR spectroscopy can be used to discriminate between pure maca powder samples and maca powder adulterated with different levels of rice flour and rice bran, achieving unitary sensitivity and specificity in the PLS-DA models.

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.