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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).

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.

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.

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.

Kurtosis-based projection pursuit analysis (kPPA) has demonstrated the ability to visualize multivariate data in a way that complements other exploratory data analysis tools, such as principal components analysis (PCA). It is especially useful for partitioning binary data sets (2k classes) with a balanced design. Since kPPA is not a variance-based method, it can often provide unsupervised class separation where other methods fail. However, when multiple classifications are possible (e.g. by gender, age, disease state, etc.), the projection provided by kPPA (corresponding to the global minimum kurtosis) will not necessarily be the one of greatest interest to the researcher. Fortunately, the optimization algorithm for kPPA allows for interrogation of projections obtained from numerous local minima. This strategy provides the basis of a new method described here, referred to as combinatorial projection pursuit analysis (CombPPA) because it presents alternative combinations of class separation. The method is truly exploratory in that it allows the landscape of interesting projections to be more fully probed. The approach uses Procrustes rotation to map local minima among the kPPA solutions, whereupon the researcher can visualize different projections. To demonstrate the new method, the clustering of grape juice samples using visible spectroscopy is presented as a model problem. This problem is well-suited to this type of study because there are eight classes of samples symmetrically partitioned into two classes by type (organic/non-organic) or four classes by brand. Results presented show the different combinations of projections that can be obtained, including the desired partitions. In addition, this work describes new enhancements to the kPPA algorithm that improve the orthogonality of solutions obtained.

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.

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.

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.

Partially hydrogenated soybean oil and palm olein are oils that are widely used in the food industry. Continuous contact with air may cause changes of the triglycerides chemical structure, to eventually produce substances of lower molar masses that may be toxic to mammals. This study aimed to determine the kinetic parameters for the thermal oxidation of these oils and of their residual used oils from the pre-frying industrial step on preparing breaded chicken meat. The main reactions were followed by thermogravimetry (TG) and differential scanning calorimetry (DSC); the formation of the produced substances was monitored by gas chromatography flame ionization detector (GC-FID) and Fourier transform infrared spectroscopy (FTIR). These analyses indicated different chemical pathways, according to the type of unsaturation and changes in the molecular structures of the fatty acids in the oils. From the thermal analysis, more than one decomposition event was observed during the thermal oxidation process. As the soybean oil has a lower oxidation onset temperature than palm olein, it has lower rate of mass loss, with a higher activation energy value.

A fritura é um dos processos mais populares para finalidade de preparação de alimentos dado que promove rapidez e agilidade na cocção, além de permitir um ganho significativo referente as propriedades sensoriais, como sabor, aparência, textura e odor. As reações que ocorrem nos óleos e gorduras vegetais, induzidas pela presença de oxigênio, e especialmente acelerado por aquecimento, têm um impacto sobre a qualidade nutricional dos óleos com implicação para a saúde humana, com isso, a preocupação com a verificação da qualidade dos alimentos que são submetidos a este processo tem se intensificado. Nesse sentido, os objetivos deste estudo foram avaliar a qualidade e estabilidade oxidativa de óleo de soja e gordura de soja parcialmente hidrogenadas através da espectroscopia na região do ultravioleta e visível (UV-Vis) e da ferramenta quimiométrica de resolução multivariada de curvas com mínimos quadrados alternantes (MCR-ALS), além disso, a composição em ácidos graxos trans foi determinada por cromatografia gasosa. Os resultados obtidos sugerem que a gordura de soja apresenta maior resistência quando submetidos a ciclos de fritura do que o óleo de soja, porém a gordura de soja parcialmente hidrolisada também apresenta quantidade significativamente maior de ácidos graxos trans.