Chemometric Approach Using ComDim and PLS-DA for Discrimination and Classification of Commercial Yerba Mate (Ilex paraguariensis St. Hil.)

Comparative assessment of antibacterial activity of Matricaria chamomilla L. extract, nisin and of its combination against Alicyclobacillus spp

Alicyclobacillus spp. is a potential spoiling agent of acidic products and citrus drinks, leading to sensory alterations in contaminated products and consequent economic losses. Treatments such as pasteurization eliminate vegetative cells, but also create a favorable atmosphere for spore germination. To guarantee quality and safety, the application of natural substances as bioconservatives is a considerable and promising alternative for the food industry. This study evaluated the effect of hexane extract of Matricaria chamomilla L. (HE), Nisin (N) and their combination (HE + N). These compounds are present in some studies describing their antibacterial action, but no studies were found on the association of these compounds against the species Alicyclobacillus spp. This study aimed to analyze the antioxidant activity (AA) for the DPPH• (0,23 μmol Trolox/mg) and ABTS (27.93 μmol Trolox/mg), the Checkboard test revealed synergism between HE and N with a fractional inhibitory index (FIC) of 0.068., and to study the antibacterial and sporicidal effect. The antibacterial and sporicidal activity was satisfactory against Alicyclobacillus acidoterrestris with MIC and MBC of 1.95 μg/mL and MSC of 7.81 μg/mL in analyzes using HE + N. The application in orange juice proved to be effective, with an MBC of 0.007 μg/mL. The MIC results served as a parameter for other tests carried out in this study, such as flow cytometry and Scanning Electron Microscopy (SEM), and for the evaluation of sensory characteristics with Electronic Nose (E-nose).

Detection of the Adulteration of Dendrobium Huoshanense with Dendrobium Henanense by UV-Vis-Shortwave Near-Infrared Diffuse Reflectance Spectroscopy Combined with Chemometrics

BACKGROUND

Dendrobium huoshanense (DHS) is a classic traditional Chinese medicine (TCM) with distinctive medicinal benefits and great economic worth; nevertheless, because of similar tastes and looks, it is simple to adulterate with less expensive substitutes (such as Dendrobium henanense [DHN]).

OBJECTIVE

This work aimed to develop a reliable tool to detect and quantify the adulteration of DHS with DHN by using UV-Vis-shortwave near-infrared diffuse reflectance spectroscopy (UV-Vis-SWNIR DRS) combined with chemometrics.

METHODS

Adulterated samples prepared in varying concentrations (0-100%, w/w) were analyzed with UV-Vis-SWNIR DRS methods. Partial least-square-discriminant analysis (PLS-DA) and partial least-squares (PLS) regression techniques were used for the differentiation of adulterated DHN from pure DHS and the prediction of adulteration levels.

RESULTS

The PLS-DA classification models successfully differentiated adulterated and nonadulterated DHS with an over 100% correct classification rate. UV-Vis-SWNIR DRS data were also successfully used to predict adulteration levels with a high coefficient of determination for calibration (0.9924) and prediction (0.9906) models and low error values for calibration (3.863%) and prediction (5.067%).

CONCLUSION

UV-Vis-SWNIR DRS, as a fast and environmentally friendly tool, has great potential for both the identification and quantification of adulteration practices involving herbal medicines and foods.

HIGHLIGHTS

UV-Vis-SWNIR DRS combined with chemometrics can be applied to identify and quantify the adulteration of herbal medicines and foods.

Analytical and chemometric strategies for elucidation of yerba mate composition

Yerba mate, a popular plant consumed mainly as an infusion, possesses nutritional and medicinal properties attributed to its secondary metabolites. This study aimed to develop strategies to elucidate the phenolic composition of yerba mate samples from Brazil, Argentina, Uruguay, and Paraguay. Optimization of ultrasonic-assisted extraction (UAE) was performed, and the extracted compounds were characterized using ultra-high-pressure liquid chromatography coupled with quadrupole/time-of-flight mass spectrometry (UHPLC-QTOF-MS), molecular fluorescence and high-pressure liquid chromatography with diode-array detection (HPLC-DAD). Chemometric analysis, including parallel factor analysis (PARAFAC) and principal component analysis (PCA) explored metabolite profiles and identify patterns. PARAFAC modelling of the molecular fluorescence results revealed higher pigment content in Brazilian samples, while other countries' samples exhibited higher phenolic content. PCA modeling of HPLC-DAD results indicated that cultivated yerba mate contained higher chlorogenic acids levels, and samples from Argentina, Paraguay, and Uruguay exhibited higher concentrations of chlorogenic acids and flavonoids.

Towards Automated Classification of Zooplankton Using Combination of Laser Spectral Techniques and Advanced Chemometrics

Zooplankton identification has been the subject of many studies. They are mainly based on the analysis of photographs (computer vision). However, spectroscopic techniques can be a good alternative due to the valuable additional information that they provide. We tested the performance of several chemometric techniques (principal component analysis (PCA), non-negative matrix factorisation (NMF), and common dimensions and specific weights analysis (CCSWA of ComDim)) for the unsupervised classification of zooplankton species based on their spectra. The spectra were obtained using laser-induced breakdown spectroscopy (LIBS) and Raman spectroscopy. It was convenient to assess the discriminative power in terms of silhouette metrics (Sil). The LIBS data were substantially more useful for the task than the Raman spectra, although the best results were achieved for the combined LIBS + Raman dataset (best Sil = 0.67). Although NMF (Sil = 0.63) and ComDim (Sil = 0.39) gave interesting information in the loadings, PCA was generally enough for the discrimination based on the score graphs. The distinguishing between Calanoida and Euphausiacea crustaceans and Limacina helicina sea snails has proved possible, probably because of their different mineral compositions. Conversely, arrow worms (Parasagitta elegans) usually fell into the same class with Calanoida despite the differences in their Raman spectra.

Progress of Research on the Application of Nanoelectronic Smelling in the Field of Food

In the past 20 years, the development of an artificial olfactory system has made great progress and improvements. In recent years, as a new type of sensor, nanoelectronic smelling has been widely used in the food and drug industry because of its advantages of accurate sensitivity and good selectivity. This paper reviews the latest applications and progress of nanoelectronic smelling in animal-, plant-, and microbial-based foods. This includes an analysis of the status of nanoelectronic smelling in animal-based foods, an analysis of its harmful composition in plant-based foods, and an analysis of the microorganism quantity in microbial-based foods. We also conduct a flavor component analysis and an assessment of the advantages of nanoelectronic smelling. On this basis, the principles and structures of nanoelectronic smelling are also analyzed. Finally, the limitations and challenges of nanoelectronic smelling are summarized, and the future development of nanoelectronic smelling is proposed.

Bioactivity screening of pinhão (Araucaria Angustifolia (Bertol.) Kuntze) seed extracts: the inhibition of cholinesterases and α-amylases, and cytotoxic and anti-inflammatory activities

The objective of this work was to determine the potential bioactive properties of extracts from bio-residues of pinhão (Araucaria angustifolia (Bertol.) Kuntze) seeds, namely the α-amylase and cholinesterase inhibition, cytotoxicity, and anti-inflammatory properties. The pinhão extracts evaluated were obtained from cooking water (CW) and as an ethanolic extract from residual pinhão seed shells (PS). Catechin was the major compound found in both extracts. The PS extract presented higher antioxidant levels and the better inhibition of human salivary and porcine pancreatic α-amylases when compared to the CW extract. Also, based on in vivo evaluations, the PS extract did not differ significantly from acarbose when compared to a control group. The most potent inhibitor of cholinesterases was the CW extract. No cytotoxicity toward normal cells was detected, and neither extract showed anti-inflammatory activity. The PS extract presented cytotoxic activity toward non-small-cell lung, cervical, hepatocellular and breast carcinoma cell lines. Overall, the results demonstrated the potential bioactivity of extracts obtained from pinhão bio-residues.

Ecometabolic mixture design-fingerprints from exploratory multi-block data analysis in Coffea arabica beans from climate changes: Elevated carbon dioxide and reduced soil water availability

Ecometabolic mixture design-fingerprinting in coffee cultivated under climate change was chemically explored using ComDim. Multi-blocks were formed using UV, NIRS, ¹H NMR, SWV, and FT-IR data. ComDim investigated all these different fingerprints according to the extractor solvent and in virtue of atmospheric CO₂ increase. Ethanol and ethanol-dichloromethane showed the best separations due to CO₂ environment. ¹H NMR loading indicate increases of fatty acids, caffeine, trigonelline, and glucose in beans under current CO₂ levels, whereas quinic acid/chlorogenic acids, malic acid, and kahweol/cafestol increased in beans under elevated CO₂ conditions. SWV indicated quercetin and chlorogenic acid as important compounds in coffee beans cultivated under current and elevated CO₂, respectively. Based on the ethanol and ethanol-dichloromethane fingerprints, k-NN correctly classified the beans cultivated under different carbon dioxide environments and water availabilities, confirming the existence of metabolic changes due to climate changes. SWV proved to be promising compared with widely used spectrometric methods.

Feasibility of Using VIS/NIR Spectroscopy and Multivariate Analysis for Pesticide Residue Detection in Tomatoes

The purpose of this work was to investigate the detection of the pesticide residual (profenofos) in tomatoes by using visible/near-infrared spectroscopy. Therefore, the experiments were performed on 180 tomato samples with different percentages of profenofos pesticide (higher and lower values than the maximum residual limit (MRL)) as compared to the control (no pesticide). VIS/near infrared (NIR) spectral data from pesticide solution and non-pesticide tomato samples (used as control treatment) impregnated with different concentrations of pesticide in the range of 400 to 1050 nm were recorded by a spectrometer. For classification of tomatoes with pesticide content at lower and higher levels of MRL as healthy and unhealthy samples, we used different spectral pre-processing methods with partial least squares discriminant analysis (PLS-DA) models. The Smoothing Moving Average pre-processing method with the standard error of cross validation (SECV) = 4.2767 was selected as the best model for this study. In addition, in the calibration and prediction sets, the percentages of total correctly classified samples were 90 and 91.66%, respectively. Therefore, it can be concluded that reflective spectroscopy (VIS/NIR) can be used as a non-destructive, low-cost, and rapid technique to control the health of tomatoes impregnated with profenofos pesticide.