Analysis of Phenolic Content in Grape Seeds and Skins by Means of a Bio-Electronic Tongue

Authentication and identification of Lamiaceae family with cyclic voltammetry fingerprint-PCA-LDA and determination of the used phenolic contents for classification using chromatographic analyses

Todays, it is essential to evaluate and check the quality of herbal medicines in to protect the public health. As medicinal plants, the extracts of labiate herbs are used directly or indirectly to treat a variety of diseases. Increase in their consumption has led to the fraud in herbal medicines. Hence, modern accurate diagnostic methods must be introduced to differentiate and authenticate these samples. Electrochemical fingerprints have not been evaluated for their capacity to distinguish and classify various genera within a family. Since it is essential to classify, identify, and distinguish between these closely related plants in order to guarantee the quality of the raw materials, the authenticity and quality of 48 dried and fresh Lamiaceae samples, which include Mint, Thyme, Oregano, Satureja, Basil, and Lavender with various geographic origins, were examined. The present study focused on (a) classification and authentication Labiate herbs extracts and (b) identification of active compounds in samples by Gas chromatography and HPLC methods. This was accomplished using principal component analysis (PCA) and PCA-linear discriminate analysis (PCA-LDA). The results of the clustering revealed that PCA-LDA categorized mint species more accurately than PCA. In addition to certain flavonoids including ferulic acid, apigenin, luteolin, and quercetin, HPLC and GC analysis of the ethanolic extract revealed the presence of phenolic acids such as rosmarenic acid, methyl rosmarenate, caffeic acid, cinnamic acid, and chlorogenic acid. Comparing results of PCA-LDA with chromatographic analysis show that the authentication and detection of fraud samples were correctly performed using chemometyrics technique based on CV fingerprints. Even, there was no need to completely identify components of the mint samples.

Comparison of Identification and Quantification of Polyphenolic Compounds in Skins and Seeds of Four Grape Varieties

The aim of this study was to identify and quantify polyphenolic compounds in skin extracts from four Bulgarian grape varieties and compare them to those of seed extracts. The values of total phenolic contents, flavonoids, anthocyanins, procyanidins and an ascorbic acid in grape skin extracts were determined. The antioxidant capacities of skin extracts were evaluated using four different methods. The total phenolic content of skin extracts was 2-3 times lower than those of seed extracts. The significant difference between total parameter values of individual grape varieties were also found. According to the total phenolic content and antioxidant capacity of skin extracts, the different grape varieties were arranged in the following order: Marselan ≥ Pinot Noir ˃ Cabernet Sauvignon ˃ Tamyanka. The individual compounds in the grape skin extracts were determined using RP-HPLC and compared with those of the seed extracts. The determined composition of skin extracts was significantly different from the seed extracts' composition. Quantitative evaluation of the procyanidins and catechins in the skins was carried out. A correlation between phenolic contents, individual compounds and antioxidant capacity of different extracts was found. The studied grape extracts have a potential to be applied as natural antioxidants in the pharmaceutical and food industries.

Application and Progress of Chemometrics in Voltammetric Biosensing

The voltammetric electrochemical sensing method combined with biosensors and multi-sensor systems can quickly, accurately, and reliably analyze the concentration of the main analyte and the overall characteristics of complex samples. Simultaneously, the high-dimensional voltammogram contains the rich electrochemical features of the detected substances. Chemometric methods are important tools for mining valuable information from voltammetric data. Chemometrics can aid voltammetric biosensor calibration and multi-element detection in complex matrix conditions. This review introduces the voltammetric analysis techniques commonly used in the research of voltammetric biosensor and electronic tongues. Then, the research on optimizing voltammetric biosensor results using classical chemometrics is summarized. At the same time, the incorporation of machine learning and deep learning has brought new opportunities to further improve the detection performance of biosensors in complex samples. Finally, smartphones connected with miniaturized voltammetric biosensors and chemometric methods provide a high-quality portable analysis platform that shows great potential in point-of-care testing.

QCM Sensor Arrays, Electroanalytical Techniques and NIR Spectroscopy Coupled to Multivariate Analysis for Quality Assessment of Food Products, Raw Materials, Ingredients and Foodborne Pathogen Detection: Challenges and Breakthroughs

Quality checks, assessments, and the assurance of food products, raw materials, and food ingredients is critically important to ensure the safeguard of foods of high quality for safety and public health. Nevertheless, quality checks, assessments, and the assurance of food products along distribution and supply chains is impacted by various challenges. For instance, the development of portable, sensitive, low-cost, and robust instrumentation that is capable of real-time, accurate, and sensitive analysis, quality checks, assessments, and the assurance of food products in the field and/or in the production line in a food manufacturing industry is a major technological and analytical challenge. Other significant challenges include analytical method development, method validation strategies, and the non-availability of reference materials and/or standards for emerging food contaminants. The simplicity, portability, non-invasive, non-destructive properties, and low-cost of NIR spectrometers, make them appealing and desirable instruments of choice for rapid quality checks, assessments and assurances of food products, raw materials, and ingredients. This review article surveys literature and examines current challenges and breakthroughs in quality checks and the assessment of a variety of food products, raw materials, and ingredients. Specifically, recent technological innovations and notable advances in quartz crystal microbalances (QCM), electroanalytical techniques, and near infrared (NIR) spectroscopic instrument development in the quality assessment of selected food products, and the analysis of food raw materials and ingredients for foodborne pathogen detection between January 2019 and July 2020 are highlighted. In addition, chemometric approaches and multivariate analyses of spectral data for NIR instrumental calibration and sample analyses for quality assessments and assurances of selected food products and electrochemical methods for foodborne pathogen detection are discussed. Moreover, this review provides insight into the future trajectory of innovative technological developments in QCM, electroanalytical techniques, NIR spectroscopy, and multivariate analyses relating to general applications for the quality assessment of food products.