Electrochemical Sensors Coupled with Multivariate Statistical Analysis as Screening Tools for Wine Authentication Issues: A Review

An insight into the state of nanotechnology-based electrochemical biosensors for PCOS detection

Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders affecting many women of reproductive age all over the world. PCOS is associated with the onset of enduring health complications, notably diabetes and cardiovascular diseases. Furthermore, PCOS escalates the propensity for conditions such as obesity, insulin resistance, and dyslipidemia, which can potentially culminate in life-threatening scenarios. A pervasive predicament surrounding PCOS pertains to its underdiagnosis due to discrepancies in diagnostic criteria and the intricacy of available testing methodologies. Consequently, many women encounter substantial delays in diagnosis with traditional diagnostic approaches. Prompt identification is imperative, as any delay can precipitate severe consequences. The conventional techniques employed for PCOS detection typically suffer from suboptimal accuracy, protracted assay times, and inherent limitations, thereby constraining their widespread applicability and accessibility. In response to these challenges, various electrochemical methods leveraging nanotechnology have been documented. In this concise review, we endeavor to delineate the deficiencies associated with established conventional methodologies while accentuating the distinctive attributes and benefits inherent to contemporary biosensors. We place particular emphasis on elucidating the pivotal advancements and recent breakthroughs in the realm of nanotechnology-facilitated biosensors for the detection of PCOS.

Recent advancements in chemosensors for the detection of food spoilage

The need for reliable sensors has become a major requirement to confirm the quality and safety of food commodities. Chemosensors are promising sensing tools to identify contaminants and food spoilage to ensure food safety. Chemosensing materials are evolving and becoming potential mechanisms to enable onsite and real-time monitoring of food safety. This review summarizes the information about the basic four types of chemosensors (colorimetric, optical, electrochemical, and piezoelectric) employed in the food sector, the latest advancements in the development of chemo-sensing mechanisms, and their food applications, with special emphasis on the future outlook of them. In this review, we discuss the novel chemosensors developed from the year 2018 to 2022 to detect spoilage in some common types of food like fish, meat, milk, cheese and soy sauce. This work will provide a fundamental step toward further development and innovations of chemosensors targeting different arenas in the food industry.

Flavor characteristics of Shanlan rice wines fermented for different time based on HS-SPME-GC-MS-O, HS-GC-IMS, and electronic sensory analyses

Flavor characteristics of Shanlan rice wines with different fermentation time were analyzed. Results suggested that 3-methyl-1-butanol, phenylethyl alcohol, ethyl acetate, and diethyl succinate were the characteristic volatiles of Shanlan rice wine by using headspace solid-phase microextraction-gas chromatography-mass spectrometry-olfactometry. The most varieties (38) of volatiles appeared at a 3-year-fermentation time, contributing a unique and harmonious aroma to the Shanlan rice wine fermented for 3 years, but only 19 types were observed at 45-days and 1-year fermentation times. A similar trend was intuitively visible in the headspace-gas chromatography-ion mobility spectrometry analysis. The Shanlan rice wine fermented for 3 years had a similar taste profile to that fermented for 45 days, but with distinguishing contents of free amino acids (1352.80 mg/L and 2261.50 mg/L, respectively) and organic acids (9.58 g/L and 49.88 g/L, respectively). The Shanlan rice wine fermented for 1 year had a strong taste with more intensity of most taste attributes.

Integrated characterization of filler tobacco leaves: HS-SPME-GC-MS, E-nose, and microbiome analysis across different origins

This study delves into the aroma characteristics and microbial composition of filler tobacco leaves (FTLs) sourced from six distinct cigar-growing regions within Yunnan, China, following standardized fermentation. An integrated approach using gas chromatography-mass spectrometry (GC-MS), electronic nose (E-nose), and microbiome analysis was employed for comprehensive profiling. Results derived from Linear Discriminant Analysis (LDA) using E-nose data confirmed the presence of notable variability in flavor substance profiles among the FTLs from six regions. Additionally, GC-MS was used to discern disparities in volatile organic compound (VOC) distribution across FTLs from these regions, identifying 92, 81, 79, 58, 69, and 92 VOCs within each respective sample set. Significantly, 24 VOCs emerged as pivotal determinants contributing to the heterogeneity of flavor profiles among FTLs from diverse origins, as indicated by Variable Importance for the Projection (VIP) analysis. Furthermore, distinctions in free amino acid content and chemical constituents were observed across FTLs. Of noteworthy significance, solanone, isophorone, durene, (-)-alpha-terpineol, and 2,3'-bipyridine exhibited the strongest correlations with microbiome data, with fungal microorganisms exerting a more pronounced influence on metabolites, as elucidated through two-way orthogonal partial least-squares (O2PLS) modeling. These findings provide a theoretical and technical basis for accurately evaluating the synchronization of FTLs in aromas and fermentation processes, and they will enhance the quality of fermented FTLs and foster the growth of the domestic cigar tobacco industry ultimately.

High-performance bioelectronic tongue for the simultaneous analysis of phenols, sugars and organic acids in wines

BACKGROUND

Electronic tongues have been widely used to analyze wines. However, owing to the complexity of the matrix, the problem is not completely solved and further improvements are required.

RESULTS

A high-performance potentiometric bioelectronic tongue (bio-ET) specifically devoted to the assessment of wine components is presented. The novelty of this system is due to two innovative approaches. First, the improved performance is obtained through the use of potentiometric biosensors based on carboxylated polyvinyl chloride (PVC) membranes, where enzymes (glucose oxidase, tyrosinase, laccase, and lyase) specific to compounds of interest are linked covalently. Second, the performance is further enhanced by introducing electron mediators (gold nanoparticles or copper phthalocyanine) into the PVC membrane to facilitate the electron transfer process. Individual sensors exposed to target analytes (glucose, catechol, cysteine, or tartaric acid) show a linear behavior, with limits of detection in the region of 10-4  mol L-1 for all the compounds analyzed, with excellent reproducibility (coefficient of variation lower than 3%). Sensors combined to form a bio-ET show excellent capabilities. Principal component (PC) analysis can discriminate monovarietal white wines (PC1 77%; PC2 15%) and red wines (PC1 63%; PC2 30%). Using partial least squares, the bio-ET can provide information about chemical parameters, including glucose, total polyphenols, total anthocyanins, free and total sulfur dioxide, total acidity, and pH with R2 between 0.91 and 0.98 in calibration and between 0.89 and 0.98 in validation.

CONCLUSIONS

This advanced instrument is able to assess the levels of seven parameters in a single measurement, providing an advantageous method to the wine industry. © 2023 Society of Chemical Industry.

Development of a low-cost electrochemical sensor for monitoring components in wastewater treatment processes

Anaerobic digestion (AD) is a complex biological process widely used to decompose various types of organic matter, as well as to produce some metabolites and biogas. Diverse microorganism groups cooperate in many intricate metabolic routes so that organic matter can be degraded. However, any imbalance on these routes can lead to process instability or even failure. Therefore, a proper monitoring system, as well as a good understanding of the process, are key steps to improve performance and stability. Several mathematical models have been developed to represent AD. Despite this, process monitoring is mostly conducted by analytical methods, whose equipment is either expensive or the analyses are time-consuming, which may be a hindrance to low-budget developments. The objective of this study was to develop a low-cost electrochemical sensor to monitor components in wastewater treatment plants. Hundreds of synthetically supplemented sugarcane vinasse and synthetic domestic sewage samples were characterised. The obtained signals were used to calibrate principal component regression, partial least square and artificial neural network estimation models. The predictable variables were chemical oxygen demand, volatile fatty acids, sodium bicarbonate, beef extract, and lipids, and their R2 ranged from 0.84 to 0.99, depending on the component.

Could Collected Chemical Parameters Be Utilized to Build Soft Sensors Capable of Predicting the Provenance, Vintages, and Price Points of New Zealand Pinot Noir Wines Simultaneously?

Soft sensors work as predictive frameworks encapsulating a set of easy-to-collect input data and a machine learning method (ML) to predict highly related variables that are difficult to measure. The machine learning method could provide a prediction of complex unknown relations between the input data and desired output parameters. Recently, soft sensors have been applicable in predicting the prices and vintages of New Zealand Pinot noir wines based on chemical parameters. However, the previous sample size did not adequately represent the diversity of provenances, vintages, and price points across commercially available New Zealand Pinot noir wines. Consequently, a representative sample of 39 commercially available New Zealand Pinot noir wines from diverse provenances, vintages, and price points were selected. Literature has shown that wine phenolic compounds strongly correlated with wine provenances, vintages and price points, which could be used as input data for developing soft sensors. Due to the significance of these phenolic compounds, chemical parameters, including phenolic compounds and pH, were collected using UV-Vis visible spectrophotometry and a pH meter. The soft sensor utilising Naive Bayes (belongs to ML) was designed to predict Pinot noir wines' provenances (regions of origin) based on six chemical parameters with the prediction accuracy of over 75%. Soft sensors based on decision trees (within ML) could predict Pinot noir wines' vintages and price points with prediction accuracies of over 75% based on six chemical parameters. These predictions were based on the same collected six chemical parameters as aforementioned.

Buckypaper-Based Nanostructured Sensor for Port Wine Analysis

The development of electronic gadgets has become of great relevance for the detection of fraud in beverages such as wine, due to the addition of adulterants that bring risks to human health as well as economic impacts. Thus, the present study aims to apply a buckypaper (BP) based on functionalized multiwalled carbon nanotubes (MWCNTs)/cellulose fibers as a sensor for the analysis of Port wine intentionally adulterated with 5 vol.% and 10 vol.% distilled water and ethyl alcohol. The morphology of BP characterized by scanning electron microscopy indicates the formation of agglomerates of random MWCNTs dispersed on the surface and between the fibers of the cellulosic paper. The analysis of the response of the film through the normalized relative resistance change showed a higher response of 0.75 ± 0.16 for adulteration with 10 vol.% of water and a mean response time of 10.0 ± 3.60 s and recovery of approximately 17.2 min for adulteration with 5 vol.% alcohol. Principal component analysis (PCA) was used in data processing to evaluate the ability of BP to recognize and discriminate analytes and adulterating agents, allowing the investigation of its potential application as a low-cost and easy-to-handle multisensor.

Quick classification of strong-aroma types of base Baijiu using potentiometric and voltammetric electronic tongue combined with chemometric techniques

Nowadays, the classification of strong-aroma types of base Baijiu (base SAB) is mainly achieved by human sensory evaluation. However, prolonged tasting brings difficulties for sommeliers in guaranteeing the consistency of results, and may even cause health problems. Herein, an electronic tongue (E-Tongue) combined with a gas chromatography-mass spectrometry (GC-MS) method was successfully developed to grade high-alcoholic base SAB. The E-tongue was capable of identifying base SAB samples into four grades by a discriminant function analysis (DFA) model based on human sensory evaluation results. More importantly, it could effectively and rapidly predict the quality grade of unknown base SAB with an average accuracy up to 95%. The differences of chemical components between base SAB samples were studied by the GC-MS analysis and 52 aroma compounds were identified. The qualitative and quantitative results showed that with the increase of base SAB grade, the varieties and contents of aroma compounds increased. Overall, the comprehensive analysis of E-tongue data and GC-MS results could be in good agreement with human sensory evaluation results, which also proved that the newly developed method has a potential to be a useful alternative to the overall quality grading of base Baijiu.

Nanocellulose-based sensing platforms for heavy metal ions detection: A comprehensive review

Increase in industrial activities has been arising a severe concern about water pollution caused by heavy metal ions (HMIs), such us lead (Pb²⁺), cadmium (Cd²⁺) or mercury (Hg²⁺). The presence of substantial amounts of these ions in the human body is harmful and can cause serious diseases. Hence, the detection of HMIs in water is of great importance. As technological advances have developed, some conventional methods have become obsolete due to some methodological disadvantages, giving way to a second generation that uses novel sensors. Recently, nanocellulose, as a biocompatible material, has drawn a remarkable attraction for developing sensors owing to its extraordinary physical and chemical properties. This review pays a special attention to the different dimensional nanocellulose-based sensors devised for HMIs recognition. What is more, different sensing techniques (optical and electrochemical), sensing mechanisms and the roles of nanocellulose in such sensors are discussed.

Flavor compounds with high odor activity values (OAV > 1) dominate the aroma of aged Chinese rice wine (Huangjiu) by molecular association

Aging is an essential operation to perfect the flavor quality of Hungjiu. In this study, formation mechanism of flavor compounds responsible for the characteristic flavor of aged Huangjiu was investigated. The contents of umami and bitter free amino acids (FAA) increased with the storage period prolonged, while that of sweet FAA showed downward trend. Gas chromatograph-mass spectrometry and principal component analysis indicated that the volatile flavor compounds with OAV exceed 1, especially middle-chain fatty-acid-ethyl-esters and aromatic compounds, dominated the characteristic flavor of aged Huangjiu. Low field-NMR was firstly applied to characterize the molecular association between water and dissolved flavor compounds in aged Huangjiu. The results showed that basic amino acids contributed greatly to the flavor formation of aged Huangjiu via molecular association. In addition, the molecular association significantly promoted the accumulation of flavor compounds with OAV > 1, especially ethyl esters.

Beta-Lactam Antibiotic Discrimination Using a Macromolecular Sensor in Water at Neutral pH

Penicillins and cephalosporins belong to the β-lactam antibiotic family, which accounts for more than half of the world market for antibiotics. Misuse of antibiotics harms human health and the environment. Here, we describe an easy, fast, and sensitive optical method for the sensing and discrimination of two penicillin and five cephalosporin antibiotics in buffered water at pH 7.4, using fifth-generation poly (amidoamine) (PAMAM) dendrimers and calcein, a commercially available macromolecular polyelectrolyte and a fluorescent dye, respectively. In aqueous solution at pH 7.4, the dendrimer and dye self-assemble to form a sensor that interacts with carboxylate-containing antibiotics through electrostatic interaction, monitored through changes in the dye’s spectroscopic properties. This response was captured through absorbance, fluorescence emission, and fluorescence anisotropy. The resulting data set was processed through linear discriminant analysis (LDA), a common pattern-base recognition method, for the differentiation of cephalosporins and penicillins. By pre-hydrolysis of the β-lactam rings under basic conditions, we were able to increase the charge density of the analytes, allowing us to discriminate the seven analytes at a concentration of 5 mM, with a limit of discrimination of 1 mM.

Analysis of Wine and Its Use in Tracing the Origin of Grape Cultivation

The concentrations of elemental and volatile components in wine and the effect of biological, meteorological, and anthropogenic factors on their levels are important for authentication and quality assurance. Sample preparation for atomic absorption and inductively coupled plasma spectrometries for elemental analysis as well as chromatographic and electronic nose (EN) analytical methods for volatile compounds are reviewed. The International Organization of Vine and Wine (OIV) and countries that produce and import wine developed methods and set limits on metal abundance to ensure that all metal concentrations are well below toxic threshold limits. With the use of data analysis tools, elemental analysis can enable wines to be traced back to their geographic region of origin. When paired with volatile and isotopic analysis the accuracy of this authentication greatly improves. Tracing studies are reviewed to demonstrate the capabilities of these analyses.