Detection of Red Wine Faults over Time with Flash Profiling and the Electronic Tongue

Comparative assessment of Riesling wine fault development by the electronic tongue and a sensory panel

Wine faults threaten brand recognition and consumer brand loyalty. The objective of this study was to compare the acuteness of e-tongue and human sensory evaluation of wine fault development in Riesling wine over 42 days of storage. Riesling wines uninoculated (control) or inoculated with 104 CFU/mL cultures of Wickerhamomyces anomalus, Acetobacter aceti, Lactobacillus brevis, or Pediococcus parvulus were assessed every 7 days with the e-tongue and a rate-all-that-apply (RATA) sensory panel. After 7 days of storage, the e-tongue detected differences in all four wine spoilage microorganism treatments, compared to control wine, with discrimination indices over 86%. The RATA sensory panel detected significant differences beginning on day 35 of storage, 28 days after the e-tongue detected differences. This study showed that the e-tongue was more sensitive than the human panel as a detection tool, without sensory fatigue. PRACTICAL APPLICATION: This research is useful for winemakers seeking additional instrumental methods in the early detection of wine faults. Given the results of this study, the e-tongue can be a useful tool for detecting early chemical changes in white wines that have undergone microbial spoilage, providing winemakers with time to mitigate faults before they surpass sensory thresholds.

Influence of saliva on the sensory properties of US commercial smoke affected wines: Preliminary findings

Previous research has suggested that the impact of smoke affected wines require human evaluation due to in-mouth changes in perception, perhaps associated with saliva. Smoke affected wines (n = 36) from three major wine growing regions in the US were sourced from commercial wineries. A subset of these wines (n = 7) were evaluated by a consumer panel (n = 57) and electronic tongue (e-tongue) to determine the influence of saliva in the sensory profile. Consumers assessed the wines for aroma and other sensory attributes, before and after individual saliva addition. Pooled saliva from consumers was used to treat all wines obtained (n = 36) and then analyzed using the e-tongue. Results showed that saliva did not significantly alter the overall aroma, other than fruity or woody aroma liking by consumers (p > .05). However, the presence of saliva significantly lowered overall liking in both red and white wines that were affected by smoke (p ≤ .05). Consumers rated the subset of smoke affected wines below the "might purchase" category, indicating these wines were not considered acceptable by consumers. When individual pairs of smoke affected wines (before and after saliva additions) were assessed using the e-tongue, the device was able to differentiate the pairs, validating potential usefulness to discern wine changes, though the discrimination indices were moderate to low (68.8% to 11.9%). Based on these data, in human ratings of the aroma and appearance of smoked affected wines, saliva decreased overall liking, and this was somewhat distinguishable by e-tongue analysis.

Recent developments of e-sensing devices coupled to data processing techniques in food quality evaluation: a critical review

A greater demand for high-quality food is being driven by the growth of economic and technological advancements. In this context, consumers are currently paying special attention to organoleptic characteristics such as smell, taste, and appearance. Motivated to mimic human senses, scientists developed electronic devices such as e-noses, e-tongues, and e-eyes, to spot signals relative to different chemical substances prevalent in food systems. To interpret the information provided by the sensors' responses, multiple chemometric approaches are used depending on the aim of the study. This review based on the Web of Science database, endeavored to scrutinize three e-sensing systems coupled to chemometric approaches for food quality evaluation. A total of 122 eligible articles pertaining to the e-nose, e-tongue and e-eye devices were selected to conduct this review. Most of the performed studies used exploratory analysis based on linear factorial methods, while classification and regression techniques came in the second position. Although their applications have been less common in food science, it is to be noted that nonlinear approaches based on artificial intelligence and machine learning deployed in a big-data context have generally yielded better results for classification and regression purposes, providing new perspectives for future studies.

Recent Applications of Potentiometric Electronic Tongue and Electronic Nose in Sensory Evaluation

Electronic tongue (e-tongue) and electronic nose (e-nose) have been widely used to determine food products' taste, aroma, and flavor profiles. Several researchers and industries have recently attempted to find relationships between these e-senses and human sensory panels to ultimately replace sensory panels or use them as a viable alternative to timeconsuming and expensive traditional sensory evaluation (e.g., consumer acceptance testing or descriptive sensory analysis). This study investigated the recent applications of e-tongue and e-nose in the food and beverages sectors and their relationships with human sensory panels, including a trained sensory panel and naïve consumers. According to several studies, the e-tongue, e-nose, or a combination of e-tongue and e-nose can be an effective and powerful tool for rapid assessment of sensory profiles and quality detection with significant correlations with human sensory data. These instruments are also often reported to be more sensitive to detect subtle changes/differences that the human panel cannot detect. Future trends and projections of the e-tongue and e-nose with limitations are also discussed.

Application progress of intelligent flavor sensing system in the production process of fermented foods based on the flavor properties

Fermented foods are sensitive to the production conditions because of microbial and enzymatic activities, which requires intelligent flavor sensing system (IFSS) to monitor and optimize the production process based on the flavor properties. As the simulation system of human olfaction and gustation, IFSS has been widely used in the field of food with the characteristics of nondestructive, pollution-free, and real-time detection. This paper reviews the application of IFSS in the control of fermentation, ripening, and shelf life, and the potential in the identification of quality differences and flavor-producing microbes in fermented foods. The survey found that electronic nose (tongue) is suitable to monitor fermentation process and identify food authenticity in real time based on the changes of flavor profile. Gas chromatography-ion mobility spectrometry and nuclear magnetic resonance technology can be used to analyze the flavor metabolism of fermented foods at various production stages and explore the correlation between flavor substances and microorganisms.

Digital Assessment and Classification of Wine Faults Using a Low-Cost Electronic Nose, Near-Infrared Spectroscopy and Machine Learning Modelling

The winemaking industry can benefit greatly by implementing digital technologies to avoid guesswork and the development of off-flavors and aromas in the final wines. This research presents results on the implementation of near-infrared spectroscopy (NIR) and a low-cost electronic nose (e-nose) coupled with machine learning to detect and assess wine faults. For this purpose, red and white base wines were used, and treatments consisted of spiked samples with 12 faults that are traditionally formed in wines. Results showed high accuracy in the classification models using NIR and e-nose for red wines (94–96%; 92–97%, respectively) and white wines (96–97%; 90–97%, respectively). Implementing new and emerging digital technologies could be a turning point for the winemaking industry to become more predictive in terms of decision-making and maintaining and increasing wine quality traits in a changing and challenging climate.