Journal articles: 'Wine sensor'

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Калмикова, Ірина Семенівна. "THE AUTOMATIC CONTROL OF WINE QUALITY ATTRIBUTES." Scientific Works 82, no. 2 (February 15, 2019): 95–99. http://dx.doi.org/10.15673/swonaft.v82i2.1273.

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Abstract. The article describes the interim results of a research project «The improvement of the process wine quality control with new sensor-based devices». The purpose of our work was to develop a block diagram of the device with connected electronic sensors.

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Grenier, Pierre, Inmaculada Álvarez, Jean-Marie Roger, Vincent Steinmetz, Pierre Barre, and Jean-Marie Sablayrolles. "Artificial intelligence in wine-making." OENO One 34, no. 2 (June 30, 2000): 61. http://dx.doi.org/10.20870/oeno-one.2000.34.2.1007.

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In this paper, some terms of Artificial Intelligence are defined. Some present and potential applications of knowledge based systems are presented in the field of wine-making. Areas of concern were: multi sensor fusion, prediction by model cooperation, and diagnosis. Artificial intelligence techniques can indeed be applied for aiding the wine-maker in his choices. They facilitate the combination between experience and recent progress in technology. When associated with statistical processing, they allow knowledge sources to be used more effectively. Beyond wine-making, the prospects of artificial intelligence are promising for research and food industry, especially for improving the robustness of measurement systems (multi-sensors, sensors interpreted or validated by models), and for process diagnosis (risk prediction, action proposal).

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Jaeger, Stefanie, and Goran Markovic. "8th Dresdner Sensor Symposium: Christmas market, mulled wine and sensors." Analytical and Bioanalytical Chemistry 391, no. 3 (April 8, 2008): 883–84. http://dx.doi.org/10.1007/s00216-008-2033-9.

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Santos, J. P., M. J. Fernández, J. L. Fontecha, J. Lozano, M. Aleixandre, M. García, J. Gutiérrez, and M. C. Horrillo. "SAW sensor array for wine discrimination." Sensors and Actuators B: Chemical 107, no. 1 (May 2005): 291–95. http://dx.doi.org/10.1016/j.snb.2004.10.013.

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Genzardi, Dario, Giuseppe Greco, Estefanía Núñez-Carmona, and Veronica Sberveglieri. "Real Time Monitoring of Wine Vinegar Supply Chain through MOX Sensors." Sensors 22, no. 16 (August 19, 2022): 6247. http://dx.doi.org/10.3390/s22166247.

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Vinegar is a fermented product that is appreciated world-wide. It can be obtained from different kinds of matrices. Specifically, it is a solution of acetic acid produced by a two stage fermentation process. The first is an alcoholic fermentation, where the sugars are converted in ethanol and lower metabolites by the yeast action, generally Saccharomyces cerevisiae. This was performed through a technique that is expanding more and more, the so-called “pied de cuve”. The second step is an acetic fermentation where acetic acid bacteria (AAB) action causes the conversion of ethanol into acetic acid. Overall, the aim of this research is to follow wine vinegar production step by step through the volatiloma analysis by metal oxide semiconductor MOX sensors developed by Nano Sensor Systems S.r.l. This work is based on wine vinegar monitored from the grape must to the formed vinegar. The monitoring lasted 4 months and the analyses were carried out with a new generation of Electronic Nose (EN) engineered by Nano Sensor Systems S.r.l., called Small Sensor Systems Plus (S3+), equipped with an array of six gas MOX sensors with different sensing layers each. In particular, real-time monitoring made it possible to follow and to differentiate each step of the vinegar production. The principal component analysis (PCA) method was the statistical multivariate analysis utilized to process the dataset obtained from the sensors. A closer look to PCA graphs affirms how the sensors were able to cluster the production steps in a chronologically correct manner.

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Sun, Ziqi, Yufeng Zhang, Xinyue Xu, Minglin Wang, and Lijuan Kou. "Determination of the Total Phenolic Content in Wine Samples Using Potentiometric Method Based on Permanganate Ion as an Indicator." Molecules 24, no. 18 (September 9, 2019): 3279. http://dx.doi.org/10.3390/molecules24183279.

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A rapid and accurate determination method for total phenolic content is of great importance for controlling the quality of wine samples. A promising potentiometric detection approach, based on permanganate ion fluxes across ion-selective electrode membranes, is fabricated for measuring the total phenolic content of wine. The results show that the presence of phenols, such as gallic acid, leads to a potential increase for the potentiometric sensor. Additionally, the present sensor exhibits a linear potential response with the concentration range from 0.05 to 3.0 g/L with a detection limit of 6.6 mg/L calculated using gallic acid. These sensors also exhibit a fast response time, an acceptable reproducibility and long-term stability. These results indicate that the proposed potentiometric sensor can be a promising and reliable tool for the rapid determination of total phenolic content in wine samples.

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Chung, Soo, Tu Park, Soo Park, Joon Kim, Seongmin Park, Daesik Son, Young Bae, and Seong Cho. "Colorimetric Sensor Array for White Wine Tasting." Sensors 15, no. 8 (July 24, 2015): 18197–208. http://dx.doi.org/10.3390/s150818197.

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Rossignol, Jérôme, Laurence Dujourdy, Didier Stuerga, Philippe Cayot, Régis D. Gougeon, and Elias Bou-Maroun. "A First Tentative for Simultaneous Detection of Fungicides in Model and Real Wines by Microwave Sensor Coupled to Molecularly Imprinted Sol-Gel Polymers." Sensors 20, no. 21 (October 31, 2020): 6224. http://dx.doi.org/10.3390/s20216224.

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A molecularly imprinted silica (MIS) coupled to a microwave sensor was used to detect three fungicides (iprodione, procymidone and pyrimethanil) present in most French wines. Chemometric methods were applied to interpret the microwave spectra and to correlate microwave signals and fungicide concentrations in a model wine medium, and in white and red Burgundy wines. The developed microwave sensor coupled to an MIS and to its control, a nonimprinted silica (NIS), was successfully applied to detect the three fungicides present in trace levels (ng L−1) in a model wine. The MIS sensor discriminated the fungicide concentrations better than the NIS sensor. Partial Least Squares models were suitable for determining iprodione in white and red wines. A preliminary method validation was applied to iprodione in the white and red wines. It showed a limit of detection (LOD) lower than 30 ng L−1 and a recovery percentage between 90 and 110% when the iprodione concentration was higher than the LOD. The determined concentrations were below the authorized level by far.

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UKEDA, Hiroyuki, Nobuya YAMAMOTO, Masayoshi SAWAMURA, and Hirozo KUSUNOSE. "Microbial Sensor for Estimating Organic Acids in Wine." Analytical Sciences 11, no. 6 (1995): 941–45. http://dx.doi.org/10.2116/analsci.11.941.

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Ferreira, Luiza, Paula Pinheiro, Newton Barbosa Neto, and Marcos Reis. "Buckypaper-Based Nanostructured Sensor for Port Wine Analysis." Sensors 22, no. 24 (December 12, 2022): 9732. http://dx.doi.org/10.3390/s22249732.

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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.

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Vasilescu, Alina, Pablo Fanjul-Bolado, Ana-Maria Titoiu, Roxana Porumb, and Petru Epure. "Progress in Electrochemical (Bio)Sensors for Monitoring Wine Production." Chemosensors 7, no. 4 (December 16, 2019): 66. http://dx.doi.org/10.3390/chemosensors7040066.

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Electrochemical sensors and biosensors have been proposed as fast and cost effective analytical tools, meeting the robustness and performance requirements for industrial process monitoring. In wine production, electrochemical biosensors have proven useful for monitoring critical parameters related to alcoholic fermentation (AF), malolactic fermentation (MLF), determining the impact of the various technological steps and treatments on wine quality, or assessing the differences due to wine age, grape variety, vineyard or geographical region. This review summarizes the current information on the voltamperometric biosensors developed for monitoring wine production with a focus on sensing concepts tested in industry-like settings and on the main quality parameters such as glucose, alcohol, malic and lactic acids, phenolic compounds and allergens. Recent progress featuring nanomaterial-enabled enhancement of sensor performance and applications based on screen-printed electrodes is emphasized. A case study presents the monitoring of alcoholic fermentation based on commercial biosensors adapted with minimal method development for the detection of glucose and phenolic compounds in wine and included in an automated monitoring system. The current challenges and perspectives for the wider application of electrochemical sensors in monitoring industrial processes such as wine production are discussed.

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Tortolini, Cristina, Paolo Bollella, Rosaceleste Zumpano, Gabriele Favero, Franco Mazzei, and Riccarda Antiochia. "Metal Oxide Nanoparticle Based Electrochemical Sensor for Total Antioxidant Capacity (TAC) Detection in Wine Samples." Biosensors 8, no. 4 (November 14, 2018): 108. http://dx.doi.org/10.3390/bios8040108.

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A single-use electrochemical screen-printed electrode is reported based on biomimetic properties of nanoceria particles (CeNPs). The developed tool showed an easy approach compared to the classical spectrophotometric methods reported in literature in terms of ease of use, cost, portability, and unnecessary secondary reagents. The sensor allowed the detection of the total antioxidant capacity (TAC) in wine samples. The sensor has been optimized and characterized electrochemically and then tested with antioxidant compounds occurred in wine samples. The electrochemical CeNPs modified sensor has been used for detection of TAC in white and red commercial wines and the data compared to the 2,2′-azino-bis(3-ethylbenzthiazoline-6-sulphonic acid (ABTS)-based spectrophotometric method. Finally, the obtained results have demonstrated that the proposed sensor was suitable for the simple and quick evaluation of TAC in beverage samples.

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König, A., and K. Thongpull. "Lab-on-Spoon – a 3-D integrated hand-held multi-sensor system for low-cost food quality, safety, and processing monitoring in assisted-living systems." Journal of Sensors and Sensor Systems 4, no. 1 (February 13, 2015): 63–75. http://dx.doi.org/10.5194/jsss-4-63-2015.

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Abstract. Distributed integrated sensory systems enjoy increasing impact leveraged by the surging advance of sensor, communication, and integration technology in, e.g., the Internet of Things, cyber-physical systems, Industry 4.0, and ambient intelligence/assisted-living applications. Smart kitchens and "white goods" in general have become an active field of R&D. The goal of our research is to provide assistance for unskilled or challenged consumers by efficient sensory feedback or context on ingredient quality and cooking step results, which explicitly includes decay and contamination detection. As one front end of such a culinary-assistance system, an integrated, multi-sensor, low-cost, autonomous, smart spoon device, denoted as Lab-on-Spoon (LoS), has been conceived. The first realized instance presented here features temperature, color, and impedance spectroscopy sensing in a 3-D-printed spoon package. Acquired LoS data are subject to sensor fusion and decision making on the host system. LoS was successfully applied to liquid ingredient recognition and quality assessment, including contamination detection, in several applications, e.g., for glycerol detection in wine. In future work, improvement to sensors, electronics, and algorithms will be pursued to achieve an even more robust, dependable and self-sufficient LoS system.

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Kawamura, Yoshiya, Nobuko Kubo, Haruhiko Arata, Yoshio Ito, Masao Tamura, and Katsuhiko Yamamoto. "A Microbial Sensor for Determination of Sulfite in Wines." Journal of AOAC INTERNATIONAL 77, no. 4 (July 1, 1994): 1052–56. http://dx.doi.org/10.1093/jaoac/77.4.1052.

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Abstract The method developed for determining sulfite in wines uses a microbial sensor that consists of sulfur-oxidizing autotrophic bacteria and an oxygen electrode (SO2 meter; SOM), which selectively determines free sulfite in an acidified wine sample. Total sulfite is determined after alkaline extraction; ferrous sulfate is added to the extractant to prevent oxidation. The SOM data showed a coefficient of a variation of 1 % or less (n = 5). The total sulfites in wine determined by SOM were compared with those determined by the Monier–Williams method. Excellent agreement was achieved, as indicated by the regression line for the data: Y = 1.01 X − 1.39 (r = 0.993). With SOM, sulfite can be determined rapidly and accurately with excellent repeatability.

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Lozano, J., M. J. Fernández, J. L. Fontecha, M. Aleixandre, J. P. Santos, I. Sayago, T. Arroyo, J. M. Cabellos, F. J. Gutiérrez, and M. C. Horrillo. "Wine classification with a zinc oxide SAW sensor array." Sensors and Actuators B: Chemical 120, no. 1 (December 2006): 166–71. http://dx.doi.org/10.1016/j.snb.2006.02.014.

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Kutyła-Olesiuk, A., U. E. Wawrzyniak, M. Jańczyk, and W. Wróblewski. "Electrochemical Sensor Arrays for the Analysis of Wine Production." Procedia Engineering 87 (2014): 580–83. http://dx.doi.org/10.1016/j.proeng.2014.11.555.

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Ibáñez, David, María Begoña González-García, David Hernández-Santos, and Pablo Fanjul-Bolado. "Spectroelectrochemical Enzyme Sensor System for Acetaldehyde Detection in Wine." Biosensors 12, no. 11 (November 17, 2022): 1032. http://dx.doi.org/10.3390/bios12111032.

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A new spectroelectrochemical two-enzyme sensor system has been developed for the detection of acetaldehyde in wine. A combination of spectroscopy and electrochemistry improves the analytical features of the electrochemical sensor because the optical information collected with this system is only associated with acetaldehyde and avoids the interferents also present in wines as polyphenols. Spectroelectrochemical detection is achieved by the analysis of the optical properties of the K3[Fe(CN)6]/K4[Fe(CN)6] redox couple involved in the enzymatic process: aldehyde dehydrogenase catalyzes the aldehyde oxidation using β-nicotinamide adenine dinucleotide hydrate (NAD+) as a cofactor and, simultaneously, diaphorase reoxidizes the NADH formed in the first enzymatic process due to the presence of K3[Fe(CN)6]. An analysis of the characteristic UV-vis bands of K3[Fe(CN)6] at 310 and 420 nm allows the detection of acetaldehyde, since absorption bands are only related to the oxidation of this substrate, and avoids the contribution of other interferents.

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Umali, Alona P., Eman Ghanem, Helene Hopfer, Ahmed Hussain, Yu-ting Kao, Lianna G. Zabanal, Brandon J. Wilkins, et al. "Grape and wine sensory attributes correlate with pattern-based discrimination of Cabernet Sauvignon wines by a peptidic sensor array." Tetrahedron 71, no. 20 (May 2015): 3095–99. http://dx.doi.org/10.1016/j.tet.2014.09.062.

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An, Jingxian, Rebecca C. Deed, Paul A. Kilmartin, and Wei Yu. "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?" Foods 12, no. 2 (January 9, 2023): 323. http://dx.doi.org/10.3390/foods12020323.

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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.

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Jeremic, Jelena, Isara Vongluanngam, Arianna Ricci, Giuseppina Paola Parpinello, and Andrea Versari. "The Oxygen Consumption Kinetics of Commercial Oenological Tannins in Model Wine Solution and Chianti Red Wine." Molecules 25, no. 5 (March 8, 2020): 1215. http://dx.doi.org/10.3390/molecules25051215.

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One property of oenological tannins, oxygen reactivity, is commonly exploited in winemaking. The reactivity is mediated by the presence of catalysts (i.e., transition metals and sulfur dioxide) and protects wine against oxidation. This work compares the oxygen consumption rate (OCR) of four commercial oenological tannins (two procyanidins from grape skin and seed, an ellagitannin from oak wood and a gallotannin from gallnut) in a model wine solution and Chianti red wine. All samples were subjected to consecutive cycles of air saturation at 20 °C to increase the total level of oxygen provided. After each cycle, the oxygen level was measured by means of a non-invasive luminescent sensor glued to a transparent surface (sensor dots) until there was no further change in substrate reactivity. The OCR followed first-order kinetics, regardless of the tannin. As expected, the ellagitannin showed the fastest OCR, followed by the two from grape seeds and skins and finally the gallotannin. The total O2 consumption in the red wine was almost double that of the model solution, due to the oxidation of wine substrates. The measurement of OCR is helpful for setting up an advanced winemaking protocol that makes use of tannins to reduce the use of sulfur dioxide.

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Liu, Lantao, Yanli Zhou, Yiyu Kang, Haihong Huang, Congming Li, Maotian Xu, and Baoxian Ye. "Electrochemical Evaluation of trans-Resveratrol Levels in Red Wine Based on the Interaction between Resveratrol and Graphene." Journal of Analytical Methods in Chemistry 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/5749025.

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trans-Resveratrol is often considered as one of the quality standards of red wine, and the development of a sensitive and reliable method for monitoring the trans-resveratrol levels in red wine is an urgent requirement for the quality control. Here, a novel voltammetric approach was described for probing trans-resveratrol using a graphene-modified glassy carbon (GC) electrode. The proposed electrode was prepared by one-step electrodeposition of reduced graphene oxide (ERGO) at a GC electrode. Compared with the bare GC electrode, the introduced graphene film on the electrode surface dramatically improved the sensitivity of the sensor response due to the π-π interaction between the graphene and trans-resveratrol. The developed sensor exhibited low detection limit of 0.2 μM with wide linear range of 0.8–32 μM and high stability. For the analysis of trans-resveratrol in red wine, the high anti-interference ability and the good recoveries indicated the great potential for practical applications.

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Summerson, Vasiliki, Claudia Gonzalez Viejo, Alexis Pang, Damir D. Torrico, and Sigfredo Fuentes. "Assessment of Volatile Aromatic Compounds in Smoke Tainted Cabernet Sauvignon Wines Using a Low-Cost E-Nose and Machine Learning Modelling." Molecules 26, no. 16 (August 23, 2021): 5108. http://dx.doi.org/10.3390/molecules26165108.

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Wine aroma is an important quality trait in wine, influenced by its volatile compounds. Many factors can affect the composition and levels (concentration) of volatile aromatic compounds, including the water status of grapevines, canopy management, and the effects of climate change, such as increases in ambient temperature and drought. In this study, a low-cost and portable electronic nose (e-nose) was used to assess wines produced from grapevines exposed to different levels of smoke contamination. Readings from the e-nose were then used as inputs to develop two machine learning models based on artificial neural networks. Results showed that regression Model 1 displayed high accuracy in predicting the levels of volatile aromatic compounds in wine (R = 0.99). On the other hand, Model 2 also had high accuracy in predicting smoke aroma intensity from sensory evaluation (R = 0.97). Descriptive sensory analysis showed high levels of smoke taint aromas in the high-density smoke-exposed wine sample (HS), followed by the high-density smoke exposure with in-canopy misting treatment (HSM). Principal component analysis further showed that the HS treatment was associated with smoke aroma intensity, while results from the matrix showed significant negative correlations (p < 0.05) were observed between ammonia gas (sensor MQ137) and the volatile aromatic compounds octanoic acid, ethyl ester (r = −0.93), decanoic acid, ethyl ester (r = −0.94), and octanoic acid, 3-methylbutyl ester (r = −0.89). The two models developed in this study may offer winemakers a rapid, cost-effective, and non-destructive tool for assessing levels of volatile aromatic compounds and the aroma qualities of wine for decision making.

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Faragó, Gălătuș, Hintea, Boșca, Feurdean, and Ilea. "An Intra-Oral Optical Sensor for the Real-Time Identification and Assessment of Wine Intake." Sensors 19, no. 21 (October 30, 2019): 4719. http://dx.doi.org/10.3390/s19214719.

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Saliva has gained considerable attention as a diagnostics alternative to blood analyses. A wide spectrum of salivary compounds is correlated to blood concentrations of biomarkers, providing informative and discriminative data regarding the state of health. Intra-oral detection and assessment of food and beverage intake can be correlated and provides valuable information to forecast the formation and modification of salivary biomarkers. In this context, the present work proposes a novel intra-oral optical fiber sensor, developed around an optical coupler topology, and exemplified on the detection and assessment of wine intake, which is accounted for example for the formation of Nε-carboxymethyllysine Advanced Glycation End-products. A laboratory proof of concept validates the proposed solution on four white and four red wine samples. The novel optical sensor geometry shows good spectral properties, accounting for selectivity with respect to grape-based soft drinks. This enables intra-oral detection and objective quality assessment of wine. Moreover, its implementation exploits the advantages of fiber-optics sensing and facilitates integration into a mouthguard, holding considerable potential for real-time biomedical applications to investigate Advanced Glycation End-products in the saliva and their connection with consumption of wine, for the evaluation of risk factors in diet-related diseases.

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Falde, E. J., J. Wang, and M. W. Grinstaff. "Surface tension sensor meshes for rapid alcohol quantification." RSC Adv. 7, no. 78 (2017): 49795–98. http://dx.doi.org/10.1039/c7ra09320a.

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Lvova, Larisa, Irina Yaroshenko, Dmitry Kirsanov, Corrado Di Natale, Roberto Paolesse, and Andrey Legin. "Electronic Tongue for Brand Uniformity Control: A Case Study of Apulian Red Wines Recognition and Defects Evaluation †." Sensors 18, no. 8 (August 7, 2018): 2584. http://dx.doi.org/10.3390/s18082584.

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The potentiometric electronic tongue system has been tested as a potential analytical tool for brand uniformity control of monoculture Apulian red wines (Primitivo and Negroamaro). The sensor array was composed of eight porphyrin coatings obtained by electrochemical polymerization process and was employed for both wines discrimination and quantitative detection of wine defect compounds: “off-odour” 3-(methylthio)-propanol; isoamyl alcohol fusel oil; benzaldehyde (marker of the yeast activity) and acetic acid (marker of vinegar formation). PLS-DA applied to Electronic tongue output data has permitted a correct discrimination of more than 70% of analysed wines in respect to the original brand affiliation. Satisfactory PLS1 predictions were obtained in real wine samples; with R2 = 0.989 for isoamyl alcohol and R2 = 0.732 for acetic acid. Moreover; the possibility to distinguish wine samples on the base of permitted levels of fault compounds content was shown.

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Mugo, S. M., B. J. Edmunds, D. J. Berg, and N. K. Gill. "An integrated carbon entrapped molecularly imprinted polymer (MIP) electrode for voltammetric detection of resveratrol in wine." Analytical Methods 7, no. 21 (2015): 9092–99. http://dx.doi.org/10.1039/c5ay01799h.

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Anastasiou, Evangelos, Athanasios Balafoutis, Serafeim Theocharis, Nikolaos Theodorou, Stefanos Koundouras, and Spyros Fountas. "Assessment of Laser Scanner Use under Different Settings in Two Differently Managed Vineyards for Estimating Pruning Wood Parameters." AgriEngineering 4, no. 3 (August 9, 2022): 733–46. http://dx.doi.org/10.3390/agriengineering4030047.

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Precision viticulture employs various sensors for assessing nondestructively key parameters in vineyards. One of the most promising technologies for this purpose is the laser scanner sensor. Laser scanner uses the LiDAR (Light Detection And Ranging) method for the calculation of the distance from the sensor. However, the number of cultivation operations affects the credibility of sensors such as the laser scanner. The main aim of this study was to assess a laser scanner sensor at different measurement settings for estimating pruning wood parameters on two wine grape cultivars (Sauvignon Blanc and Syrah) that received different numbers of farming interventions. The experiment was conducted in the two vineyards situated in the same farm for two successive years (2014 and 2015). The results indicated that the use of a laser scanner in the Syrah vineyard presented more accurate results (r = 0.966 in 2014 and r = 0.806 in 2015) when compared to the Sauvignon Blanc one (r = 0.839 in 2014 and r = 0.607 in 2015) regarding pruning wood parameters estimation. Different measurement settings and weather conditions had different effects on the accuracy of the sensor. It can be concluded that the laser scanner is a very helpful sensor for estimating pruning wood parameters in vineyards.

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Li, Junjie, Beibei Fu, Changjun Hou, Danqun Huo, Mei Yang, Caihong Shen, and Huibo Luo. "A colorimetric multilayer sensor for discriminating red wine and green tea by measurement of antioxidant activity." Analytical Methods 8, no. 16 (2016): 3345–52. http://dx.doi.org/10.1039/c5ay03360h.

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A sensor was fabricated by alternative assembly of chitosan, Fe³⁺ complexes and alginate sodium on filter paper modified with a TiO₂ membrane. The sensor has good super-hydrophobicity and polyphenols in aqueous samples can be pre-concentrated on its surface, providing improved sensor sensitivity.

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Kim, Yong-Sung, and Yong-Suk Kim. "Biometrics Analysis and Evaluation on KoreanMakgeolliUsing Brainwaves and Taste Biological Sensor System." BioMed Research International 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/918631.

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There are several methods available in measuring food taste. The sensory evaluation, for instance, is a typical method for panels to test of taste and recognize smell with their nose by measuring the degree of taste characteristic, intensity, and pleasure. There are many issues entailed in the traditional sensory evaluation method such as forming a panel and evaluation cost; moreover, it is only localized in particular areas. Accordingly, this paper aimed to select food in one particular area, and compare and review the content between sensory evaluations using a taste biological sensor, as well as presenting an analysis of brainwaves using EEG and finally a proposal of a new method for sensory evaluation. In this paper, the researchers have conducted a sensory evaluation whereas a maximum of nine points were accumulated by purchasing eight types of rice wine. These eight types ofMakgeolliwere generalized by generating multidimensional data with the use of TS-5000z, thus learning mapping points and scaling them. The contribution of this paper, therefore, is to overcome the disadvantages of the sensory evaluation with the usage of the suggested taste biological sensor system.

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Wu, Qinghong, and Wanying Zhang. "Nano Sensor Using One Dimensional Porous Indium Oxide and Pattern Recognition Method of Its Electronic Information." Journal of Nanoelectronics and Optoelectronics 16, no. 2 (February 1, 2021): 255–63. http://dx.doi.org/10.1166/jno.2021.2955.

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Due to its high sensitivity, low price and fast response speed, gas sensors based on metal oxide nanomate-rials have attracted many researchers to modify and explore the materials. First, pure indium oxide (In2O3) nanotubes (NTs)/porous NTs (PNTs) and Ho doped In2O3 NTs/PNTs are prepared by electrospinning and calcination. Then, based on the prepared nanomaterials, the 6-channel sensor array is obtained and used in the electronic nose sensing system for wine product identification. The system obtains the frequency signals of different liquor products by means of 6-channel sensor array, analyzes the extracted electronic signal characteristic information by means of ordinary least squares, and introduces the pattern recognition method of moving average and linear discriminant to identify liquor products. In the experiment, compared with pure In2O3 NTs sensor, pure In2O3 PNTs sensor has higher sensitivity to 100 ppm ethanol gas, and the sensitivity is further improved after mixing Ho. Among them, 6 mol% Ho + In2O3 PNTs have the highest sensitivity and the shortest response time; based on the electronic nose system composed of prepared nanomaterial sensor array, frequency signals of different Wu Liang Ye wines are collected. With the extension of acquisition time, the corresponding frequency first decreases and then becomes stable; the extracted liquor characteristic signal is projected into two-dimensional space and three-dimensional space. The results show that the pattern recognition system based on this method can extract the characteristic signals of liquor products and distinguish them.

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Diago, María Paz, Zenaida Guadalupe, Javier Baluja, Borja Millan, and Javier Tardáguila. "Appraisal of wine color and phenols from a non-invasive grape berry fluorescence method." OENO One 47, no. 1 (March 31, 2013): 55. http://dx.doi.org/10.20870/oeno-one.2013.47.1.1532.

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Aims: To investigate the relationships between the anthocyanin content of Vitis vinifera L. cvs. Tempranillo and Graciano grapes, determined in the vineyard and in the winery by a non-invasive fluorescence sensor, and the final wine color and phenolic traits.Methods and results: Grape anthocyanin and phenol measurements were conducted with a hand-held, non-destructive fluorescence-based proximal sensor, in the vineyard (on clusters hanging on the vine) and at the winery (on harvested clusters in boxes) in two seasons. The anthocyanin fluorescence indices, ANTH_RG and FERARI, were found to significantly correlate with the wine color density (R2 ranged from 0.51 to 0.82) and total phenol index (R2 ranged from 0.44 to 0.87), regardless that the measurements were made in the vineyard or in the winery. Similarly, the CIELAB parameters defining lightness (L*), hue angle (h*) and coordinate b* (yellow-blue component of the wine tonality) also showed significant relationships (R2 ranged from 0.55 to 0.74) with ANTH_RG and FERARI indices in very young wines.Conclusion: This preliminary study showed that satisfactory estimation of the final wine color and phenolic characteristics can be obtained from fast, non-destructive measurements in grapes, using a fluorescence-based sensor, either in the vineyard or in the winery.Significance and impact of the study: This is the first work showing the capabilities of the chlorophyll fluorescence of grapes to estimate the final wine color and phenolic traits. This information could help the wine industry make more informed decisions regarding selective harvest and winemaking in a fast and cost-effective way.

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Schmidt, Dominik, Maximilian Freund, and Kai Velten. "End-User Software for Efficient Sensor Placement in Jacketed Wine Tanks." Fermentation 4, no. 2 (June 9, 2018): 42. http://dx.doi.org/10.3390/fermentation4020042.

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Zeng, Jiayi, Xiaoan Cao, Yonghui Liu, Jinglin Chen, and Keke Ren. "A single cataluminescence sensor for wine identification by luminescent response profiles." Analytical Methods 6, no. 8 (2014): 2633. http://dx.doi.org/10.1039/c4ay00021h.

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Rong, Li, Wang Ping, and Hu Wenlei. "A novel method for wine analysis based on sensor fusion technique." Sensors and Actuators B: Chemical 66, no. 1-3 (July 2000): 246–50. http://dx.doi.org/10.1016/s0925-4005(00)00378-6.

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Cañizares, Pilar, and M. D. Luque de Castro. "Flow-through spectrofluorimetric sensor for the determination of glycerol in wine." Analyst 120, no. 12 (1995): 2837–40. http://dx.doi.org/10.1039/an9952002837.

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Lin, Ke, and Yao. "Discrimination of Red Wines with a Gas-Sensor Array Based on a Surface-Acoustic-Wave Technique." Micromachines 10, no. 11 (October 26, 2019): 725. http://dx.doi.org/10.3390/mi10110725.

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We applied a thermal-desorption gas-chromatograph mass-spectrometer (TD-GC–MS) system to identify the marker volatile organic compounds (VOCs) in the aroma of red wine. After obtaining the marker VOC, we utilized surface acoustic waves (SAWs) to develop a highly sensitive sensing system as 'electronic nose' to detect these marker VOC. The SAW chips were fabricated on a LiNbO3 substrate with a lithographic process. We coated sensing polymers on the sensing area to adsorb the marker VOC in a sample gas. The adsorption of the marker VOC altered the velocity of the SAW according to a mass-loading effect, causing a frequency decrease. This experiment was conducted with wines of three grape varieties—cabernet sauvignon, merlot and black queen. According to the results of TD-GC–MS, the King brand of red wine is likely to have unique VOC, which are 2-pentanone, dimethyl disulfide, 2-methylpropyl acetate and 2-pentanol; Blue Nun-1 probably has a special VOC such as 2,3-butanedione. We hence used a SAW sensor array to detect the aroma of red wines and to distinguish their components by their frequency shift. The results show that the use of polyvinyl butyral (PVB) as a detecting material can distinguish Blue Nun-2 from the others and the use of polyvinyl alcohol (PVA) can distinguish King from the others. We conducted random tests to prove the accuracy and the reliability of our SAW sensors.

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Izquierdo-Llopart, Anais, and Javier Saurina. "Multi-Sensor Characterization of Sparkling Wines Based on Data Fusion." Chemosensors 9, no. 8 (July 30, 2021): 200. http://dx.doi.org/10.3390/chemosensors9080200.

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This paper is focused on the assessment of a multi-sensor approach to improve the overall characterization of sparkling wines (cava wines). Multi-sensor, low-level data fusion can provide more comprehensive and more accurate vision of results compared with the study of simpler data sets from individual techniques. Data from different instrumental platforms were combined in an enriched matrix, integrating information from spectroscopic (UV/Vis and FTIR), chromatographic, and other techniques. Sparkling wines belonging to different classes, which differed in the grape varieties, coupages, and wine-making processes, were analyzed to determine organic acids (e.g., tartaric, lactic, malic, and acetic acids), pH, total acidity, polyphenols, total antioxidant capacity, ethanol, or reducing sugars. The resulting compositional values were treated chemometrically for a more efficient recovery of the underlaying information. In this regard, exploratory methods such as principal component analysis showed that phenolic compounds were dependent on varietal and blending issues while organic acids were more affected by fermentation features. The analysis of the multi-sensor data set provided a more comprehensive description of cavas according to grape classes, blends, and vinification processes. Hierarchical Cluster Analysis (HCA) allowed specific groups of samples to be distinguished, featuring malolactic fermentation and the chardonnay and red grape classes. Partial Least Squares-Discriminant Analysis (PLS-DA) also classified samples according to the type of grape varieties and fermentations. Bar charts and complementary statistic test were performed to better define the differences among the studied samples based on the most significant markers of each cava wine type. As a conclusion, catechin, gallic, gentisic, caftaric, caffeic, malic, and lactic acids were the most remarkable descriptors that contributed to their discrimination based on varietal, blending, and oenological factors.

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Rossignol, Jérôme, Philippe Cayot, Didier Stuerga, Régis D. Gougeon, and Elias Bou-Maroun. "Real-Time Detection of Phenylacetaldehyde in Wine: Application of a Microwave Sensor Based on Molecularly Imprinted Silica." Molecules 27, no. 5 (February 23, 2022): 1492. http://dx.doi.org/10.3390/molecules27051492.

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Molecularly imprinted sol–gel silica (MIS) coupled to a microwave sensor was designed and used to detect phenylacetaldehyde (PAA), a chemical tracer of wine oxidation. The developed method is fast, cheap and could replace the classical chromatographic methods, which require a tedious sample preparation and are expensive. To reach our objective, five MIS and their control non-imprinted silica (NIS) were synthesized and their extraction capacity toward PAA was studied in hydro alcoholic medium. The selected polymers, based on this first step, were subjected to a selectivity study in the presence of PAA and three other competing molecules. The best polymer was integrated in a microwave sensor and was used to assess PAA in red wine. The developed sensor was able to detect PAA at the µg·L−1 level, which is below the off-flavour threshold.

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Xia, Yanan, Musu Zha, Hao Liu, Quan Shuang, Yongfu Chen, and Xujin Yang. "Novel Insight into the Formation of Odour—Active Compounds in Sea Buckthorn Wine and Distilled Liquor Based on GC–MS and E–Nose Analysis." Foods 11, no. 20 (October 20, 2022): 3273. http://dx.doi.org/10.3390/foods11203273.

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Sea buckthorn wine (SW) and distilled liquor (DL) are fruit wines with beneficial health effects. However, their unpleasant flavour limits their development and widespread acceptance. Therefore, it is necessary to analyse their flavour composition and changes. In this study, differential metabolites of sea buckthorn DL during processing were analysed, and the relationships between E–nose sensor values and key volatile organic compounds (VOCs) were established. The results show that 133 VOCs were identified, with 22 aroma–contributing components. Fermentation significantly increased the content of VOCs, especially esters. A total of seven and 51 VOCs were significantly upregulated after fermentation and distillation, respectively. Meanwhile, seven sensors were positively correlated with the increased level of alcohols and esters, and reflected the increasing trends of 10 key VOCs.

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Zheng, Ziwei, Shanshan Qiu, and Zhenbo Wei. "A Novel Voltammetric Electronic Tongue Based on Nanocomposites Modified Electrodes for the Discrimination of Red Wines from Different Geographical Origins." Chemosensors 10, no. 8 (August 13, 2022): 332. http://dx.doi.org/10.3390/chemosensors10080332.

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A novel voltammetric electronic tongue (VE-tongue) system based on three nanocomposites modified working electrodes was used for the discrimination of red wine from different geographical origins. The three types of modified working electrodes were fabricated to detect glucose (Glu), tartaric acid (TA), and non-specific flavor information in a red wine sample, respectively. The electrochemical properties of three electrodes were tested by cyclic voltammetric method, and pH, accumulation time, and scan rates were optimized for Glu and TA sensors. Scanning electron microscopy (SEM), X-ray proton spectrum (XPS), and X-ray diffraction (XRD) were used for the characterization of modified materials. This sensor array was then applied to identify four kinds of red wines from different geographical origins, and the multi-frequency and potential steps (STEP) method was used to obtain flavor information regarding rice wines. The classification ability of this VE-tongue system was evaluated by using partial least squares (PLS) regression and principal component analysis (PCA), while back propagation neural network (BPNN), random forest (RF), support vector machines (SVM), deep neural network (DNN), and K-nearest neighbor (KNN) were used for the prediction. The results showed that PCA could explain about the 95.7% of the total variance, and BPNN performed best in the prediction work (the prediction accuracy was 95.8%). Therefore, the VE-tongue system with BPNN was chosen to effectively discriminate red wines from different geographical origins, and the novel VE-tongue aiming at red wine discrimination with high accuracy and lower cost was established.

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Vlasov, Yu, A. Legin, A. Rudnitskaya, C. Di Natale, and A. D'Amico. "Nonspecific sensor arrays ("electronic tongue") for chemical analysis of liquids (IUPAC Technical Report)." Pure and Applied Chemistry 77, no. 11 (January 1, 2005): 1965–83. http://dx.doi.org/10.1351/pac200577111965.

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The history of the development of potentiometric sensors over the past century demonstrates progress in constructing single, discrete (i.e., separate, to distinguish from sensor arrays) ion sensors, which have been made as selective as possible. Only a few types reveal high selectivity. However, easy measurement procedure, with low cost and availability, give rise to the search for new ways for their successful application. The present document describes a new concept for application of potentiometric multisensor systems, viz., sensor arrays for solution analysis, and the performance of this new analytical tool - the "electronic tongue". The electronic tongue is a multisensor system, which consists of a number of low-selective sensors and uses advanced mathematical procedures for signal processing based on the pattern recognition (PARC) and/or multivariate analysis [artificial neural networks (ANNs), principal component analysis (PCA), etc.]. Definitions of the multisensor systems and their parameters are suggested. Results from the application of the electronic tongue, both for quantitative and qualitative analysis of different mineral water and wine samples, are presented and discussed.

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Borowik, Piotr, Leszek Adamowicz, Rafał Tarakowski, Krzysztof Siwek, and Tomasz Grzywacz. "Odor Detection Using an E-Nose With a Reduced Sensor Array." Sensors 20, no. 12 (June 23, 2020): 3542. http://dx.doi.org/10.3390/s20123542.

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Recent advances in the field of electronic noses (e-noses) have led to new developments in both sensors and feature extraction as well as data processing techniques, providing an increased amount of information. Therefore, feature selection has become essential in the development of e-nose applications. Sophisticated computation techniques can be applied for solving the old problem of sensor number optimization and feature selections. In this way, one can find an optimal application-specific sensor array and reduce the potential cost associated with designing new e-nose devices. In this paper, we examine a procedure to extract and select modeling features for optimal e-nose performance. The usefulness of this approach is demonstrated in detail. We calculated the model’s performance using cross-validation with the standard leave-one-group-out and group shuffle validation methods. Our analysis of wine spoilage data from the sensor array shows when a transient sensor response is considered, both from gas adsorption and desorption phases, it is possible to obtain a reasonable level of odor detection even with data coming from a single sensor. This requires adequate extraction of modeling features and then selection of features used in the final model.

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Nekrasov, Kireev, Emelianov, and Bobrinetskiy. "Graphene-Based Sensing Platform for On-Chip Ochratoxin A Detection." Toxins 11, no. 10 (September 20, 2019): 550. http://dx.doi.org/10.3390/toxins11100550.

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In this work, we report an on-chip aptasensor for ochratoxin A (OTA) toxin detection that is based on a graphene field-effect transistor (GFET). Graphene-based devices are fabricated via large-scale technology, allowing for upscaling the sensor fabrication and lowering the device cost. The sensor assembly was performed through covalent bonding of graphene’s surface with an aptamer specifically sensitive towards OTA. The results demonstrate fast (within 5 min) response to OTA exposure with a linear range of detection between 4 ng/mL and 10 pg/mL, with a detection limit of 4 pg/mL. The regeneration time constant of the sensor was found to be rather small, only 5.6 s, meaning fast sensor regeneration for multiple usages. The high reproducibility of the sensing response was demonstrated via using several recycling procedures as well as various GFETs. The applicability of the aptasensor to real samples was demonstrated for spiked red wine samples with recovery of about 105% for a 100 pM OTA concentration; the selectivity of the sensor was also confirmed via addition of another toxin, zearalenone. The developed platform opens the way for multiplex sensing of different toxins using an on-chip array of graphene sensors.

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Gutiérrez, A., J. A. Burgos, C. Garcerá, M. Zarzo, M. L. Ruiz, and E. Moltó. "Optimization of an aroma sensor for assessing grape quality for wine making." Spanish Journal of Agricultural Research 5, no. 2 (June 1, 2007): 157. http://dx.doi.org/10.5424/sjar/2007052-235.

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Lozano, Jesús, José Pedro Santos, José Ignacio Suárez, Mariano Cabellos, Teresa Arroyo, and Carmen Horrillo. "Automatic Sensor System for the Continuous Analysis of the Evolution of Wine." American Journal of Enology and Viticulture 66, no. 2 (October 30, 2014): 148–55. http://dx.doi.org/10.5344/ajev.2014.14103.

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Sasaki, Yui, Satoshi Ito, Zhoujie Zhang, Xiaojun Lyu, Shin‐ya Takizawa, Riku Kubota, and Tsuyoshi Minami. "Supramolecular Sensor for Astringent Procyanidin C1: Fluorescent Artificial Tongue for Wine Components." Chemistry – A European Journal 26, no. 69 (October 14, 2020): 16236–40. http://dx.doi.org/10.1002/chem.202002262.

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Osorio, Daniel, J. Ricardo Pérez-Correa, Eduardo Agosin, and Miguel Cabrera. "Soft-sensor for on-line estimation of ethanol concentrations in wine stills." Journal of Food Engineering 87, no. 4 (August 2008): 571–77. http://dx.doi.org/10.1016/j.jfoodeng.2008.01.011.

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Kwon, Sun-Young, Hai-Doo Kwen, and Seong-Ho Choi. "Fabrication of Nonenzymatic Glucose Sensors Based on Multiwalled Carbon Nanotubes with Bimetallic Pt-M (M = Ru and Sn) Catalysts by Radiolytic Deposition." Journal of Sensors 2012 (2012): 1–8. http://dx.doi.org/10.1155/2012/784167.

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Nonenzymatic glucose sensors employing multiwalled carbon nanotubes (MWNTs) with highly dispersed Pt-M (M = Ru and Sn) nanoparticles (Pt-M@PVP-MWNTs) were fabricated by radiolytic deposition. The Pt-M nanoparticles on the MWNTs were characterized by transmittance electron microscopy, elemental analysis, and X-ray diffraction. They were found to be well dispersed and to exhibit alloy properties on the MWNT support. Electrochemical testing showed that these nonenzymatic sensors had larger currents (mA) than that of a bare glassy carbon (GC) electrode and one modified with MWNTs. The sensitivity (A mM−1), linear range (mM), and detection limit (mM) (S/N = 3) of the glucose sensor with the Pt-Ru catalyst in NaOH electrolyte were determined as 18.0, 1.0–2.5, 0.7, respectively. The corresponding data of the sensor with Pt-Sn catalyst were 889.0, 1.00–3.00, and 0.3, respectively. In addition, these non-enzymatic sensors can effectively avoid interference arising from the oxidation of the common interfering species ascorbic acid and uric acid in NaOH electrolyte. The experimental results show that such sensors can be applied in the detection of glucose in commercial red wine samples.

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Noguer, Thierry, Anca Tencaliec, Carole Calas-Blanchard, Alina Avramescu, and Jean-Louis Marty. "Interference-Free Biosensor Based on Screen-Printing Technology and Sol-Gel Immobilization for Determination of Acetaldehyde in Wine." Journal of AOAC INTERNATIONAL 85, no. 6 (November 1, 2002): 1382–89. http://dx.doi.org/10.1093/jaoac/85.6.1382.

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Abstract A monoenzymatic amperometric biosensor was developed for the detection of acetaldehyde. The sensor is based on the association of screen-printed carbon electrodes and aldehyde dehydrogenase immobilized by a sol-gel entrapment method. Modification of screen-printed carbon electrodes with Reinecke salt of Meldola's Blue (MBRS) resulted in highly sensitive and interference- free nicotinamide-adenine dinucleotide (NADH) detectors. Based on MBRS-mediated oxidation of NADH at –150 mV versus pseudo Ag/AgCl, acetaldehyde was determined in the range 10–260 μM, compatible with wine quality monitoring. The method of immobilization based on sol-gel entrapment was optimized to obtain the best compromise between sensitivity and operational stability. The sensor response was stable for 40 consecutive assays with methyltrimethoxysilane used as alkoxide precursor, thus allowing a possible calibration of the sensor before each measurement. The biosensors were used to analyze French wines. The method was validated with a commercially available enzymatic kit based on a standard spectrophotometric method.

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Zhang, Sheng Yi, and Xin Ming Wang. "The Design of Temperature Control System for Rice Wine Fermentation." Applied Mechanics and Materials 341-342 (July 2013): 660–63. http://dx.doi.org/10.4028/www.scientific.net/amm.341-342.660.

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Fermentation temperature is the key to decide the quality of the rice wine, so thetemperature controlling system in fermentation room is established base on stm32 microcontrollerand digital temperature sensor. The whole block diagram for the system is firstly detailed, and thenthe Temperature collecting module and temperature control module are also described. At last thesoftware flow chart is discussed. The experiment is done based on designed system, and the data isanalyzed. The result show that designed system can realize high accuracy temperature controlling.

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Journal articles on the topic 'Wine sensor'

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