Evaluation of Red Wine Acidification Using an E-Nose System with Venturi Tool Sampling

Hernández, Esmeralda; Pelegrí-Sebastiá, José; Sogorb, T.; Chilo, José

doi:10.3390/s23062878

Cited by 8 publications

(5 citation statements)

References 22 publications

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“…Regarding volatile acidity, the TGS2620 sensor, in which the gas-induced conductivity change on the metal oxide semiconductor layer is proportional to the gas concentration, is highly selective and sensitive toward each individual volatile organic gas (sensitivity 0.3-0.5), including acetic acid [16]. The lower linearity between the data obtained from the reference method and those evaluated by the instrument can be explained by the fact that some brines, i.e., the regular ones, had an acetic acid concentration lower than the instrument's detection limit (LOD) of 0.1 g/l, falling outside the instrument's calibration line with acetic acid.…”

Section: Discussionmentioning

confidence: 99%

Innovative Device for Automated Monitoring of Table Olive Fermentation Parameters: First Experimental Results

Manganiello¹,

Pagano²,

Ciccoritti

et al. 2023

Machines

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The table olive sector is highly important to the Italian agri-food industry. To produce quality table olives without defects in appearance, flavors, or aroma and to meet consumer expectations, special precautions must be taken to limit side effects associated with transformation and storage processes. During these processes, essential to debitter and stabilize the final product, drupes may undergo undesirable fermentations due to changes in the olive-to-brine ratio, temperature changes, and alteration of the brine’s chemico–physical parameters, thus decreasing their commercial and nutritional value. An innovative user-friendly system, equipped with low-cost digital and sensorized devices, has been engineered and realized for step-by-step batch monitoring of table olive storage brines. The main fermentation parameters (i.e., temperature, pH, salinity, free acidity, volatile acidity, and residual sodium hydroxide) of virgin, compliant, and altered brines were analyzed with both the automated prototype and Official reference methods, with the aim of testing the functionality of the prototype device and verifying the reliability and repeatability of the measurements. Good linearity was observed for all parameters examined, with a relatively low mean deviation between the two approaches. It is therefore possible to constantly monitor brine conformity automatically during the processing stages, benefiting product quality and environmental, energy, and economic sustainability.

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Section: Discussionmentioning

confidence: 99%

Innovative Device for Automated Monitoring of Table Olive Fermentation Parameters: First Experimental Results

Manganiello¹,

Pagano²,

Ciccoritti

et al. 2023

Machines

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“…In other study, a TGS2620 gas sensor module (E‐nose) was fabricated to determine the acetic acid content in red wine which is an indication of quality of wine. The sensor has demonstrated to analyze different concentrations of acetic acid levels in wine (Hernández et al., 2023).…”

Section: Nanosensor Application In Smart Packagingmentioning

confidence: 99%

Review on emerging applications of nanobiosensor in food safety

Guruprasath,

Sankarganesh,

Adeyeye

et al. 2024

Journal of Food Science

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Nanosensors have become an indispensable tool in the food sector due to their specificity and sensitivity. The biosensor consists of a transducer coupled with a biorecognition component to transform biological signal into digital signal. Nanobiosensors have been widely used for sensing toxic chemicals such as pesticide residues and pathogenic microbes owing to their accurate sensitivity in an affordable manner, which gives more hope to the food industry on their applications. It employs nanocarriers to bind to impurities and pollutants, as well as food‐borne microorganisms and their resulting toxins, such as mycotoxins. This modern technology ensures food safety in food processing industries. Nowadays, nanoparticle‐immobilized sensors act as spot indicators to improve smart food packing technology. Certain types of nanobiosensors are deployed to monitor food product manufacture till packaging and to check the freshness of the product till spoilage identification. They are mainly using enzyme catalysts, which are highly sensitive to extreme environmental conditions. As a result, there is a greater evaluation requirement in nanosensor technology to adopt any temperature, pH, or other difficult parameters. Its stability, while in contact with food substrates, is another criterion that needs to be regularized. Within this framework, this review delves into the latest developments in nanobiosensors and the obstacles encountered during their use across different food industries.

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“…After obtaining Q, the intermediate vector is fed into the overheating diagnostic neural network to derive the diagnostic vector named h, which takes the form shown in (15).…”

Section: B Design Of Neural Networkmentioning

confidence: 99%

“…In (15), typeResult vector denotes the category of Xi predicted by the overheating diagnosis neural network, and hmax is the maximum value among h1, h2, h3 and h4.…”

Section: B Design Of Neural Networkmentioning

confidence: 99%

“…Machine olfaction is a technology that enables gas detection by simulating the human olfactory system. It has been widely used and has shown significant advantages in scientific research fields such as gas composition analysis 8 VOLUME XX, 2017 [7], chemical analysis [8,9], agriculture [10,11], medicine [12], food [13][14][15], and criminal investigation [16]. In electrical equipment overheating detection, some scholars have used gas sensors combined with machine olfaction techniques to detect overheating of cables [17,18].…”

Section: Introductionmentioning

confidence: 99%

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A Machine Olfaction-Based Overheating Diagnosis Method for Electrical Equipment

Bao,

Wang,

Yang

et al. 2023

IEEE Access

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Achieving early warning of electrical fires is of great importance in preventing their occurrence. The overheating diagnosis of electrical equipment by detecting volatiles is an effective way to achieve early warning of electrical fires. This paper proposes a machine olfaction-based overheating diagnosis method for electrical equipment. First, the primary materials commonly used for non-metallic elements in electrical equipment are determined. Second, a semiconductor oxide sensor array is designed based on the volatiles generated by these materials during overheating. Next, the output curves of the sensor array at different heating temperatures for these materials are obtained through experiments. Subsequently, the output data of the sensor array at multiple moments in the period of each output curve entering the plateau are extracted to construct the output vectors of the sensor array. Then, the Principal Component Analysis (PCA) algorithm and Linear Discriminant Analysis (LDA) algorithm are used to extract the characteristic quantities in the output vectors to construct the feature vectors. Finally, a second-order BP neural network model is designed based on the feature vector to determine whether the electrical equipment is overheated and what the overheated material is. The experimental results show that the accuracy of the proposed overheating diagnosis method can reach 94.58%.

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Evaluation of Red Wine Acidification Using an E-Nose System with Venturi Tool Sampling

Cited by 8 publications

References 22 publications

Innovative Device for Automated Monitoring of Table Olive Fermentation Parameters: First Experimental Results

Innovative Device for Automated Monitoring of Table Olive Fermentation Parameters: First Experimental Results

Review on emerging applications of nanobiosensor in food safety

A Machine Olfaction-Based Overheating Diagnosis Method for Electrical Equipment

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