Electronic Tongues and Noses: A General Overview.

As technology advances, electronic tongues and noses are becoming increasingly important in various industries. These devices can accurately detect and identify different substances and gases based on their chemical composition. This can be incredibly useful in fields such as environmental monitoring and industrial food applications, where the quality and safety of products or ecosystems should be ensured through a precise analysis. Traditionally, this task is performed by an expert panel or by using laboratory tests but sometimes becomes a bottleneck because of time and other human factors that can be solved with technologies such as the provided by electronic tongue and nose devices. Additionally, these devices can be used in medical diagnosis, quality monitoring, and even in the automotive industry to detect gas leaks. The possibilities are endless, and as these technologies continue to improve, they will undoubtedly play an increasingly important role in improving our lives and ensuring our safety. Because of the multiple applications and developments in this field in the last years, this work will present an overview of the electronic tongues and noses from the point of view of the approaches developed and the methodologies used in the data analysis and steps to this aim. In the same manner, this work shows some of the applications that can be found in the use of these devices and ends with some conclusions about the current state of these technologies.

[Application and development of electronic sensing technologies represented by electronic nose in modern traditional Chinese medicine preparations].

Odor is one of the important indicators evaluating the quality of traditional Chinese medicines. Research data has shown that there are increasing methods available for evaluating the odors of traditional Chinese medicines. Compared with conventional odor sensing techniques, electronic noses stand out for their convenience, high speed, and objectivity. The progress in the pharmaceutical technology of traditional Chinese medicines has provided new formulas and dosage forms for the innovative development in this field. The electronic nose with versatility can be customized to be equipped with a variety of cross-sensors, which can well satisfy the needs of the traditional Chinese medicine preparation technology. This study summarizes the characteristics, application status, and representative products of the current electronic nose, and analyzes the application and feasibility of electronic nose in the production of traditional Chinese medicine preparations based on the current status of odor evaluation. This review is expected to provide new methods, techno-logies, and ideas for electronic nose to play its unique role in the whole-process quality control and pharmaceutical process of traditional Chinese medicine preparations.

Modulating peppermint oil flavor release properties of emulsion-filled protein gels: Impact of cross-linking method and matrix composition.

For some food applications, it is desirable to control the flavor release profiles of volatile flavor compounds. In this study, the effects of crosslinking method and protein composition on the flavor release properties of emulsion-filled protein hydrogels were explored, using peppermint essential oil as a model volatile compound. Emulsion-filled protein gels with different properties were prepared using different crosslinking methods and gelatin concentrations. Flavor release from the emulsion gels was then monitored using an electronic nose, gas chromatography-mass spectrometry (GC-MS), and sensory evaluation. Enzyme-crosslinked gels had greater hardness and storage modulus than heat-crosslinked ones. The hardness and storage modulus of the gels increased with increasing gelatin concentration. For similar gel compositions, flavor release and sensory perception were faster from the heat-crosslinked gels than the enzyme-crosslinked ones. For the same crosslinking method, flavor release and perception decreased with increasing gelatin concentration, which was attributed to retardation of flavor diffusion through the hydrogel matrix. Overall, this study shows that the release of hydrophobic aromatic substances can be modulated by controlling the composition and crosslinking of protein hydrogels, which may be useful for certain food applications.

MXene/Hydrogel-based bioelectronic nose for the direct evaluation of food spoilage in both liquid and gas-phase environments.

Various bioelectronic noses have been recently developed for mimicking human olfactory systems. However, achieving direct monitoring of gas-phase molecules remains a challenge for the development of bioelectronic noses due to the instability of receptor and the limitations of its surrounding microenvironment. Here, we report a MXene/hydrogel-based bioelectronic nose for the sensitive detection of liquid and gaseous hexanal, a signature odorant from spoiled food. In this study, a conducting MXene/hydrogel structure was formed on a sensor via physical adsorption. Then, canine olfactory receptor 5269-embedded nanodiscs (cfOR5269NDs) which could selectively recognize hexanal molecules were embedded in the three-dimensional (3D) MXene/hydrogel structures using glutaraldehyde as a linker. Our MXene/hydrogel-based bioelectronic nose exhibited a high selectivity and sensitivity for monitoring hexanal in both liquid and gas phases. The bioelectronic noses could sensitively detect liquid and gaseous hexanal down to 10-18 M and 6.9 ppm, and they had wide detection ranges of 10-18 - 10-6 M and 6.9-32.9 ppm, respectively. Moreover, our bioelectronic nose allowed us to monitor hexanal levels in fish and milk. In this respect, our MXene/hydrogel-based bioelectronic nose could be a practical strategy for versatile applications such as food spoilage assessments in both liquid and gaseous systems.

Characterization of Flavor Profile of Sauced Pork from Different Regions of China Based on E-Nose, E-Tongue and Gas Chromatography-Ion Mobility Spectroscopy.

This study aimed to investigate the volatile flavor compounds and tastes of six kinds of sauced pork from the southwest and eastern coastal areas of China using gas chromatography-ion mobility spectroscopy (GC-IMS) combined with an electronic nose (E-nose) and electronic tongue (E-tongue). The results showed that the combined use of the E-nose and E-tongue could effectively identify different kinds of sauced pork. A total of 52 volatile flavor compounds were identified, with aldehydes being the main flavor compounds in sauced pork. The relative odor activity value (ROAV) showed that seven key volatile compounds, including 2-methylbutanal, 2-ethyl-3, 5-dimethylpyrazine, 3-octanone, ethyl 3-methylbutanoate, dimethyl disulfide, 2,3-butanedione, and heptane, contributed the most to the flavor of sauced pork (ROAV ≥1). Multivariate data analysis showed that 13 volatile compounds with the variable importance in projection (VIP) values > 1 could be used as flavor markers to distinguish six kinds of sauced pork. Pearson correlation analysis revealed a significant link between the E-nose sensor and alcohols, aldehydes, terpenes, esters, and hetero-cycle compounds. The results of the current study provide insights into the volatile flavor compounds and tastes of sauced pork. Additionally, intelligent sensory technologies can be a promising tool for discriminating different types of sauced pork.

Recent Advances and Future Perspectives in the E-Nose Technologies Addressed to the Wine Industry.

Electronic nose devices stand out as pioneering innovations in contemporary technological research, addressing the arduous challenge of replicating the complex sense of smell found in humans. Currently, sensor instruments find application in a variety of fields, including environmental, (bio)medical, food, pharmaceutical, and materials production. Particularly the latter, has seen a significant increase in the adoption of technological tools to assess food quality, gradually supplanting human panelists and thus reshaping the entire quality control paradigm in the sector. This process is happening even more rapidly in the world of wine, where olfactory sensory analysis has always played a central role in attributing certain qualities to a wine. In this review, conducted using sources such as PubMed, Science Direct, and Web of Science, we examined papers published between January 2015 and January 2024. The aim was to explore prevailing trends in the use of human panels and sensory tools (such as the E-nose) in the wine industry. The focus was on the evaluation of wine quality attributes by paying specific attention to geographical origin, sensory defects, and monitoring of production trends. Analyzed results show that the application of E-nose-type sensors performs satisfactorily in that trajectory. Nevertheless, the integration of this type of analysis with more classical methods, such as the trained sensory panel test and with the application of destructive instrument volatile compound (VOC) detection (e.g., gas chromatography), still seems necessary to better explore and investigate the aromatic characteristics of wines.

Electronic tongue, proton-transfer-reaction mass spectrometry, spectral analysis, and molecular docking characterization for determining the effect of α-amylase on flavor perception.

The effects of α-amylase on of flavor perception were investigated via spectrum analysis, electronic tongue, on-line mass spectrometry, and molecular docking. Aroma release results showed that α-amylase exhibited variable release patterns of different aroma compounds. Electronic tongue analysis showed that the perception of bitterness, sweetness, sour, and saltiness was subtly increased and that of umami was significantly increased (p < 0.01) along with the increasing enzyme activity of α-amylase. Ultraviolet absorption and fluorescence spectroscopy analyses showed that static quenching occurred between α-amylase and eight flavor compounds and their interaction effects were spontaneous. One binding pocket was confirmed between the α-amylase and flavor compounds, and molecular docking simulation results showed that the hydrogen, electrostatic, and hydrophobic bonds were the main force interactions. The TYP82, TRP83, LEU173, HIS80, HIS122, ASP297, ASP206, and ARG344 were the key α-amylase amino acid residues that interacted with the eight flavor compounds.

Flavor characteristics of garlic fish cakes using electronic nose and tongue analyses.

This study investigated the utility of garlic powder as a functional ingredient. The aim was to develop fish cakes with improved functionality and sensory preference based on the antioxidant activity and quality characteristics. Increasing amounts of garlic powder in the prepared fish cakes were associated with increasing total polyphenol and flavonoid contents, 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2'-azino-bis(3-ethylbenzothiazolin-6-sulfonic acid) (ABTS+) radical scavenging activity, and reducing power. Furthermore, electronic tongue and electronic nose analyses showed an increased the intensity of umami and sourness and increased the levels of volatile compounds. The lowest trimethylamine peak corresponded to the highest amount of garlic powder. Sensory evaluation indicated that 3% garlic powder had the highest score for all criteria. Fishy odor decreased as the proportion of garlic powder increased. These findings suggest that the addition of 3% garlic powder improves quality characteristics, sensory preference, and antioxidant activity of fish cakes.

Structure Optimization and Data Processing Method of Electronic Nose Bionic Chamber for Detecting Ammonia Emissions from Livestock Excrement Fermentation.

In areas where livestock are bred, there is a demand for accurate, real-time, and stable monitoring of ammonia concentration in the breeding environment. However, existing electronic nose systems have slow response times and limited detection accuracy. In this study, we introduce a novel solution: the bionic chamber construction of the electronic nose is optimized, and the sensor response data in the chamber are analyzed using an intelligent algorithm. We analyze the structure of the biomimetic chamber and the surface airflow of the sensor array to determine the sensing units of the system. The system employs an electronic nose to detect ammonia and ethanol gases in a circulating airflow within a closed box. The captured signals are processed, followed by the application of classification and regression models for data prediction. Our results suggest that the system, leveraging the biomimetic chamber, offers rapid gas detection response times. A high classification prediction accuracy, with a determination coefficient R2 value of 0.99 for single-output regression and over 0.98 for multi-output regression predictions, is achieved by incorporating a backpropagation (BP) neural network algorithm. These outcomes demonstrate the effectiveness of the electronic nose, based on an optimized bionic chamber combined with a BP neural network algorithm, in accurately detecting ammonia emitted during livestock excreta fermentation, satisfying the ammonia detection requirements of breeding farms.

VOC-based detection of prostate cancer using an electronic nose and ion mobility spectrometry: A novel urine-based approach.

BACKGROUND: Many diseases leave behind specific metabolites which can be detected from breath and urine as volatile organic compounds (VOC). Our group previously described VOC-based methods for the detection of bladder cancer and urinary tract infections. This study investigated whether prostate cancer can be diagnosed from VOCs in urine headspace. METHODS: For this pilot study, mid-stream urine samples were collected from 56 patients with histologically confirmed prostate cancer. A control group was formed with 53 healthy male volunteers matched for age who had recently undergone a negative screening by prostate-specific antigen (PSA) and digital rectal exam. Headspace measurements were performed with the electronic nose Cyranose 320TM. Statistical comparison was performed using principal component analysis, calculating Mahalanobis distance, and linear discriminant analysis. Further measurements were carried out with ion mobility spectrometry (IMS) to compare detection accuracy and to identify potential individual analytes. Bonferroni correction was applied for multiple testing. RESULTS: The electronic nose yielded a sensitivity of 77% and specificity of 62%. Mahalanobis distance was 0.964, which is indicative of limited group separation. IMS identified a total of 38 individual analytical peaks, two of which showed significant differences between groups (p < 0.05). To discriminate between tumor and controls, a decision tree with nine steps was generated. This model led to a sensitivity of 98% and specificity of 100%. CONCLUSIONS: VOC-based detection of prostate cancer seems feasible in principle. While the first results with an electronic nose show some limitations, the approach can compete with other urine-based marker systems. However, it seems less reliable than PSA testing. IMS is more accurate than the electronic nose with promising sensitivity and specificity, which warrants further research. The individual relevant metabolites identified by IMS should further be characterized using gas chromatography/mass spectrometry to facilitate potential targeted rapid testing.

Peanut origin traceability: A hybrid neural network combining an electronic nose system and a hyperspectral system.

Peanuts, sourced from various regions, exhibit noticeable differences in quality owing to the impact of their natural environments. This study proposes a fast and nondestructive detection method to identify peanut quality by combining an electronic nose system with a hyperspectral system. First, the electronic nose and hyperspectral systems are used to gather gas and spectral information from peanuts. Second, a module for extracting gas and spectral information is designed, combining the lightweight multi-head transposed attention mechanism (LMTA) and convolutional computation. The fusion of gas and spectral information is achieved through matrix combination and lightweight convolution. A hybrid neural network, named UnitFormer, is designed based on the information extraction and fusion processes. UnitFormer demonstrates an accuracy of 99.06 %, a precision of 99.12 %, and a recall of 99.05 %. In conclusion, UnitFormer effectively distinguishes quality differences among peanuts from various regions, offering an effective technological solution for quality supervision in the food market.

Impact of aroma-enhancing microorganisms on aroma attributes of industrial Douchi: An integrated analysis using E-nose, GC-IMS, GC-MS, and descriptive sensory evaluation.

In order to enhance the aromatic profile of industrial Douchi, a comprehensive investigation was undertaken to assess the impact of aroma-enhancing microorganisms on the sensory attributes of Douchi. This evaluation utilized a combination of analytical techniques, including electronic nose analysis, gas chromatography-ion mobility spectrometry (GC-IMS), gas chromatography-mass spectrometry (GC-MS), and descriptive sensory analysis (DA). Both GC-IMS and GC-MS revealed significant changes in the volatile composition of Douchi following the addition of aroma-enhancing microorganisms (p < 0.05). Partial least squares-discriminant analysis (PLS-DA) identified benzaldehyde, benzene acetaldehyde, 3-octanone, and ethyl 2-methylbutyrate as significant differentiating volatile compounds. Additionally, compared to the control group, the sensory attributes of sourness in Douchi were significantly reduced (p < 0.001), while the attributes of wine-like and sweetness were notably enhanced (p < 0.05) when the ratio of G. candidum to C. versatilis was 1:1 (GCC group). By calculating the odor-activity values (OAVs) of key volatiles, it can be hypothesized that this aroma improvement of Douchi may be attributed to an increase in the typical volatiles (3-methyl-1-butanol, 1-octen-3-ol, 3-octanol, and 3-octanone) and ethyl 2-methylbutanoate with high OAVs (2340849.64 âˆ¼ 16695327.86), as well as to decreases in the musty acetophenone. In conclusion, the aroma profile of Douchi was significantly enhanced when G. candidum and C. versatilis were added at a ratio of 1:1. This study provides valuable insights into the development of aroma enhancers for improving the sensory profile of Douchi.

Comparative Analysis of Volatile Compounds in the Flower Buds of Three Panax Species Using Fast Gas Chromatography Electronic Nose, Headspace-Gas Chromatography-Ion Mobility Spectrometry, and Headspace Solid Phase Microextraction-Gas Chromatography-Mass Spectrometry Coupled with Multivariate Statistical Analysis.

The flower buds of three Panax species (PGF: P. ginseng; PQF: P. quinquefolius; PNF: P. notoginseng) widely consumed as health tea are easily confused in market circulation. We aimed to develop a green, fast, and easy analysis strategy to distinguish PGF, PQF, and PNF. In this work, fast gas chromatography electronic nose (fast GC e-nose), headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS), and headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) were utilized to comprehensively analyze the volatile organic components (VOCs) of three flowers. Meanwhile, a principal component analysis (PCA) and heatmap were applied to distinguish the VOCs identified in PGF, PQF, and PNF. A random forest (RF) analysis was used to screen key factors affecting the discrimination. As a result, 39, 68, and 78 VOCs were identified in three flowers using fast GC e-nose, HS-GC-IMS, and HS-SPME-GC-MS. Nine VOCs were selected as potential chemical markers based on a model of RF for distinguishing these three species. Conclusively, a complete VOC analysis strategy was created to provide a methodological reference for the rapid, simple, and environmentally friendly detection and identification of food products (tea, oil, honey, etc.) and herbs with flavor characteristics and to provide a basis for further specification of their quality and base sources.

A cooperative combination of non-targeted metabolomics and electronic tongue evaluation reveals the dynamic changes in metabolites and sensory quality of radish during pickling.

Pickled radish is a traditional fermented food with a unique flavor after long-term preservation. This study analyzed the organoleptic and chemical characteristics of pickled radish from different years to investigate quality changes during pickling. The results showed that the sourness, saltiness, and aftertaste-bitterness increased after pickling, and bitterness and astringency decreased. The levels of free amino acids, soluble sugars, total phenols, and total flavonoids initially decreased during pickling but increased with prolonged pickling. The diversity of organic acids also increased over time. Through non-targeted metabolomics analysis, 349 differential metabolites causing metabolic changes were identified to affect the quality formation of pickled radish mainly through amino acid metabolism, phenylpropane biosynthesis and lipid metabolism. Correlation analysis showed that L*, soluble sugars, lactic acid, and acetic acid were strongly associated with taste quality. These findings provide a theoretical basis for standardizing and scaling up traditional pickled radish production.

Analyzing changes in volatile flavor compounds of soy protein isolate during ultrasonic-thermal synergistic treatments using electronic nose and HS-SPME-GC-MS combined with chemometrics.

The beany flavor of soy protein isolate (SPI) creates barriers to their application in food processing. This study investigated the effect of ultrasonic-thermal synergistic treatments, combined with vacuum degassing, on the removal of volatile compounds from SPI. The results revealed that ultrasonic-thermal synergistic treatments altered protein secondary structure and increased fluorescence intensity and surface hydrophobicity, which affected the flavor-binding ability of protein, resulting in reduced electronic nose sensor response values. At synergistic treatment (350 W, 120 ℃ and 150 s), the content of hexanal, (E)-2-hexenal, and 1-octen-3-ol reduced by 70.60 %, 95.60 % and 61.23 %. (E)-2-nonenal and 2-pentylfuran were not detected. Chemometric analysis indicated significant flavor differences between control and treated SPI. Furthermore, α-helix, ß-sheet, ß-turn, and surface hydrophobicity highly correlated with volatile compounds through correlation analysis, indicating that altered protein structure affected interactions with volatile compounds. The study reduced beany flavor and further expanded the range of applications of plant protein in food industry.

Noninvasive Diabetes Detection through Human Breath Using TinyML-Powered E-Nose.

Volatile organic compounds (VOCs) in exhaled human breath serve as pivotal biomarkers for disease identification and medical diagnostics. In the context of diabetes mellitus, the noninvasive detection of acetone, a primary biomarker using electronic noses (e-noses), has gained significant attention. However, employing e-noses requires pre-trained algorithms for precise diabetes detection, often requiring a computer with a programming environment to classify newly acquired data. This study focuses on the development of an embedded system integrating Tiny Machine Learning (TinyML) and an e-nose equipped with Metal Oxide Semiconductor (MOS) sensors for real-time diabetes detection. The study encompassed 44 individuals, comprising 22 healthy individuals and 22 diagnosed with various types of diabetes mellitus. Test results highlight the XGBoost Machine Learning algorithm's achievement of 95% detection accuracy. Additionally, the integration of deep learning algorithms, particularly deep neural networks (DNNs) and one-dimensional convolutional neural network (1D-CNN), yielded a detection efficacy of 94.44%. These outcomes underscore the potency of combining e-noses with TinyML in embedded systems, offering a noninvasive approach for diabetes mellitus detection.

Electronic Tongue Based on ZnO/ITO@glass for Electrochemical Monitoring of Spiciness Levels.

Capsaicin, a chemical compound present in chili peppers, is widely acknowledged as the main contributor to the spicy and hot sensations encountered during consumption. Elevated levels of capsaicin can result in meals being excessively spicy, potentially leading to health issues, such as skin burning, irritation, increased heart rate and circulation, and discomfort in the gastrointestinal system and even inducing nausea or diarrhea. The level of spiciness that individuals can tolerate may vary, so what may be considered incredibly hot for one person could be mild for another. To ensure food safety, human healthcare, regulatory compliance, and quality control in spicy food products, capsaicin levels must be measured. For these purposes, a reliable and stable sensor is required to quantify the capsaicin level. To leverage the effect of zinc oxide (ZnO), herein, we demonstrated the one-step fabrication process of an electronic tongue (E-Tongue) based on an electrochemical biosensor for the determination of capsaicin. ZnO was electrodeposited on the indium tin oxide (ITO) surface. The biosensor demonstrated the two notable linear ranges from 0.01 to 50 µM and from 50 to 500 µM with a limit of detection (LOD) of 2.1 nM. The present study also included the analysis of real samples, such as green chilis, red chili powder, and dried red chilis, to evaluate their spiciness levels. Furthermore, the E-Tongue exhibited notable degrees of sensitivity, selectivity, and long-term stability for a duration of more than a month. The development of an E-Tongue for capsaicin real-time monitoring as a point-of-care (POC) device has the potential to impact various industries and improve safety, product quality, and healthcare outcomes.

Carbamoylase-based impedimetric electronic tongue for rapid detection of paralytic shellfish toxins.

Phytotoxins produced by marine microalgae, such as paralytic shellfish toxins (PSTs), can accumulate in bivalve molluscs, representing a human health concern due to the life-threatening symptoms they cause. To avoid the commercialization of contaminated bivalves, monitoring programs were established in the EU. The purpose of this work is the implementation of a PST transforming enzyme-carbamoylase-in an impedimetric test for rapid simultaneous detection of several carbamate and N-sulfocarbamoyl PSTs. Carbamoylase hydrolyses carbamate and sulfocarbamoyl toxins, which may account for up to 90% of bivalve toxicity related to PSTs. Conformational changes of carbamoylase accompanying enzymatic reactions were probed by Fourier transform mid-infrared spectroscopy (FT-MIR) and electrochemical impedance spectroscopy (EIS). Furthermore, a combination of EIS with a metal electrode and a carbamoylase-based assay was employed to harness changes in the enzyme conformation and adsorption on the electrode surface during the enzymatic reaction as an analytical signal. After optimization of the working conditions, the developed impedimetric e-tongue could quantify N-sulfocarbamoyl toxins with a detection limit of 0.1 µM. The developed e-tongue allows the detection of these toxins at concentration levels observed in bivalves with PST toxicity close to the regulatory limit. The quantification of a sum of N-sulfocarbamoyl PSTs in naturally contaminated mussel extracts using the developed impedimetric e-tongue has been demonstrated.

Rapid purification of alkylamides from Zanthoxylum bungeanum by medium-pressure liquid chromatography and the establishment of a numbness prediction model using an electronic tongue.

In the present study, an efficient and rapid method for the preparation of high-purity typical alkylamides from Zanthoxylum bungeanum (Z. bungeanum) pericarps using medium-pressure liquid chromatography (MPLC) was developed. Under the optimized conditions using a mobile phase of methanol : water (70 : 30, v/v) at a flow rate of 25 mL min-1 and one run for 30 min, hydroxy-α-sanshool with a purity of 97.85% could be obtained. Sensory evaluation and electronic tongue analysis of the hydroxyl-α-sanshool were performed, and the aftertastes of bitterness and astringency were found to be more representative of the compounds in Chinese prickly ash that causes numbness, which has not been reported in the literature before. An electronic tongue prediction model for the evaluation of numbing intensity was established: Y = 20.452X1 - 7.594X2 - 2.876, R2 = 0.973, where Y is a sensory evaluation value based on the 15 cm linear scale method and X1 and X2 are the aftertastes from astringency and bitterness, respectively. The evaluation model can be used for the evaluation of the numbing intensity of amides of Zanthoxylum bungeanum.

Optimizing BP neural network algorithm for Pericarpium Citri Reticulatae (Chenpi) origin traceability based on computer vision and ultra-fast gas-phase electronic nose data fusion.

This study utilized computer vision to extract color and texture features of Pericarpium Citri Reticulatae (PCR). The ultra-fast gas-phase electronic nose (UF-GC-E-nose) technique successfully identified 98 volatile components, including olefins, alcohols, and esters, which significantly contribute to the flavor profile of PCR. Multivariate statistical Analysis was applied to the appearance traits of PCR, identifying 57 potential marker-trait factors (VIP > 1 and P < 0.05) from the 118 trait factors that can distinguish PCR from different origins. These factors include color, texture, and odor traits. By integrating multivariate statistical Analysis with the BP neural network algorithm, a novel artificial intelligence algorithm was developed and optimized for traceability of PCR origin. This algorithm achieved a 100% discrimination rate in differentiating PCR samples from various origins. This study offers a valuable reference and data support for developing intelligent algorithms that utilize data fusion from multiple intelligent sensory technologies to achieve rapid traceability of food origins.