Graphene Oxide, Carbon Nanotubes, and Polyelectrolytes-Based Impedanciometric E-Tongue for Estrogen Detection in Complex Matrices.

Currently, it is necessary to maintain the quality of aquifers and water bodies, which means the need for sensors that detect molecules as emerging pollutants (EPs) at low concentrations in aqueous complex solutions. In this work, an electronic tongue (e-tongue) prototype was developed to detect 17ß-estradiol in tap water. To achieve such a prototype, an array of sensors was prepared. Each sensor consists of a solid support with interdigitated electrodes without or with thin films prepared with graphene oxide, nanotubes, and other polyelectrolytes molecules adsorbed on them. To collect data from each sensor, impedance spectroscopy was used to analyze the electrical characteristics of samples of estrogen solutions with different concentrations. To analyze the collected data from the sensors, principal components analysis (PCA) method was used to create a three-dimensional plane using the calculated principal components, namely PC1 and PC2, and the estrogen concentration values. Then, damped least squares (DLS) was used to find the optimal values for the hyperplane calibration, as the sensitivity of this e-tongue was not represented by a straight line but by a surface. For the collected data, from nanotubes and graphene oxide sensors, a calibration curve for concentration given by the 10PC1×0.492-PC2×0.14-14.5 surface was achieved. This e-tongue presented a detection limit of 10-16 M of 17ß-estradiol in tap water.

Analysis of the Correlation between Persimmon Fruit-Sugar Components and Taste Traits from Germplasm Evaluation.

Persimmon fruits are brightly colored and nutritious and are fruits that contain large amounts of sugar, vitamins, mineral elements, and phenolic substances. The aim of this study was to explore the differences in fruit-sugar components of different persimmon germplasms and their relationships with phenotypic and flavor indices through the determination of phenotypes and sugar components and through electronic-tongue indices, which provided the basis and inspiration for the selection of different sugar-accumulating types of persimmon fruits and the selection of high-sugar persimmon varieties. Our results showed that persimmon germplasm fruit-sugar components were dominated by sucrose, glucose and fructose and that the remaining sugar components were more diverse but less distributed among the various germplasm types. Based on the proportion of each sugar component in the fruit, persimmon germplasms can be categorized into sucrose-accumulating and reduced-sugar-accumulation types. Sucrose-accumulating types are dominated by sucrose, galactose, fucose and inositol, while reduced-sugar-accumulation types are dominated by glucose, fructose, mannose-6-phosphate, and xylose. The content of sugar components in the germplasm persimmon of fruits of different types and maturity periods of also differed, with significant differences in sugar components between PCNA (pollination-constant non-astringent) and PCA (pollination-constant astringent) fruits. Cluster analysis classified 81 persimmon germplasms into three clusters, including cluster I-A, with low glucose and fructose content, and cluster I-B, with medium glucose, fructose, and sucrose contents. Cluster II was high in sucrose and fructose. Cluster III had high contents of glucose and fructose and low contents of sucrose and inositol.

Unleashing the Potential of ß -cyclodextrin Inclusion Complexes in Bitter Taste Abatement: Development, Optimization and Evaluation of Taste Masked Anti-emetic Chewing Gum of Promethazine Hydrochloride.

Motion sickness also known as kinetosis is a condition in which there exists a disagreement between visually perceived movement and the vestibular system's sense of movement. Nausea, vomiting, dizziness, fatigue, and headache are the most common symptoms of motion sickness. This study mainly focuses on the taste masking of Promethazine Hydrochloride (PMZ) by inclusion complexation method, its formulation development in the chewing gum form by using directly compressible gum base HIG® and its quality and performance testing. Different molar ratios (1:1, 1:2, 1:3 and 1:4) of PMZ-cyclodextrin complexes were prepared by using ß-Cyclodextrin (ß-CD) as a taste masking agent. These complexes were evaluated for FTIR, DSC, % Entrapment Efficiency, % drug yield, and taste evaluation by E-Tongue. The optimized ratio was further evaluated by sophisticated analytical techniques such as Scanning Electron Microscopy (SEM) and X-Ray Diffraction (XRD). A central composite design (CCD) (3 ^2) was utilized to examine the effects of independent variables (amount of gum-X1 and amount of plasticizer-X2) on dependent variables (%CDRY1 and hardness Y2). The prepared gums were evaluated for drug content, organoleptic properties, in-vitro dissolution testing by fabricated disintegration apparatus, texture analysis, etc. The optimization statistics showed that on decreasing the amount of gum, in- vitro drug release increases and hardness decreases. The optimized batch MCG-2 of Promethazine MCG showed 92.34 ± 0.92% of drug release, whereas for marketed formulation (Phenergan®-25 mg) drug release value was 86.19 ± 1.88%. Results provided evidence that PMZ MCGs could be a better alternative to conventional tablet formulations with improved drug release, palatability and texture.

Determination of heavy metals in edible oils by a novel voltammetry taste sensor array.

Herein, a novel voltammetry taste sensor array (VTSA) using pencil graphite electrode, screen-printed electrode, and glassy carbon electrode was used to identify heavy metals (HM) including Cad, Pb, Sn and Ni in soybean and rapeseed oils. HMs were added to edible oils at three concentrations of 0.05, 0.1 and 0.25 ppm, and then, the output of the device was classified using a chemometric classification method. According to the principal component analysis results, PG electrode explains 96% and 81% of the variance between the data in rapeseed and soybean edible oils, respectively. Additionally, the SP electrode explains 91% of the variance between the data in rapeseed and soybean oils. Moreover, the GC electrode explains 100% and 99% of the variance between the data in rapeseed and soybean edible oils, respectively. K-nearest neighbor exhibited high capability in classifying HMs in edible oils. In addition, partial least squares in the combine of VTSA shows a predict 99% in rapeseed oil. The best electrode for soybean edible oil was GC.

Performance evaluation of E-nose and E-tongue combined with machine learning for qualitative and quantitative assessment of bear bile powder.

Bear bile powder (BBP) is a valuable animal-derived product with a huge adulteration problem on market. It is a crucially important task to identify BBP and its counterfeit. Electronic sensory technologies are the inheritance and development of traditional empirical identification. Considering that each drug has its own specific odor and taste characteristics, electronic tongue (E-tongue), electronic nose (E-nose) and GC-MS were used to evaluate the aroma and taste of BBP and its common counterfeit. Two active components of BBP, namely tauroursodeoxycholic acid (TUDCA) and taurochenodeoxycholic acid (TCDCA) were measured and linked with the electronic sensory data. The results showed that bitterness was the main flavor of TUDCA in BBP, saltiness and umami were the main flavor of TCDCA. The volatiles detected by E-nose and GC-MS were mainly aldehydes, ketones, alcohols, hydrocarbons, carboxylic acids, heterocyclic, lipids, and amines, mainly earthy, musty, coffee, bitter almond, burnt, pungent odor descriptions. Four different machine learning algorithms (backpropagation neural network, support vector machine, K-nearest neighbor, and random forest) were used to identify BBP and its counterfeit, and the regression performance of these four algorithms was also evaluated. For qualitative identification, the algorithm of random forest has shown the best performance, with 100% accuracy, precision, recall and F1-score. Also, the random forest algorithm has the best R2 and the lowest RMSE in terms of quantitative prediction.

Study on the taste-masking effect and mechanism of Acesulfame K on berberine hydrochloride.

OBJECTIVE: In our previous taste-masking study, we found that Acesulfame K (AK) had a better taste-masking effect than other high-efficiency sweeteners for several representative bitter natural drugs in aqueous decoction. Furthermore, we performed a preliminary taste-masking study of AK for representative bitter API Berberine Hydrochloride (BH) and found that it had a good taste-masking effect. We also found that flocculent precipitation was generated in the BH solution, but it was not clear whether it was related to the good taste-masking effect. This study was conducted to explore the taste-masking effect and mechanism of AK on BH. METHODS: The taste-masking effect of AK on BH was evaluated based on the Traditional Human Taste Panel Method and the electronic tongue evaluation method. DSC, XRD, and molecular simulation techniques were used to explore the mechanism of AK on BH, from the macro level and molecular level, respectively. RESULTS: When evaluating the taste-masking effect, we found that 0.1% AK had the best taste-masking effect on BH, while higher concentrations had a worse taste-masking effect. DSC and XRD revealed that the flocculent precipitation was a complex AK-BH. Finally, by simulating the binding of AK, BH, and TAS2R46 receptors, we found the unique taste-masking mechanism of AK. CONCLUSION: The sweet taste stimulus of AK can mask the bitter taste stimulus of BH, and AK can generate AK-BH with BH to reduce the contact between BH and bitter taste receptors. Additionally, it could block the expression of the TAS2R46 receptors.

Effect of Sichuan Pepper (Zanthoxylum genus) Addition on Flavor Profile in Fermented Ciba Chili (Capsicum genus) Using GC-IMS Combined with E-Nose and E-Tongue.

This study examined the flavor profiles of fermented Ciba chili, comparing samples with Sichuan pepper (HJ) to those without Sichuan pepper (CK), using three analytical techniques: E-tongue, E-nose, and gas chromatography-ion mobility spectrometry (GC-IMS). The results obtained from the E-tongue and E-nose exhibited a clear difference in taste and flavor between CK and HJ. In detail, CK mainly exhibited a sour flavor profile, whereas HJ displayed an intricate and rich flavor. The HS-GC-IMS results identified a total of 60 compounds in the samples, with terpenes, alcohols, and esters being the primary volatile flavor compounds. Additionally, Zanthoxylum was found to significantly enhance the concentration of these compounds in fermented Ciba chili. Through robust principal component analysis (rPCA), 17 distinct flavor compounds were selected. Correlation analysis revealed that most terpenes exhibited positive correlations with LY2/LG, LY2/gCT1, LY2/Gct, LY2/G, LY2/Gh, and terpenes were found in higher concentrations in HJ. This study contributes a theoretical basis and provides data support for optimizing the fermentation process and elucidating the underlying mechanism of characteristic aroma formation in Ciba chili after fermentation.

Evaluation of the Chemosensoric Properties of Commercially Available Dog Foods Using Electronic Sensors and GC-MS/O Analysis.

Pet owners think of their animals as part of their family, which further promotes the growth of the pet food market, encouraging pet owners to select nutritious, palatable, and high-quality foods for pets. Therefore, the evaluation of taste and volatile compounds in pet foods is essential to improve palatability. In this study, the sensory characteristics of taste and odor compounds in 10 commercially available dry dog foods were investigated using electronic tongue (E-tongue), electronic nose (E-nose), gas chromatography-mass spectrometry (GC-MS), and gas chromatography-olfactometry (GC-O). Dry dog foods were separated based on the sensory properties of taste and volatile compounds through the multivariate analysis of integrated results of the E-tongue and E-nose. A total of 67 odor active compounds were detected through GC-MS and GC-O, and octanal, nonanal, 2-pentyl furan, heptanal, and benzaldehyde were identified as key odor compounds which may have positive effects on food intake. The multivariate analysis was used to classify samples based on key odor compounds. Volatile compounds responsible for aroma properties of samples were evaluated using GC-O and multivariate analysis in this present study for the first time. These results are expected to provide fundamental data for sensory evaluation in producing new dog foods with improved palatability.

Semi-Quantitative Discrimination of Honey Adulterated with Cane Sugar Solution by an ETongue.

This study successfully applied a potentiometric E-tongue with 20 cross-selectivity lipidic polymeric membranes in the discrimination of three semi-quantitative groups, that represented the following intervals of honey adulteration percentage with cane sugar: 0 %; [0, 10]%; [10, 20]% of adulteration. We analysed five different types of Portuguese honey; five brands of cane sugar were added to the adulterated samples; a comparative analysis was then performed. Linear discriminant analysis coupled with a tabu search algorithm for feature selection was applied to the ETongue's analytical data to select the best model. A discriminant model with 12 sensors was obtained. This model classified correctly all samples in both in internal (train data, 15 samples) and external validation (test data,10 samples). Also, multiple linear regression with tabu search was applied to verify if ETongue's data would allow quantifying the honey's adulteration level. The results showed that it was possible to obtain a quantitative model but with unsatisfactory predictive performance in the test data group (external validation), giving, in general, values below the expected concentrations. E-tongue is a real-time green, flexible and low-cost analytical tool that requires minimum sample preparation and no special technical skills, being a promising tool for everyday application.

Growth Prediction of the Total Bacterial Count in Freshly Squeezed Strawberry Juice during Cold Storage Using Electronic Nose and Electronic Tongue.

The growth models of total bacterial count in freshly squeezed strawberry juice were established by gas and taste sensors in this paper. By selecting the optimal sensors and fusing the response values, the Modified Gompertz, Logistic, Huang and Baranyi models were used to predict and simulate the growth of bacteria. The results showed that the R2 values for fitting the growth model of total bacterial count of the sensor S7 (an electronic nose sensor), of sweetness and of the principal components scores were 0.890-0.944, 0.861-0.885 and 0.954-0.964, respectively. The correlation coefficients, or R-values, between models fitted by the response values and total bacterial count ranged from 0.815 to 0.999. A single system of electronic nose (E-nose) or electronic tongue (E-tongue) sensors could be used to predict the total bacterial count in freshly squeezed strawberry juice during cold storage, while the higher rate was gained by the combination of these two systems. The fusion of E-nose and E-tongue had the best fitting-precision in predicting the total bacterial count in freshly squeezed strawberry juice during cold storage. This study proved that it was feasible to predict the growth of bacteria in freshly squeezed strawberry juice using E-nose and E-tongue sensors.

Comparative Study on Volatile Compounds and Taste Components of Different Durian Cultivars Based on GC-MS, UHPLC, HPAEC-PAD, E-Tongue and E-Nose.

In order to comprehensively evaluate the aroma-active substances and taste components of durian, solid-phase microextraction combined with gas chromatography mass spectrometry (SPME/GC-MS), high-performance anion-exchange chromatography with pulsed amperometric detection (HPAEC-PAD) and ultra-high-performance liquid chromatography (UHPLC) were used to test the key components of three popular durian cultivars. A total of 27 volatile compounds, 5 sugars, 27 organic acids and 19 free amino acids were detected in Black Thorn (BT) durian. A total of 38 volatile compounds, 4 sugars, 27 organic acids and 19 free amino acids were detected in Monthong (MT) durian. A total of 36 volatile compounds, 4 sugars, 27 organic acids and 20 free amino acids were detected in Musang King (MK) durian. Finally, the flavor differences of the three durians were evaluated using electronic nose (e-nose) and electronic tongue (e-tongue), and different cultivars were classified through principal component analysis (PCA).

Characterisation of Flavour Attributes in Egg White Protein Using HS-GC-IMS Combined with E-Nose and E-Tongue: Effect of High-Voltage Cold Plasma Treatment Time.

Egg white protein (EWP) is susceptible to denaturation and coagulation when exposed to high temperatures, adversely affecting its flavour, thereby influencing consumers' decisions. Here, we employ high-voltage cold plasma (HVCP) as a novel nonthermal technique to investigate its influence on the EWP's flavour attributes using E-nose, E-tongue, and headspace gas-chromatography-ion-mobilisation spectrometry (HS-GC-IMS) due to their rapidness and high sensitivity in identifying flavour fingerprints in foods. The EWP was investigated at 0, 60, 120, 180, 240, and 300 s of HVCP treatment time. The results revealed that HVCP significantly influences the odour and taste attributes of the EWP across all treatments, with a more significant influence at 60 and 120 s of HVCP treatment. Principal component analyses of the E-nose and E-tongue clearly distinguish the odour and taste sensors' responses. The HS-GC-IMS analysis identified 65 volatile compounds across the treatments. The volatile compounds' concentrations increased as the HVCP treatment time was increased from 0 to 300 s. The significant compounds contributing to EWP characterisation include heptanal, ethylbenzene, ethanol, acetic acid, nonanal, heptacosane, 5-octadecanal, decanal, p-xylene, and octanal. Thus, this study shows that HVCP could be utilised to modify and improve the EWP flavour attributes.

Application of Multiple-Source Data Fusion for the Discrimination of Two Botanical Origins of Magnolia Officinalis Cortex Based on E-Nose Measurements, E-Tongue Measurements, and Chemical Analysis.

Magnolia officinalis Rehd. et Wils. and Magnolia officinalis Rehd. et Wils. var. biloba Rehd. et Wils, as the legal botanical origins of Magnoliae Officinalis Cortex, are almost impossible to distinguish according to their appearance traits with respect to medicinal bark. The application of AFLP molecular markers for differentiating the two origins has not yet been successful. In this study, a combination of e-nose measurements, e-tongue measurements, and chemical analyses coupled with multiple-source data fusion was used to differentiate the two origins. Linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) were applied to compare the discrimination results. It was shown that the e-nose system presented a good discriminant ability with a low classification error for both LDA and QDA compared with e-tongue measurements and chemical analyses. In addition, the discriminating capacity of LDA for low-level fusion with original data, similar to a combined system, was superior or equal to that acquired individually with the three approaches. For mid-level fusion, the combination of different principals extracted by PCA and variables obtained on the basis of PLS-VIP exhibited an analogous discrimination ability for LDA (classification error 0.0%) and was significantly superior to QDA (classification error 1.67-3.33%). As a result, the combined e-nose, e-tongue, and chemical analysis approach proved to be a powerful tool for differentiating the two origins of Magnoliae Officinalis Cortex.

Keeping Track of Phaeodactylum tricornutum (Bacillariophyta) Culture Contamination by Potentiometric E-Tongue.

The large-scale cultivation of microalgae provides a wide spectrum of marketable bioproducts, profitably used in many fields, from the preparation of functional health products and feed supplement in aquaculture and animal husbandry to biofuels and green chemistry agents. The commercially successful algal biomass production requires effective strategies to maintain the process at desired productivity and stability levels. Hence, the development of effective early warning methods to timely indicate remedial actions and to undertake countermeasures is extremely important to avoid culture collapse and consequent economic losses. With the aim to develop an early warning method of algal contamination, the potentiometric E-tongue was applied to record the variations in the culture environments, over the whole growth process, of two unialgal cultures, Phaeodactylum tricornutum and a microalgal contaminant, along with those of their mixed culture. The E-tongue system ability to distinguish the cultures and to predict their growth stage, through the application of multivariate data analysis, was shown. A PLS regression method applied to the E-tongue output data allowed a good prediction of culture growth time, expressed as growth days, with R2 values in a range from 0.913 to 0.960 and RMSEP of 1.97-2.38 days. Moreover, the SIMCA and PLS-DA techniques were useful for cultures contamination monitoring. The constructed PLS-DA model properly discriminated 67% of cultures through the analysis of their growth media, i.e., environments, thus proving the potential of the E-tongue system for a real time monitoring of contamination in microalgal intensive cultivation.

Evaluation of Olive Oil Quality with Electrochemical Sensors and Biosensors: A Review.

Electrochemical sensors, sensor arrays and biosensors, alongside chemometric instruments, have progressed remarkably of late, being used on a wide scale in the qualitative and quantitative evaluation of olive oil. Olive oil is a natural product of significant importance, since it is a rich source of bioactive compounds with nutritional and therapeutic properties, and its quality is important both for consumers and for distributors. This review aims at analysing the progress reported in the literature regarding the use of devices based on electrochemical (bio)sensors to evaluate the bioactive compounds in olive oil. The main advantages and limitations of these approaches on construction technique, analysed compounds, calculus models, as well as results obtained, are discussed in view of estimation of future progress related to achieving a portable, practical and rapid miniature device for analysing the quality of virgin olive oil (VOO) at different stages in the manufacturing process.

Pasteurization of flavored shredded pork using Zno nanoparticles combined with radio frequency pasteurization technology.

Effects of ZnO nanoparticles combined radio frequency (ZNCRF) pasteurization on the survival of microorganism, flavor and taste of Flavored shredded pork were compared with conventional high pressure steam (HPS) sterilization. The results showed that ZNCRF pasteurization was better than HPS sterilization in terms of flavor and taste parameters and at the same time met the pasteurization requirement. GC-MS and NMR measurements were performed to explore changes in volatile compounds and status and distribution of water within the sample. The ZNCRF pasteurization when carried out for 30 min and the HPS sterilization reduced the relative contents of aldehydes by 18.8% and 19.7%, respectively, while the ZNCRF pasteurization within 20 min had less effect on aldehydes. Both ZNCRF pasteurization and HPS sterilization destroyed the vacuolar membrane of the samples caused the loss of water from the cytoplasm (T23). This work shows that ZNCRF when applied for 20 min is a mild pasteurization method that can be applied to improve the quality of Flavored shredded pork.

Emerging trends of advanced sensor based instruments for meat, poultry and fish quality- a review.

Meat and fish chemical composition and sensory attributes are markers of quality that require innovative assessment methods as existing ones are rather technical, laborious, and expensive. Emerging trends of advanced technology instruments have been lauded in the pharmaceutical, cosmetic and food industries for their high sensitivity, customizability, rapidness and affordability. Common among these, are the electronic tongue (e-tongue) and electronic nose (e-nose) but their use for meat and fish quality, remains scanty and scattered. This paper aims to systematically discuss the developing trends, principles and the recent use of e-tongue and e-nose for quality measurements in fish and meat. From over 90 research papers, it was observed that an arsenal of chemometric tools have been pivotal in applying these instruments for rapid quantitative, qualitative and predictive analysis of some physical properties, chemical properties, storability and the authentication of meat and fish. Both instruments require no reagent (waste free analytical procedure) and have been lauded for precision and*accuracy but e-nose may be better suited for meat and fish assessments. Unlike the e-tongue, e-nose requires no liquid sample preparation and portable versions are promising for rapid remote analysis of meat and fish samples that can save cost on transferring carcass to laboratories.

Collaborative Analysis on the Marked Ages of Rice Wines by Electronic Tongue and Nose based on Different Feature Data Sets.

Aroma and taste are the most important attributes of alcoholic beverages. In the study, the self-developed electronic tongue (e-tongue) and electronic nose (e-nose) were used for evaluating the marked ages of rice wines. Six types of feature data sets (e-tongue data set, e-nose data set, direct-fusion data set, weighted-fusion data set, optimized direct-fusion data set, and optimized weighted-fusion data set) were used for identifying rice wines with different wine ages. Pearson coefficient analysis and variance inflation factor (VIF) analysis were used to optimize the fusion matrixes by removing the multicollinear information. Two types of discrimination methods (principal component analysis (PCA) and locality preserving projections (LPP)) were used for classifying rice wines, and LPP performed better than PCA in the discrimination work. The best result was obtained by LPP based on the weighted-fusion data set, and all the samples could be classified clearly in the LPP plot. Therefore, the weighted-fusion data were used as independent variables of partial least squares regression, extreme learning machine, and support vector machines (LIBSVM) for evaluating wine ages, respectively. All the methods performed well with good prediction results, and LIBSVM presented the best correlation coefficient (R2 ≥ 0.9998).

Potentiometric E-Tongue System for Geosmin/Isoborneol Presence Monitoring in Drinkable Water.

A potentiometric E-tongue system based on low-selective polymeric membrane and chalcogenide-glass electrodes is employed to monitor the taste-and-odor-causing pollutants, geosmin (GE) and 2-methyl-isoborneol (MIB), in drinkable water. The developed approach may permit a low-cost monitoring of these compounds in concentrations near the odor threshold concentrations (OTCs) of 20 ng/L. The experiments demonstrate the success of the E-tongue in combination with partial least squares (PLS) regression technique for the GE/MIB concentration prediction, showing also the possibility to discriminate tap water samples containing these compounds at two concentration levels: the same OTC order from 20 to 100 ng/L and at higher concentrations from 0.25 to 10 mg/L by means of PLS-discriminant analysis (DA) method. Based on the results, developed multisensory system can be considered a promising easy-to-handle tool for express evaluation of GE/MIB species and to provide a timely detection of alarm situations in case of extreme pollution before the drinkable water is delivered to end users.

Changes in flavor of fragrant rice during storage under different conditions.

BACKGROUND: Because of its high nutritional value and good sensory properties, fragrant rice is very popular all over the world. The aroma and taste of fragrant rice play an essential role in its sensory properties. However, there has been a lack of studies on flavor changes in fragrant rice during storage. RESULTS: Hexanal, nonanal, benzaldehyde, hexadecanoic acid, and methyl ester, were identified as aroma-active compounds in fresh fragrant rice. After storage, more than 100 volatile compounds can be identified. The results indicated that, at high-temperature storage, volatile compounds such as aldehydes, ketones, and furans increased, which led to a deterioration in rice quality. Marker compounds of flavor deterioration, methyl palmitate, 2-methyl-propanoic acid, and 3-hydroxy-2,2,4-trimethylpentyl ester, were determined by principal component analysis. In addition to threonine and proline, the other 14 amino acids contributed to the taste of fragrant rice during storage. Sucrose is the only main contributor to the sweetness of Daohuaxiang 2, whereas glucose and fructose had a little sweet taste contribution during storage. The electronic nose (e-nose) and the electronic tongue (e-tongue) could distinguish samples with different storage conditions. CONCLUSION: Different storage conditions can cause flavor differences in fragrant rice. Especially under high-temperature storage, volatile compounds such as aldehydes, ketones, and furans increase, which is an important reason for the deterioration in the quality of fragrant rice during storage. © 2020 Society of Chemical Industry.