Application of electronic tongue for fresh foods quality evaluation: A review

From Traditional to Intelligent, A Review of Application and Progress of Sensory Analysis in Alcoholic Beverage Industry

Sensory analysis is an interdisciplinary field that combines multiple disciplines to analyze food qualitatively and quantitatively. At present, this analysis method has been widely used in product development, quality control, marketing, flavor analysis, safety supervision and inspection of alcoholic beverages. Due to the changing needs of analysis, new and more optimized methods are still emerging. Thereinto, intelligent and biometric technologies with growing attention have also been applied to sensory analysis. This work summarized the sensory analysis methods from three aspects, including traditional artificial sensory analysis, intelligent sensory technology, and innovative technologies. Meanwhile, the application sensory analysis in alcoholic beverages and its industrial production was scientifically emphasized. Moreover, the future tendency of sensory analysis in the alcoholic beverage industry is also highlights.

Deep Learning Used with a Colorimetric Sensor Array to Detect Indole for Nondestructive Monitoring of Shrimp Freshness

Intelligent colorimetric freshness indicator is a low-cost way to intuitively monitor the freshness of fresh food. A colorimetric strip sensor array was prepared by p-dimethylaminocinnamaldehyde (PDL)-doped poly(vinyl alcohol) (PVA) and chitosan (Chit) for the quantitative analysis of indole, which is an indicator of shrimp freshness. As a result of indole simulation, the array strip turned from faint yellow to pink or mulberry color with the increasing indole concentration, like a progress bar. The indicator film exhibited excellent permeability, mechanical and thermal stability, and color responsiveness to indole, which was attributed to the interactions between PDL and Chit/PVA. Furthermore, the colorimetric strip sensor array provided a good relationship between the indole concentration and the color intensity within a range of 50-350 ppb. The pathogens and spoilage bacteria of shrimp possessed the ability to produce indole, which caused the color changes of the strip sensor array. In the shrimp freshness monitoring experiment, the color-changing progress of the strip sensor array was in agreement with the simulation and could distinguish the shrimp freshness levels. The image classification system based on deep learning were developed, the accuracies of four DCNN algorithms are above 90%, with VGG16 achieving the highest accuracy at 97.89%. Consequently, a "progress bar" strip sensor array has the potential to realize nondestructive, more precise, and commercially available food freshness monitoring using simple visual inspection and intelligent equipment identification.

Application of a microfluidic electronic tongue based on impedance spectroscopy for coconut water analysis

The food industry has grown with the demands for new products and their authentication, which has not been accompanied by the area of analysis and quality control, thus requiring novel process analytical technologies for food processes. An electronic tongue (e-tongue) is a multisensor system that can characterize complex liquids in a fast and simple way. Here, we tested the efficacy of an impedimetric microfluidic e-tongue setup - comprised by four interdigitated electrodes (IDE) on a printed circuit board (PCB), with four pairs of digits each, being one bare sensor and three coated with different ultrathin nanostructured films with different electrical properties - in the analysis of fresh and industrialized coconut water. Principal Component Analysis (PCA) was applied to observe sample differences, and Partial Least Squares Regression (PLSR) was used to predict sample physicochemical parameters. Linear Discriminant Analysis (LDA) and Partial Least Square - Discriminant Analysis (PLS-DA) were compared to classify samples based on data from the e-tongue device. Results indicate the potential application of the microfluidic e-tongue in the identification of coconut water composition and determination of physicochemical attributes, allowing for classification of samples according to soluble solid content (SSC) and total titratable acidity (TTA) with over 90% accuracy. It was also demonstrated that the microfluidic setup has potential application in the food industry for quality assessment of complex liquid samples.

Characterization and discrimination of the taste and aroma of Tibetan Qingke baijiu using electronic tongue, electronic nose and gas chromatography-mass spectrometry

Consumers rely on flavor characteristics to distinguish different types of Qingke Baijiu (QKBJ). Clarifying QKBJ's traits enhances its recognition and long-term growth. Thus, this study analyzed eight QKBJ samples from different regions of Tibet (Lhasa, Sannan, Shigatse, and Qamdo) using GC-MS, electronic nose and electronic tongue. The radar charts of the electronic tongue and electronic nose revealed highly similar profiles for all eight samples. Fifteen common compounds were found in all samples, with the main alcohol compounds being 3-Methyl-1-butanol, 1-hexanol, isobutanol, 1-butanol, 1-nonanol, and phenylethyl alcohol, imparting fruity, floral, and herbal aromas. However, the Sannan samples had higher total alcohol content than total ester content, emphasizing bitterness. Lhasa1 exhibited the most prominent sweetness, Lhasa2 the most noticeable sourness, and Qamdo the most pronounced umami. Lhasa3 and Lhasa4 had total acid content second only to total ester content. Tyd had the highest alkanes, while Lhasa had most aldehydes among samples.

Integration of widely targeted metabolomics and the e-tongue reveals the chemical variation and taste quality of Yunnan Arabica coffee prepared using different primary processing methods

UPLC-Q-TOF-MS and electronic tongue analysis were applied to analyse the metabolic profile and taste quality of Yunnan Arabica coffee under seven primary processing methods. The total phenolic content ranged from 34.44 to 44.42 mg/g DW, the e-tongue results revealed the strongest umami sensor response value in the sample prepared with traditional dry processing, while the samples prepared via honey processing II had the strongest astringency sensor response value. Metabolomics analysis identified 221 differential metabolites, with higher contents of amino acids and derivatives within dry processing II sample, and increased contents of lipids and phenolic acids in the honey processing III sample. The astringency and aftertaste-astringency of the coffee samples positively correlated with the trigonelline, 3,5-di-caffeoylquinic acid and 4-caffeoylquinic acid content. The results contributed to a better understanding of how the primary processing process affects coffee quality, and supply useful information for the enrichment of coffee biochemistry theory.

The Effect of Heat Stress on Sensory Properties of Fresh Oysters: A Comprehensive Study Using E-Nose, E-Tongue, Sensory Evaluation, HS-SPME-GC-MS, LC-MS, and Transcriptomics

Heat stress has received growing concerns regarding the impact on seafood quality. However, the effects of heat stress on the sensory properties of seafood remain unknown. In this study, the sensory properties of fresh oyster (Crassostrea ariakensis) treated with chronic heat stress (30 °C) for 8 weeks were characterized using electronic nose, electronic tongue, sensory evaluation, HS-SPME-GC-MS, LC-MS and transcriptomics. Overall, chronic heat stress reduced the overall sensory properties of oysters. The metabolic network constructed. based on enrichment results of 423 differential metabolites and 166 differentially expressed genes, showed that the negative effects of chronic heat stress on the sensory properties of oysters were related to oxidative stress, protein degradation, lipid oxidation, and nucleotide metabolism. The results of the study provide valuable insights into the effects of heat stress on the sensory properties of oysters, which are important for ensuring a sustainable supply of high-quality seafood and maintaining food safety.

Novel Insights into the Effects of Different Cooking Methods on Salted Egg Yolks: Physicochemical and Sensory Analysis

In this study, the flavor characteristics and physicochemical properties of salted egg yolk (SEY) under different cooking methods (steaming/baking/microwaving) were investigated. The microwave-treated SEY exhibited the highest levels of salt content, cooking loss, lightness, and b* value, as well as the highest content of flavor amino acids. A total of 31, 27, and 29 volatile compounds were detected after steaming, baking, and microwave treatments, respectively, covering 10 chemical families. The partial least squares discriminant analysis confirmed that 21 compounds, including octanol, pyrazine, 2-pentyl-furan, and 1-octen-3-ol, were the key volatile compounds affecting the classification of SEY aroma. The electronic nose revealed a sharp distinction in the overall flavor profile of SEY with varying heat treatments. However, no dramatic differences were observed in terms of fatty acid composition. Microwave treatment was identified as presenting a promising approach for enhancing the aroma profile of SEY. These findings contribute novel insights into flavor evaluation and the development of egg products as ingredients for thermal processing.

Evaluation of a Voltametric E-Tongue Combined with Data Preprocessing for Fast and Effective Machine Learning-Based Classification of Tomato Purées by Cultivar

The potential of a voltametric E-tongue coupled with a custom data pre-processing stage to improve the performance of machine learning techniques for rapid discrimination of tomato purées between cultivars of different economic value has been investigated. To this aim, a sensor array with screen-printed carbon electrodes modified with gold nanoparticles (GNP), copper nanoparticles (CNP) and bulk gold subsequently modified with poly(3,4-ethylenedioxythiophene) (PEDOT), was developed to acquire data to be transformed by a custom pre-processing pipeline and then processed by a set of commonly used classifiers. The GNP and CNP-modified electrodes, selected based on their sensitivity to soluble monosaccharides, demonstrated good ability in discriminating samples of different cultivars. Among the different data analysis methods tested, Linear Discriminant Analysis (LDA) proved to be particularly suitable, obtaining an average F1 score of 99.26%. The pre-processing stage was beneficial in reducing the number of input features, decreasing the computational cost, i.e., the number of computing operations to be performed, of the entire method and aiding future cost-efficient hardware implementation. These findings proved that coupling the multi-sensing platform featuring properly modified sensors with the custom pre-processing method developed and LDA provided an optimal tradeoff between analytical problem solving and reliable chemical information, as well as accuracy and computational complexity. These results can be preliminary to the design of hardware solutions that could be embedded into low-cost portable devices.

Intelligent System/Equipment for Quality Deterioration Detection of Fresh Food: Recent Advances and Application

The quality of fresh foods tends to deteriorate rapidly during harvesting, storage, and transportation. Intelligent detection equipment is designed to monitor and ensure product quality in the supply chain, measure appropriate food quality parameters in real time, and thus minimize quality degradation and potential financial losses. Through various available tracking devices, consumers can obtain actionable information about fresh food products. This paper reviews the recent progress in intelligent detection equipment for sensing the quality deterioration of fresh foods, including computer vision equipment, electronic nose, smart colorimetric films, hyperspectral imaging (HSI), near-infrared spectroscopy (NIR), nuclear magnetic resonance (NMR), ultrasonic non-destructive testing, and intelligent tracing equipment. These devices offer the advantages of high speed, non-destructive operation, precision, and high sensitivity.

The effect of broad bean diet on structure, flavor and taste of fresh grass carp: A comprehensive study using E-nose, E-tongue, TPA, HS-SPME-GC-MS and LC-MS

Broad bean (Vicia faba L.) has received particular attention with regards to the improvement of flesh meat quality. However, the effect of broad bean diet on structure, flavor and taste of flesh meat is unclear. In present study, E-nose, E-tongue, TPA, HS-SPME-GC-MS, and LC-MS were used to characterize the structure, flavor and taste of grass carp (Ctenopharyngodon idellus) fed with broad bean. Overall, broad bean significantly improved the texture of grass carp muscle, but reduced the overall taste and flavor. The 50 volatile compounds were detected using HS-SPME-GC-MS. The 252 differential metabolites were identified by LC-MS, of which 107 were up-regulated and 145 were down-regulated. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis demonstrated this reduction in taste and flavor was associated with the metabolism of amino acids, lipids and nucleotides. Our findings provide a theoretical basis for improving meat quality and the functional applications of broad bean.

Inclusion of Beef Heart in Ground Beef Patties Alters Quality Characteristics and Consumer Acceptability as Assessed by the Application of Electronic Nose and Tongue Technology

Consumer purchasing of beef is often driven by the trinity of flavor, palatability, and convenience. Currently, beef patties in the United States are manufactured with fat and lean trimmings derived from skeletal muscles. A reduction in total beef supply may require the use of animal by-product utilization such as variety meats to achieve patty formulations. The current study aimed to assess textural, color, and flavor characteristics in addition to volatile compounds through electronic technology, e-nose and e-tongue, of ground beef patties formulated with beef heart. Ground beef patties were manufactured with 0%, 6%, 12%, or 18% beef heart, with the remainder of the meat block being shoulder clod-derived ground beef. Patties (n = 65/batch/treatment) within each batch (n = 3) with each treatment were randomly allocated to cooked color (n = 17/batch/treatment), Allo-Kramer shear force (AKSF; n = 17/batch/treatment), texture profile analysis (TPA; n = 6/batch/treatment), cooking loss (n = 17/batch/treatment), consumer panel (n = 3/batch/treatment), e-nose (n = 1/batch/treatment), and e-tongue (n = 1/batch/treatment) analysis groups. Patties containing beef heart did not require additional cooking time (p = 0.1325) nor exhibit greater cooking loss (p = 0.0803). Additionally, inclusion rates of beef heart increased hardness (p = 0.0030) and chewiness values (p = 0.0316) in TPA, were internally redder (p = 0.0001), and reduced overall liking by consumer panelists (p = 0.0367). Lastly, patties containing beef heart exhibited greater red-to-brown (p = 0.0003) and hue angle (p = 0.0001) values than control patties. The results suggest that beef heart inclusion does alter ground beef quality characteristics and consumer acceptability.

Discovery of peptides with saltiness-enhancing effects in enzymatic hydrolyzed Agaricus bisporus protein and evaluation of their salt-reduction property

This study aimed to screen peptides with saltiness-enhancing effects from enzymatic hydrolyzed Agaricus bisporus protein and quantify their salt-reduction. The saltiness evaluation standard curve was first established to evaluate salinity. The peptide fractions (U-1, U-2, and U-3) were obtained from enzymatic hydrolyzed Agaricus bisporus protein by ultrafiltration. Quantitative calculations showed that the U-2 fraction (200-2000 Da) had the strongest saltiness-enhancing effect, and its perceived saltiness in 50 mmol NaCl solution was 60.24 ± 0.10 mmol/L. The peptide sequences were identified by liquid chromatography/mass spectrometry (LC-MS/MS). Results suggested that the potential peptides with saltiness-enhancing effects were umami peptides. Molecular docking with the umami receptor T1R1/T1R3 revealed that the key amino acid residues were Asp82, Glu392, Glu270, and Asp269. Furthermore, peptide YDPNDPEK (976.4138 Da), DDWDEDAPR(1117.4312 Da), and DVPDGPPPE (1058.4668 Da) were synthesized for salt-reduction quantification. 0.4 % peptide YDPNDPEK in NaCl solution was found to have a salt-reduction of 30 %, which provided the basic theory and data for the salt-reduction of peptide in enzymatic hydrolyzed Agaricus bisporus protein.

Technological tools for the measurement of sensory characteristics in food: A review

The use of technological tools, in the food industry, has allowed a quick and reliable identification and measurement of the sensory characteristics of food matrices is of great importance, since they emulate the functioning of the five senses (smell, taste, sight, touch, and hearing). Therefore, industry and academia have been conducting research focused on developing and using these instruments which is evidenced in various studies that have been reported in the scientific literature. In this review, several of these technological tools are documented, such as the e-nose, e-tongue, colorimeter, artificial vision systems, and instruments that allow texture measurement (texture analyzer, electromyography, others). These allow us to carry out processes of analysis, review, and evaluation of food to determine essential characteristics such as quality, composition, maturity, authenticity, and origin. The determination of these characteristics allows the standardization of food matrices, achieving the improvement of existing foods and encouraging the development of new products that satisfy the sensory experiences of the consumer, driving growth in the food sector. However, the tools discussed have some limitations such as acquisition cost, calibration and maintenance cost, and in some cases, they are designed to work with a specific food matrix.

Effects of tandem fermentation of edible mushroom and L. plantarum on sensory, polysaccharide, vitamin C, and γ-aminobutyric acid of Rosa roxburghii Tratt and coix seed beverage

A new Rosa roxburghii Tratt (RRT) and coix seed (CS) beverage rich in multi-active ingredients was developed. Edible mushrooms and L. plantarum were selected for fermentation in stages. Some physicochemical properties, γ-aminobutyric acid (GABA), polysaccharides and sensory were studied during the T. versicolor and L. plantarum fermentation. T. versicolor increased the free amino acid through enzymatic protein digestion in the early growth stage and used these amino acids to synthesize its bacteriophage protein. T. versicolor and L. plantarum increased the polysaccharide and GABA of the fermentation broth. Vitamin C was retained as much as possible, with a slight loss occurring mainly in the aerobic fermentation stage of T. versicolor. Its less loss in exchange was for a higher value of T. versicolor polysaccharide, protein enhancement, and bitterness reduction. This study provides a reference for the deep processing of Guizhou's unique agricultural products and edible mushroom fermented beverage.

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

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

Successful combination of benchtop nuclear magnetic resonance spectroscopy and chemometric tools: A review

Low-field nuclear magnetic resonance (NMR) has three general modalities: spectroscopy, imaging, and relaxometry. In the last twelve years, the modality of spectroscopy, also known as benchtop NMR, compact NMR, or just low-field NMR, has undergone instrumental development due to new permanent magnetic materials and design. As a result, benchtop NMR has emerged as a powerful analytical tool for use in process analytical control (PAC). Nevertheless, the successful application of NMR devices as an analytical tool in several areas is intrinsically linked to its coupling with different chemometric methods. This review focuses on the evolution of benchtop NMR and chemometrics in chemical analysis, including applications in fuels, foods, pharmaceuticals, biochemicals, drugs, metabolomics, and polymers. The review also presents different low-resolution NMR methods for spectrum acquisition and chemometric techniques for calibration, classification, discrimination, data fusion, calibration transfer, multi-block and multi-way.

Juice Quality Evaluation with Multisensor Systems-A Review

E-nose and e-tongue are advanced technologies that allow for the fast and precise analysis of smells and flavours using special sensors. Both technologies are widely used, especially in the food industry, where they are implemented, e.g., for identifying ingredients and product quality, detecting contamination, and assessing their stability and shelf life. Therefore, the aim of this article is to provide a comprehensive review of the application of e-nose and e-tongue in various industries, focusing in particular on the use of these technologies in the fruit and vegetable juice industry. For this purpose, an analysis of research carried out worldwide over the last five years, concerning the possibility of using the considered multisensory systems to test the quality and taste and aroma profiles of juices is included. In addition, the review contains a brief characterization of these innovative devices through information such as their origin, mode of operation, types, advantages and disadvantages, challenges and perspectives, as well as the possibility of their applications in other industries besides the juice industry.

Off-flavor profiling of cultured salmonids using hyperspectral imaging combined with machine learning

Off-flavors can have significant impacts on the quality of salmonid products. This study investigated the possibility of comprehensive off-flavor profiling considering both olfactory and taste sensory perspectives by combining near-infrared hyperspectral imaging (NIR-HSI) and machine/deep learning. Four feature extraction algorithms were employed for the extraction and interpretation of spectral fingerprint information regarding off-flavor-related compounds. Classification models, including the partial least squares discriminant analysis, least-squares support vector machine, extreme learning machine, and one-dimensional convolutional neural network (1DCNN) were constructed using the full wavelengths and selected spectral features for the identification of off-flavor salmonids. The 1DCNN achieved the highest discrimination accuracy with full and selected wavelengths (i.e., 91.11 and 86.39 %, respectively). Furthermore, the prediction and visualization of off-flavor-related compounds were achieved with acceptable performances (R² > 0.6) for practical applications. These results indicate the potential of NIR-HSI for the off-flavor profiling of salmonid muscle samples for producers and researchers.

Characterization of selected commercially available grilled lamb shashliks based on flavor profiles using GC-MS, GC × GC-TOF-MS, GC-IMS, E-nose and E-tongue combined with chemometrics

HS-SPME-GC-MS, SPME-Arrow-GC × GC-TOF-MS, HS-GC-IMS, Electronic-nose, and Electronic-tongue systems were applied in a feasibility study of the flavor characterization of five commercially available Chinese grilled lamb shashliks. A total of 198 volatile organic compounds (VOCs) were identified (∼71% by GC × GC-TOF-MS). Using data fusion strategies, five predictive models were applied to the composition of VOCs and brand identification of the lamb shashliks. Compared with partial least squares regression, support vector machine, deep neural network, and RegBoost modeling, a momentum deep belief network model performed best in predicting VOCs content and identifying shashlik brands (R² above 0.96, and RMSE below 0.1). Intelligent sensory technology combined with chemometrics is a promising approach to the flavor characterization of shashliks and other food matrices.

Regulation of the Colour Change of 3D-Printed Mackerel Mince (Scomber scombrus) Based on Purple Potato Powder and Citric Acid

The present study evaluates the effect of purple potato (PP) powder and citric acid (CA) on the regulation of the colour change of 3D (three-dimensional) printed mackerel mince (Scomber scombrus). In addition, the effects of PP and CA content on the 3D-printability and quality of mackerel mince were also investigated. The results showed that an increase in PP and CA concentrations gradually brightened the product colour and turned it pink. Furthermore, an increase in PP concentration and added CA reduced the fluidity and loss of water in mackerel mince. Proper PP and CA concentrations moderately increased the storage modulus (G'), loss modulus (G″), and yield stress of mackerel mince, making it suitable for 3D printing. At the same time, an increase in PP and CA concentrations enhanced the umami and sweet taste of mackerel mince but reduced the fishy and sour taste, and the degree of preference was within the acceptable range, except for PP1%-CA0%. It was found that, when the 3D-printing accuracy of mackerel-mince samples reached more than 97% and was acceptable, the optimal PP and CA concentrations for realizing the regulation of L*, a*, and b* were 1.00~3.00% and 0.09~0.32%, respectively.

Flavor substances of low-valued red swamp crayfish (Procambarus clarkii) hydrolysates derived from double enzymatic systems

To make better use of low-valued crayfish (Procambarus clarkii), double enzymatic systems containing endopeptidase and Flavourzyme® were applied to investigate their effect on the physicochemical properties and volatile substances of low-valued crayfish. The results demonstrated that the double enzymatic hydrolysis had a positive effect on reduced bitterness and increased umami. Among them, the highest degree of hydrolysis (31.67 %) was obtained using trypsin and Flavourzyme® (TF), which showed 96.32 % of peptides with molecular weight < 0.5 kDa and 101.99 mg/g of free amino acids. The quality and quantity analysis showed that the types and relative contents of volatile compounds especially benzaldehyde, 1-octen-3-ol, nonanal, hexanal, 2-nonanone, 2-undecanonewere increased in the double enzymatic hydrolysis. In addition, the increase of esters and pyrazines was also found in gas chromatography-ion mobility spectrometry (GC-IMS). The results indicated that different enzymatic systems could be performed to enhance the flavor substances of low-valued crayfish. In conclusion, double enzymatic hydrolysis may be used as an advisable technique to promote the high-value utilization of low-valued crayfish and provides valuable information for the shrimp products requiring enzymatic hydrolysis.

Applications of Electronic Nose, Electronic Eye and Electronic Tongue in Quality, Safety and Shelf Life of Meat and Meat Products: A Review

The quality and shelf life of meat and meat products are key factors that are usually evaluated by complex and laborious protocols and intricate sensory methods. Devices with attractive characteristics (fast reading, portability, and relatively low operational costs) that facilitate the measurement of meat and meat products characteristics are of great value. This review aims to provide an overview of the fundamentals of electronic nose (E-nose), eye (E-eye), and tongue (E-tongue), data preprocessing, chemometrics, the application in the evaluation of quality and shelf life of meat and meat products, and advantages and disadvantages related to these electronic systems. E-nose is the most versatile technology among all three electronic systems and comprises applications to distinguish the application of different preservation methods (chilling vs. frozen, for instance), processing conditions (especially temperature and time), detect adulteration (meat from different species), and the monitoring of shelf life. Emerging applications include the detection of pathogenic microorganisms using E-nose. E-tongue is another relevant technology to determine adulteration, processing conditions, and to monitor shelf life. Finally, E-eye has been providing accurate measuring of color evaluation and grade marbling levels in fresh meat. However, advances are necessary to obtain information that are more related to industrial conditions. Advances to include industrial scenarios (cut sorting in continuous processing, for instance) are of great value.

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

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

Data fusion of electronic noses and electronic tongues aids in botanical origin identification on imbalanced Codonopsis Radix samples

Codonopsis Radix (CR) is an edible food and traditional Chinese herb medicine in China. Various varieties of Codonopsis Radix have different tastes. To make the flavor of processed food stable, two kinds of electronic sensory devices, electronic nose and electronic tongue, were used to establish a discrimination model to identify the botanical origin of each sample. The optimal model built on the 88 batches of samples was selected from the models trained with all combination of two pretreatment methods and three classification methods. A comparison were performed on the models trained on the data collected by electronic nose and electronic tongue. The results showed that the model trained on the fused dataset outperformed the models trained separately on the electronic nose data and electronic tongue data. The two preprocessing approaches could improve the prediction performance of all classification methods. Classification and Regression Tree approach performed better than Partial Least Square Discriminant Analysis and Linear Discriminant Analysis in terms of accuracy. But Classification and Regression Tree tends to assign the samples of minority class to the majority class. Meanwhile, Partial Least Square Discriminant Analysis keeps a good balance between the identification requirements of all the two groups of samples. Taking all the results above, the model built using the Partial Least Square Discriminant Analysis method on the fused data after z-score was used to identify the botanical origin of Codonopsis Radix.

Multisensory Systems Based on Perfluorosulfonic Acid Membranes Modified with Functionalized CNTs for Determination of Sulfamethoxazole and Trimethoprim in Pharmaceuticals

Sulfamethoxazole and trimethoprim are synthetic bacteriostatic drugs. A potentiometric multisensory system for the analysis of sulfamethoxazole and trimethoprim combination drugs was developed. Perfluorosulfonic acid membranes containing functionalized CNTs were used as the sensor materials. The CNTs' surface was modified by carboxyl, sulfonic acid, or (3-aminopropyl)trimethoxysilanol groups. The influence of the CNT concentration and the properties of their surface, as well as preliminary ultrasonic treatment of the polymer and CNT solution before the casting of hybrid membranes, on their ion-exchange capacity, water uptake, and transport properties was revealed. Cross-sensitivity of the sensors to the analytes was achieved due to ion exchange and hydrophobic interactions with hybrid membranes. An array of cross-sensitive sensors based on the membranes containing 1.0 wt% of CNTs with sulfonic acid or (3-aminopropyl)trimethoxysilanol groups enabled us to provide the simultaneous determination of sulfamethoxazole and trimethoprim in aqueous solutions with a concentration ranging from 1.0 × 10^-5 to 1.0 × 10^-3 M (pH 4.53-8.31). The detection limits of sulfamethoxazole and trimethoprim were 3.5 × 10^-7 and 1.3 × 10^-7 М. The relative errors of sulfamethoxazole and trimethoprim determination in the combination drug as compared with the content declared by the manufacturer were 4% (at 6% RSD) and 5% (at 7% RSD).

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.

Synergistic antibacterial mechanism of different essential oils and their effect on quality attributes of ready-to-eat pakchoi (Brassica campestris L. ssp. chinensis)

The mixture of garlic essential oil (GEO), ginger essential oil (GIEO) and litsea cubeba essential oil (LCEO) was prepared and its effect on the antibacterial activity of E. coli, S. aureus and P. aeruginosa, as well as properties of ready-to-eat pakchoi during storage were assessed. GEO, GIEO or LCEO treatment significantly enhanced the accumulation of reactive oxygen species (ROS) levels, resulting in disruption of the permeability of cell membrane, the leakage of cytoplasmic contents, and the alteration of the secondary structure of bacterial proteins. Meanwhile, GEO, GIEO or LCEO treatment repressed the key enzyme in tricarboxylic acid (TCA) and Hexose monophosphate pathway (HMP) cycle of E. coli, S. aureus and P. aeruginosa. Essential oil treatments (p < 0.05) could significantly prolong the shelf life of pakchoi, total bacterial count (TBC) values and chlorophyll content of GEO/GIEO/LCEO sample were 3.47 log cfu/g and 0.82 mg/g, respectively, after storage for 7 days. E. coli, S. aureus and P. aeruginosa counts in GEO/GIEO/LCEO samples decreased by 56.76 %, 70.10 %, 73.95 % compared to CK (no essential oil) samples. The comprehensive results from the sensory (flavor and color) and microbial analysis (especially TBC) showed that GEO/GIEO/LCEO could extend the shelf life of ready-to-eat pakchoi from 4 d to 7 d. As compared with GEO, GIEO or LCEO individually, the combination of GEO, GIEO and LCEO exhibited synergistic effect and more pronouncedly antibacterial activity to improve quality of ready-to-eat pakchoi.

Antibacterial mechanism of ultrasound combined with sodium hypochlorite and their application in pakchoi (Brassica campestris L. ssp. chinensis)

BACKGROUND

In order to prolong the storage and inhibit microorganisms of pakchoi, the antibacterial activity and mechanism of ultrasound combined with sodium hypochlorite (NaClO-US), the efficiency of NaClO-US in reducing Escherichia coli, Staphylococcus aureus and Pseudomonas aeruginosa as well as preserving quality of pakchoi were investigated.

RESULTS

Ultrasound treatment could significantly reduce the usage of NaClO solution from 800 ppm to 500 ppm. NaClO-US decreased the counts of E. coli, S. aureus and P. aeruginosa, which disrupted the bacterial cell membrane with cytoplasmic leakage. In addition, NaClO-US significantly increased cell membrane permeability, while cell membrane integrity decreased, the secondary structure of bacterial proteins showed several obvious changes, such as the increase of random coil content, as well as the decrease of α-helix content. The bacterial counts, E. coli, S. aureus and P. aeruginosa population in pakchoi treated with NaClO-US reduced by 1.89, 1.40, 1.60, 1.72 log CFU g^-1 , respectively compared to control sample after storage for 15 days. NaClO-US resulted in minimum chlorophyll depletion, flavor and sensory deterioration.

CONCLUSION

NaClO-US solution treatment inhibited microorganisms and prolonged storage of pakchoi. © 2022 Society of Chemical Industry.

Flavor Differences of Edible Parts of Grass Carp between Jingpo Lake and Commercial Market

This study investigated the flavor differences among three individual parts (abdomen, back, and tail) of Jingpo Lake grass carp (JPGC) and commercial grass carp (CGC). The growing environment and fish parts influenced the volatile compounds of the fish. The highest total contents of alcohols and ethers were found in the back of JPGC (p < 0.05). The combination of an electronic tongue and electronic nose (E-nose) could effectively distinguish the flavor differences between the different parts of JPGC and CGC by principal component analysis. Both the content of total free amino acids (FAAs) and content of amino acids contributing to the sweet and fresh flavors were higher in JPGC than CGC (p < 0.05). Among the ATP-associated products, the inosine 5’-monophosphate (IMP) contents of the back and tail of JPGC were higher (p < 0.05), but the abdomen content was lower (p > 0.05) than the respective contents in the corresponding parts of CGC. Sensory evaluation shows that JPGC had a better texture, odor, and taste, compared to CGC. Correlation analysis showed that the E-nose data and FAAs were highly correlated with the content of alcohols, aldehydes, and ethers. This study showed that the flavors of the different parts of JPGC differed significantly from those of CGC.

A Bioinspired Artificial Gustatory Neuron for a Neuromorphic Based Electronic Tongue

A novel biomimicked neuromorphic sensor for an energy efficient and highly scalable electronic tongue (E-tongue) is demonstrated with a metal-oxide-semiconductor field-effect transistor (MOSFET). By mimicking a biological gustatory neuron, the proposed E-tongue can simultaneously detect ion concentrations of chemicals on an extended gate and encode spike signals on the MOSFET, which acts as an input neuron in a spiking neural network (SNN). Such in-sensor neuromorphic functioning can reduce the energy and area consumption of the conventional E-tongue hardware. pH-sensitive and sodium-sensitive artificial gustatory neurons are implemented by using two different sensing materials: Al₂O₃ for pH sensing and sodium ionophore X for sodium ion sensing. In addition, a sensitivity control function inspired by the biological sensory neuron is demonstrated. After the unit device characterization of the artificial gustatory neuron, a fully hardware-based E-tongue that can classify two distinct liquids is demonstrated to show a practical application of the artificial gustatory neurons.

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.

Shelf-Life Prediction and Critical Value of Quality Index of Sichuan Sauerkraut Based on Kinetic Model and Principal Component Analysis

Kinetic models and accelerated shelf-life testing were employed to estimate the shelf-life of Sichuan sauerkraut. The texture, color, total acid, microbe, near-infrared analysis, volatile components, taste, and sensory evaluation of Sichuan sauerkraut stored at 25, 35, and 45 °C were determined. Principal component analysis (PCA) and Fisher discriminant analysis (FDA) were used to analyze the e-tongue data. According to the above analysis, Sichuan sauerkraut with different storage times can be divided into three types: completely acceptable period, acceptable period, and unacceptable period. The model was found to be useful to determine the critical values of various quality indicators. Furthermore, the zero-order kinetic reaction model (R², 0.8699-0.9895) was fitted better than the first-order kinetic reaction model. The Arrhenius model (E_a value was 47.23-72.09 kJ/mol, k_ref value was 1.076 × 10⁶-9.220 × 10¹⁰ d^-1) exhibited a higher fitting degree than the Eyring model. Based on the analysis of physical properties, the shelf-life of Sichuan sauerkraut was more accurately predicted by the combination of the zero-order kinetic reaction model and the Arrhenius model, while the error back propagation artificial neural network (BP-ANN) model could better predict the chemical properties. It is a better choice for dealers and consumers to judge the shelf life and edibility of food by shelf-life model.

Effect of beef tallow, phospholipid and microwave combined ultrasonic pretreatment on Maillard reaction of bovine bone enzymatic hydrolysate

The effects of beef tallow, phospholipid, microwave, and ultrasonic pretreatment (MUP) on the Maillard reaction process, the sensory characteristics of Maillard reaction products (MRPs), and the composition and content of volatile compounds were studied. Maillard reaction of the sample was more intense after MUP, but more hydrophobic amino acids were generated, resulting in relatively high sourness in MRPs. Beef tallow encapsulation has no significant effect on the sensory characteristics of MRPs. The content of volatile compounds in MRPs added with phospholipids increased significantly, and the content of sulfur compounds (especially furan and furanthiol) increased most significantly. Hexanal, Nonanal, 2-Hexylfuran, 2-Hexylthiophene, and 1-Octanol were positively correlated with the value of umami and saltiness of MRPs. The addition of phospholipids after MUP and beef tallow encapsulation helps to increase the saltiness and umami of MRPs, reduce astringency, and produce more sulfur and other flavor compounds.

Analysis of Alternative Shelf Life-Extending Protocols and Their Effect on the Preservation of Seafood Products

Seafood is essential to a healthy and varied diet due to its highly nutritious characteristics. However, seafood products are highly perishable, which results in financial losses and quality concerns for consumers and the industry. Due to changes in consumer concerns, demand for healthy products has increased. New trends focusing on reducing synthetic preservatives require innovation and the application of additional or alternative strategies to extend the shelf life of this type of product. Currently, refrigeration and freezing storage are the most common methods for fish preservation. However, refrigeration alone cannot provide long shelf-life periods for fish, and freezing worsens sensorial characteristics and consumer interest. Therefore, the need to preserve seafood for long periods without exposing it to freezing temperatures exists. This review focuses on the application of other approaches to seafood products, such as biodegradable films and coating technology; superchilling; irradiation; high-pressure processing; hyperbaric storage; and biopreservation with lactic acid bacteria, bacteriocins, or bacteriophages. The efficiency of these techniques is discussed based on their impact on microbiological quality, sensorial degradation, and overall preservation of the product’s nutritional properties. Although these techniques are already known, their use in the industrial processing of seafood is not widespread. Thus, the novelty of this review is the aggregation of recent studies on shelf life extension approaches, which provide useful information for the selection of the most appropriate technology and procedures and industrial innovation. Despite the fact that all techniques inhibit or delay bacterial proliferation and product decay, an undesirable sensory impact may occur depending on the treatment conditions. Although no technique appears to replace refrigeration, the implementation of additional treatments in the seafood processing operation could reduce the need for freezing, extending the shelf life of fresh unfrozen products.

Sensors and Instruments for Brix Measurement: A Review

Quality assessment of fruits, vegetables, or beverages involves classifying the products according to the quality traits such as, appearance, texture, flavor, sugar content. The measurement of sugar content, or Brix, as it is commonly known, is an essential part of the quality analysis of the agricultural products and alcoholic beverages. The Brix monitoring of fruit and vegetables by destructive methods includes sensory assessment involving sensory panels, instruments such as refractometer, hydrometer, and liquid chromatography. However, these techniques are manual, time-consuming, and most importantly, the fruits or vegetables are damaged during testing. On the other hand, the traditional sample-based methods involve manual sample collection of the liquid from the tank in fruit/vegetable juice making and in wineries or breweries. Labour ineffectiveness can be a significant drawback of such methods. This review presents recent developments in different destructive and nondestructive Brix measurement techniques focused on fruits, vegetables, and beverages. It is concluded that while there exist a variety of methods and instruments for Brix measurement, traits such as promptness and low cost of analysis, minimal sample preparation, and environmental friendliness are still among the prime requirements of the industry.

Toward the Development of Combined Artificial Sensing Systems for Food Quality Evaluation: A Review on the Application of Data Fusion of Electronic Noses, Electronic Tongues and Electronic Eyes

Devices known as electronic noses (ENs), electronic tongues (ETs), and electronic eyes (EEs) have been developed in recent years in the in situ study of real matrices with little or no manipulation of the sample at all. The final goal could be the evaluation of overall quality parameters such as sensory features, indicated by the "smell", "taste", and "color" of the sample under investigation or in the quantitative detection of analytes. The output of these sensing systems can be analyzed using multivariate data analysis strategies to relate specific patterns in the signals with the required information. In addition, using suitable data-fusion techniques, the combination of data collected from ETs, ENs, and EEs can provide more accurate information about the sample than any of the individual sensing devices. This review's purpose is to collect recent advances in the development of combined ET, EN, and EE systems for assessing food quality, paying particular attention to the different data-fusion strategies applied.

Detection of catechins using a fluorescent molecule and its application toward the evaluation of astringent intensity

It is possible to estimate astringent intensities of catechin solutions based on changes in the intensity of fluorescence emission.

Light-emitting diodes (below 700 nm): Improving the preservation of fresh foods during postharvest handling, storage, and transportation

In order to maintain the original taste, flavors, and appearance, fresh foods usually do not go through complex processing prior to sale; this makes them prone to deterioration due to external factors. Light-emitting diodes (LEDs) have many unique advantages over traditional preservation technologies leading to their increasing application in the food industry. This paper reviews the luminescence principles of LED, the advantages of LED compared with traditional lighting equipment, and its possible preservation mechanism, and then critically summarizes the beneficial effects of LED irradiation on the ripening and aging process of various fruits and vegetables (climacteric and non-climacteric). The activity changes of many enzymes closely related to crop development and quality maintenance, and the variation of flavor components caused by LED irradiation are discussed. LED illumination with a specific spectrum also has the important effect of maintaining the original color and flavor of meat, seafood, and dairy products. For microorganisms attached to the surface of animal-derived food, both 400-460 nm LED irradiation based on photodynamic inactivation principle and UV-LED irradiation based on ultraviolet sterilization principle have high bactericidal efficacy. Although there is still a lack of useful standards for matching optimal LED irradiation dose with wavelength, perhaps in the near future, the improved LED irradiation system will be applied extensively in the food industry.

Maillard-reacted peptides from glucosamine-induced glycation exhibit a pronounced salt taste-enhancing effect

Reducing salt intake, as one of the most cost-effective approaches, is congruent with improved population health. Grass carp skin collagen was subjected to enzymatic hydrolysis and ultrafiltration, followed by glucosamine-induced Maillard reaction to prepare Maillard-reacted peptides. Their color, free amino acid and peptide size distribution were analyzed, while UV and fluorescence spectroscopy were utilized to characterize the progress of Maillard reaction. The salt taste-enhancing effect of Maillard-reacted peptides was investigated via sensory analysis and electronic tongue. LC-MS/MS was employed to analyze the glycation sites of Maillard-reacted peptides. The results indicated that the degree of Maillard reaction was relatively low, and thermal degradation and crosslinking simultaneously occurred. Maillard-reacted peptides exhibited a significant salt taste-enhancing effect, which may be attributed to the glucosamine-induced glycation confirmed by LC-MS/MS analysis. The current study provides a theoretical basis for preparation of salt taste-enhancing peptides and their future application to reduce salt content of formulated foods.

Human-like performance umami electrochemical biosensor by utilizing co-electrodeposition of ligand binding domain T1R1-VFT and Prussian blue

Over the past decades, due to the desire for artificial umami flavors, apparatuses for detecting the umami taste have constantly been developed. Nevertheless, most information on umami is still acquired through human sensory assessment, which makes it difficult to establish an umami standard or quantify the umami flavor. In this study, the ligand binding domain called venus flytrap (VFT) domain of the umami taste receptor protein T1R1 was used as a recognition element, and an electrochemical biosensor based on a double-signal amplification strategy was constructed using single-walled carbon nanotubes (SWCNTs) and Prussian blue (PB). Moreover, the umami taste of four representative umami substances, inosine-5'-monophosphate (IMP), monosodium L-glutamate (MSG), beefy meaty peptide (BMP), and sodium succinate (WSA), were successfully quantitatively measured using differential pulse voltammetry (DPV) at an electrochemical workstation. Based on an equation (S/N = 3), the low detection limits (LODs) of IMP, MSG, BMP, and WSA were 0.1, 0.1, 0.1, and 0.01 pM, respectively. Meanwhile, a normalized signal intensity of more than 90% was kept for 4 days. The results showed that the biosensor could be used to detect umami substances with high sensitivity and selectivity, and was shown to have human-like performance. To develop the T1R1-VFT biosensor using the above-mentioned method, we utilized the ligand binding domain of the human umami receptor, rather than the entire umami receptor protein, which had a complex structure, having the following advantages: volume reduction, simplicity, and stability. This method has great potential for the detection of umami tastes, instead of using sensory evaluation, and for the development of new artificial flavorings.

Application of Artificial Intelligence in Food Industry—a Guideline

Artificial intelligence (AI) has embodied the recent technology in the food industry over the past few decades due to the rising of food demands in line with the increasing of the world population. The capability of the said intelligent systems in various tasks such as food quality determination, control tools, classification of food, and prediction purposes has intensified their demand in the food industry. Therefore, this paper reviews those diverse applications in comparing their advantages, limitations, and formulations as a guideline for selecting the most appropriate methods in enhancing future AI- and food industry–related developments. Furthermore, the integration of this system with other devices such as electronic nose, electronic tongue, computer vision system, and near infrared spectroscopy (NIR) is also emphasized, all of which will benefit both the industry players and consumers.