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

New evidence for gut-muscle axis: Lactic acid bacteria-induced gut microbiota regulates duck meat flavor

The interaction between gut microbiota and muscles through the gut-muscle axis has received increasing attention. This study attempted to address existing research gaps by investigating the effects of gut microbiota on meat flavor. Specifically, lactic acid bacteria were administered to ducks, and the results of e-nose and e-tongue showed significantly enhanced meat flavor in the treatment group. Further analyses using GC-MS revealed an increase in 6 characteristic volatile flavor compounds, including pentanal, hexanal, heptanal, 1-octen-3-ol, 2,3-octanedione, and 2-pentylfuran. Linoleic acid was identified as the key fatty acid that influences meat flavor. Metagenomic and transcriptomic results further confirmed that cecal microbiota affects the duck meat flavor by regulating the metabolic pathways of fatty acids and amino acids, especially ACACB was related to fatty acid biosynthesis and ACAT2, ALDH1A1 with fatty acid degradation. This study sheds light on a novel approach to improving the flavor of animal-derived food.

Unraveling proteome changes of Sunit lamb meat in different feeding regimes and its relationship to flavor analyzed by TMT-labeled quantitative proteomic

In order to explore the molecular mechanism of the effect of feeding regimes on lamb flavor, biceps femoris muscle samples from pasture-fed groups (PF) and concentrate-fed groups (CF) were chosen, and tandem mass tag (TMT) labeling combined with mass spectrometry (MS) was performed to find associations between flavor indicators and proteome profiles. The content and composition of amino acids and volatile flavor substances were better in the PF compared to the CF, with higher levels of some beneficial flavor components such as Arg, Pro Pentanal, Heptanal, Octanal, 1-octen-3-ol and 2,3-Octanedione. About 82 differentially abundant proteins (DAPs) were identified. The Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis indicated that the pathways that may be associated with lamb flavor are focused on amino acid anabolism. These results provide a basis for further understanding of the molecular mechanisms of proteins in meat flavor regulation.

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.

Review of technology advances to assess rice quality traits and consumer perception

The increase in rice consumption and demand for high-quality rice is impacted by the growth of socioeconomic status in developing countries and consumer awareness of the health benefits of rice consumption. The latter aspects drive the need for rapid, low-cost, and reliable quality assessment methods to produce high-quality rice according to consumer preference. This is important to ensure the sustainability of the rice value chain and, therefore, accelerate the rice industry toward digital agriculture. This review article focuses on the measurements of the physicochemical and sensory quality of rice, including new and emerging technology advances, particularly in the development of low-cost, non-destructive, and rapid digital sensing techniques to assess rice quality traits and consumer perceptions. In addition, the prospects for potential applications of emerging technologies (i.e., sensors, computer vision, machine learning, and artificial intelligence) to assess rice quality and consumer preferences are discussed. The integration of these technologies shows promising potential in the forthcoming to be adopted by the rice industry to assess rice quality traits and consumer preferences at a lower cost, shorter time, and more objectively compared to the traditional approaches.

Differentiation of Goat Meat Freshness Using Gas Chromatography with Ion Mobility Spectrometry

To investigate the flavor changes in goat meat upon storage, the volatile components observed in goat meat after different storage periods were determined using gas chromatography-ion mobility spectrometry (GC-IMS). A total of 38 volatile organic compounds (VOCs) were determined from the goat meat samples, including alcohols, ketones, aldehydes, esters, hydrocarbons, ethers, and amine compounds. 1-Hexanol, 3-Hydroxy-2-butanone, and Ethyl Acetate were the main volatile substances in fresh goat meat, and they rapidly decreased with increasing storage time and can be used as biomarkers for identifying fresh meat. When combined with the contents of total volatile basic-nitrogen (TVB-N) and the total numbers of bacterial colonies observed in physical and chemical experiments, the characteristic volatile components of fresh, sub-fresh, and spoiled meat were determined by principal component analysis (PCA). This method will help with the detection of fraudulent production dates in goat meat sales.

Metal-oxide-semiconductor resistive gas sensors for fish freshness detection

Fish are prone to spoilage and deterioration during processing, storage, or transportation. Therefore, there is a need for rapid and efficient techniques to detect and evaluate fish freshness during different periods or conditions. Gas sensors are increasingly important in the qualitative and quantitative evaluation of high-protein foods, including fish. Among them, metal-oxide-semiconductor resistive (MOSR) sensors with advantages such as low cost, small size, easy integration, and high sensitivity have been extensively studied in the past few years, which gradually show promising practical application prospects. Herein, we take the detection, classification, and assessment of fish freshness as the actual demand, and summarize the physical and chemical changes of fish during the spoilage process, the volatile marker gases released, and their production mechanisms. Then, we introduce the advantages, performance parameters, and working principles of gas sensors, and summarize the MOSR gas sensors aimed at detecting different kinds of volatile marker gases of fish spoiling in the last 5 years. After that, this paper reviews the research and application progress of MOSR gas sensor arrays and electronic nose technology for various odor indicators and fish freshness detection. Finally, this review points out the multifaceted challenges (sampling system, sensing module, and pattern recognition technology) faced by the rapid detection technology of fish freshness based on metal oxide gas sensors, and the potential solutions and development directions are proposed from the view of multidisciplinary intersection.

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.

Application progress of intelligent flavor sensing system in the production process of fermented foods based on the flavor properties

Fermented foods are sensitive to the production conditions because of microbial and enzymatic activities, which requires intelligent flavor sensing system (IFSS) to monitor and optimize the production process based on the flavor properties. As the simulation system of human olfaction and gustation, IFSS has been widely used in the field of food with the characteristics of nondestructive, pollution-free, and real-time detection. This paper reviews the application of IFSS in the control of fermentation, ripening, and shelf life, and the potential in the identification of quality differences and flavor-producing microbes in fermented foods. The survey found that electronic nose (tongue) is suitable to monitor fermentation process and identify food authenticity in real time based on the changes of flavor profile. Gas chromatography-ion mobility spectrometry and nuclear magnetic resonance technology can be used to analyze the flavor metabolism of fermented foods at various production stages and explore the correlation between flavor substances and microorganisms.

Analysis of Phenolic Compounds in Food by Coulometric Array Detector: A Review

Phenolic compounds are an important group of organic molecules with high radical scavenging, antimicrobial, anti-inflammatory, and antioxidant properties. The emerging interest in phenolic compounds in food products has led to the development of various analytical techniques for their detection and characterization. Among them, the coulometric array detector is a sensitive, selective, and precise method for the analysis of polyphenols. This review discusses the principle of this method and recent advances in its development, as well as trends in its application for the analysis of phenolic compounds in food products, such as fruits, cereals, beverages, herbs, and spices.

Detecting the Bitterness of Milk-Protein-Derived Peptides Using an Electronic Tongue

Bitterness is a considerable limiting factor for the application of bioactive peptides in the food industry. The objective of this study was to compare the level of bitterness of milk-protein-derived peptides using an electronic tongue (E-tongue). Liquid milk protein concentrate (LMPC) was prepared from ultra-heat-treated skimmed cow’s milk. It was initially hydrolyzed with different concentrations of trypsin, namely, 0.008 g·L−1, 0.016 g·L−1 and 0.032 g·L−1. In a later exercise, tryptic-hydrolyzed LMPC (LMPC-T) was further hydrolyzed using Lactobacillus bulgaricus and Streptococcus thermophilus. The effect of glucose in microbial hydrolysis was studied. The bitterness of peptides was evaluated with respect to quinine, a standard bittering agent. The level of bitterness of the peptides after microbial hydrolysis of LMPC-T (LMPC-T-F and LMPC-T-FG) was evaluated using a potentiometric E-tongue equipped with a sensor array that had seven chemically modified field-effect transistor sensors. The results of the measurements were evaluated using principal component analysis (PCA), and subsequently, a classification of the models was built using the linear discriminant analysis (LDA) method. The bitterness of peptides in LMPC-T-F and LMPC-T-FG was increased with the increase in the concentration of trypsin. The bitterness of peptides was reduced in LMPC-T-FG compared with LMPC-T-F. The potential application of the E-tongue using a standard model solution with quinine was shown to follow the bitterness of peptides.

Implementation of Whale Optimization for Budding Healthiness of Fishes with Preprocessing Approach

This article examines distinctive techniques for monitoring the condition of fishes in underwater and also provides tranquil procedures after catching the fishes. Once the fishes are hooked, two different techniques that are explicitly designed for smoking and drying are implemented for saving the time of fish suppliers. Existing methods do not focus on the optimization algorithms for solving this issue. When considering the optimization problem, the solution is adequate for any number of inputs at time t. For this combined new flanged technique, a precise system model has been designed and incorporated with a set of rules using contention protocols. In addition, the designed system is also instigated with a whale optimization algorithm that is having sufficient capability to test the different parameters of assimilated sensing devices using different sensors. Further to test the effectiveness of the proposed method, an online monitoring system has been presented that can monitor and in turn provides the consequences using a simulation model for better understanding. Moreover, after examining the simulation results under three different scenarios, it has been observed that the proposed method provides an enhancement in real-time monitoring systems for an average of 78%.

Handheld Devices for Food Authentication and Their Applications: A Review

This review summarises miniaturised technologies, commercially available devices, and device applications for food authentication or measurement of features that could potentially be used for authentication. We first focus on the handheld technologies and their generic characteristics: (1) technology types available, (2) their design and mode of operation, and (3) data handling and output systems. Subsequently, applications are reviewed according to commodity type for products of animal and plant origin. The 150 applications of commercial, handheld devices involve a large variety of technologies, such as various types of spectroscopy, imaging, and sensor arrays. The majority of applications, ~60%, aim at food products of plant origin. The technologies are not specifically aimed at certain commodities or product features, and no single technology can be applied for authentication of all commodities. Nevertheless, many useful applications have been developed for many food commodities. However, the use of these applications in practice is still in its infancy. This is largely because for each single application, new spectral databases need to be built and maintained. Therefore, apart from developing applications, a focus on sharing and re-use of data and calibration transfers is pivotal to remove this bottleneck and to increase the implementation of these technologies in practice.

Electronic Tongue as a Correlative Technique for Modeling Cattle Meat Quality and Classification of Breeds

Discrimination and species identification of meat has always been of paramount importance in the European meat market. This is often achieved using different conventional analytical methods but advanced sensor-based methods, such as the electronic tongue (e-tongue), are also gaining attention for rapid and reliable analysis. The aim of this study was to discriminate Angus, domestic buffalo, Hungarian Grey, Hungarian Spotted cattle, and Holstein beef meat samples from the chuck steak part of the animals, which mostly contained longissimus dorsi muscles, using e-tongue as a correlative technique with conventional methods for analysis of pH, color, texture, water activity, water-holding capacity, cooking yield, water binding activity, and descriptive sensory analysis. Analysis of variance (ANOVA) was used to determine significant differences between the measured quality traits of the five-meat species after analysis with conventional analytical methods. E-tongue data were visualized with principal component analysis (PCA) before classifying the five-meat species with linear discriminant analysis (LDA). Significant differences were observed among some of the investigated quality parameter. In most cases, Hungarian Grey was most different from the other species. Using e-tongue, separation patterns could be observed in the PCA that were confirmed with 100% recognition and 97.5% prediction of all the different meat species in LDA.

Black Soldier Fly Larvae Meal as Alternative to Fish Meal for Aquaculture Feed

Hermetia illucens meal (HIM) as ingredient in feed represents a way to achieve more sustainable food production. The aim was to characterize the chemical, microbiological and organoleptic characteristics of four diets for Sparus aurata, isoenergetic and isoproteic, containing 0%, 25%, 35% and 50% of HIM in substitution of fish meal (FM). Analyses were carried out using gas chromatography for fatty acids and amino acids, ICP-OES for minerals and liquid chromatography for aflatoxins and following International Organization for Standardization methods for microbial flora. E-sensing analysis of the diets was evaluated using an artificial sensory platform (E-eye, E-nose and E-tongue). The chemical results were submitted to a one-way ANOVA while Principal Component Analysis (PCA) of the e-sensing data was performed. No significant differences were observed for polyunsaturated fatty acids, thrombogenic and peroxidation indices among the diets. The replacement of FM with HIM increased the content of lysine, methionine, isoleucine, leucine, threonine and valine, while phosphorus, calcium and sodium content decreased (p < 0.01) as the percentage of HIM increased. Lead was significantly below the maximum level set by the EU regulation. The diets showed good hygienic and sanitary quality. The artificial senses permitted distinguishing color, odor and taste among the diets. Data allow considering Hermetia illucens as alternative protein source in fish nutrition.

E-sensing and nanoscale-sensing devices associated with data processing algorithms applied to food quality control: a systematic review

Devices of human-based senses such as e-noses, e-tongues and e-eyes can be used to analyze different compounds in several food matrices. These sensors allow the detection of one or more compounds present in complex food samples, and the responses obtained can be used for several goals when different chemometric tools are applied. In this systematic review, we used Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines, to address issues such as e-sensing with chemometric methods for food quality control (FQC). A total of 109 eligible articles were selected from PubMed, Scopus and Web of Science. Thus, we predicted that the association between e-sensing and chemometric tools is essential for FQC. Most studies have applied preliminary approaches like exploratory analysis, while the classification/regression methods have been less investigated. It is worth mentioning that non-linear methods based on artificial intelligence/machine learning, in most cases, had classification/regression performances superior to non-liner, although their applications were seen less often. Another approach that has generated promising results is the data fusion between e-sensing devices or in conjunction with other analytical techniques. Furthermore, some future trends in the application of miniaturized devices and nanoscale sensors are also discussed.

Standardized Extraction Techniques for Meat Analysis with the Electronic Tongue: A Case Study of Poultry and Red Meat Adulteration

The electronic tongue (e-tongue) is an advanced sensor-based device capable of detecting low concentration differences in solutions. It could have unparalleled advantages for meat quality control, but the challenges of standardized meat extraction methods represent a backdrop that has led to its scanty application in the meat industry. This study aimed to determine the optimal dilution level of meat extract for e-tongue evaluations and also to develop three standardized meat extraction methods. For practicality, the developed methods were applied to detect low levels of meat adulteration using beef and pork mixtures and turkey and chicken mixtures as case studies. Dilution factor of 1% w/v of liquid meat extract was determined to be the optimum for discriminating 1% w/w, 3% w/w, 5% w/w, 10% w/w, and 20% w/w chicken in turkey and pork in beef with linear discriminant analysis accuracies (LDA) of 78.13% (recognition) and 64.73% (validation). Even higher LDA accuracies of 89.62% (recognition) and 68.77% (validation) were achieved for discriminating 1% w/w, 3% w/w, 5% w/w, 10% w/w, and 20% w/w of pork in beef. Partial least square models could predict both sets of meat mixtures with good accuracies. Extraction by cooking was the best method for discriminating meat mixtures and can be applied for meat quality evaluations with the e-tongue.

Electronic Nose for Monitoring Odor Changes of Lactobacillus Species during Milk Fermentation and Rapid Selection of Probiotic Candidates

Probiotic bacteria have been associated with a unique production of aroma compounds in fermented foods but rapid methods for discriminating between foods containing probiotic, moderately probiotic, or non-probiotic bacteria remain aloof. An electronic nose (e-nose) is a high-sensitivity instrument capable of non-invasive volatile measurements of foods. In our study, we applied the e-nose to differentiate probiotic, moderately probiotic, and non-probiotic Lactobacillus bacteria strains at different fermentation time points (0th, 4th, and 11th) of milk fermentation. The pH of the changing milk medium was monitored with their corresponding increase in microbial cell counts. An e-nose with two gas chromatographic columns was used to develop classification models for the different bacteria groups and time points and to monitor the formation of the aromatic compounds during the fermentation process. Results of the e-nose showed good classification accuracy of the different bacteria groups at the 0th (74.44% for column 1 and 82.78% for column 2), the 4th (89.44% for column 1 and 92.22% for column 2), and the 11th (81.67% for column 1 and 81.67% for column 2) hour of fermentation. The loading vectors of the classification models showed the importance of some specific aroma compounds formed during the fermentation. Results show that aroma monitoring of the fermentation process with the e-nose is a promising and reliable analytical method for the rapid classification of bacteria strains according to their probiotic activity and for the monitoring of aroma changes during the fermentation process.

Advances in Electrochemical Aptasensors Based on Carbon Nanomaterials

Carbon nanomaterials offer unique opportunities for the assembling of electrochemical aptasensors due to their high electroconductivity, redox activity, compatibility with biochemical receptors and broad possibilities of functionalization and combination with other auxiliary reagents. In this review, the progress in the development of electrochemical aptasensors based on carbon nanomaterials in 2016–2020 is considered with particular emphasis on the role of carbon materials in aptamer immobilization and signal generation. The synthesis and properties of carbon nanotubes, graphene materials, carbon nitride, carbon black particles and fullerene are described and their implementation in the electrochemical biosensors are summarized. Examples of electrochemical aptasensors are classified in accordance with the content of the surface layer and signal measurement mode. In conclusion, the drawbacks and future prospects of carbon nanomaterials’ application in electrochemical aptasensors are briefly discussed.

Historical Evolution and Food Control Achievements of Near Infrared Spectroscopy, Electronic Nose, and Electronic Tongue-Critical Overview

Amid today's stringent regulations and rising consumer awareness, failing to meet quality standards often results in health and financial compromises. In the lookout for solutions, the food industry has seen a surge in high-performing systems all along the production chain. By virtue of their wide-range designs, speed, and real-time data processing, the electronic tongue (E-tongue), electronic nose (E-nose), and near infrared (NIR) spectroscopy have been at the forefront of quality control technologies. The instruments have been used to fingerprint food properties and to control food production from farm-to-fork. Coupled with advanced chemometric tools, these high-throughput yet cost-effective tools have shifted the focus away from lengthy and laborious conventional methods. This special issue paper focuses on the historical overview of the instruments and their role in food quality measurements based on defined food matrices from the Codex General Standards. The instruments have been used to detect, classify, and predict adulteration of dairy products, sweeteners, beverages, fruits and vegetables, meat, and fish products. Multiple physico-chemical and sensory parameters of these foods have also been predicted with the instruments in combination with chemometrics. Their inherent potential for speedy, affordable, and reliable measurements makes them a perfect choice for food control. The high sensitivity of the instruments can sometimes be generally challenging due to the influence of environmental conditions, but mathematical correction techniques exist to combat these challenges.

Fish Quality Index Method: Principles, weaknesses, validation, and alternatives-A review

Fish is a high nutritional value matrix of which production and consumption have been increasing in the last years. Advancements in the efficient evaluation of freshness are essential to optimize the quality assessment, to improve consumer safety, and to reduce raw material losses. Therefore, it is necessary to use rapid, nondestructive, and objective methodologies to evaluate the quality of this matrix. Quality Index Method (QIM) is a tool applied to indicate fish freshness through a sensory evaluation performed by a group of assessors. However, the use of QIM as an official method for quality assessment is limited by the protocol, sampling size, specificities of the species, storage conditions, and assessor's experience, which make this method subjective. Also, QIM may present divergences regarding the development of microorganisms and chemical analysis. In this way, novel quality evaluation methods such as electronic noses, electronic tongues, machine vision system, and colorimetric sensors have been proposed, and novel technologies such as proteomics and mitochondrial analysis have been developed. In this review, the weaknesses of QIM were exposed, and novel methodologies for quality evaluation were presented. The consolidation of these novel methodologies and their use as methods of quality assessment are an alternative to sensory methods, and their understanding enables a more effective fish quality control.

Factors Influencing the Long-Term Stability of Electronic Tongue and Application of Improved Drift Correction Methods

Temperature, memory effect, and cross-contamination are suspected to contribute to drift in electronic tongue (e-tongue) sensors, therefore drift corrections are required. This paper aimed to assess the disturbing effects on the sensor signals during measurement with an Alpha Astree e-tongue and to develop drift correction techniques. Apple juice samples were measured at different temperatures. pH change of apple juice samples was measured to assess cross-contamination. Different sequential orders of model solutions and apple juice samples were applied to evaluate the memory effect. Model solutions corresponding to basic tastes and commercial apple juice samples were measured for six consecutive weeks to model drift of the sensor signals. Result showed that temperature, cross-contamination, and memory effect influenced the sensor signals. Three drift correction methods: additive drift correction based on all samples, additive drift correction based on reference samples, and multi sensor linear correction, were developed and compared to the component correction in literature through linear discriminant analysis (LDA). LDA analysis showed all the four methods were effective in reducing sensor drift in long-term measurements but the additive correction relative to the whole sample set gave the best results. The results could be explored for long-term measurements with the e-tongue.