Monitoring of chicken meat freshness by means of a colorimetric sensor array

Optical sensor arrays for the detection and discrimination of natural products

Covering: up to the end of 2022Natural products (NPs) have found uses in medicine, food, cosmetics, materials science, environmental protection, and other fields related to our life. Their beneficial properties along with potential toxicities make the detection and discrimination of NPs crucial for their applications. Owing to the merits of low cost and simple operation, optical sensor arrays, including colorimetric and fluorometric sensor arrays, have been widely applied in the detection of small molecule NPs and discrimination of structurally similar small molecule NPs or complex mixtures of NPs. This review provides a brief introduction to the optical sensor array and focuses on its progress toward the detection and discrimination of NPs. We summarized the design principle of sensor arrays toward various NPs (i.e., saccharides and polyhydroxy compounds, organic acids, flavonoids, organic sulfur compounds, amines, amino acids, and saponins) based on their functional groups and characteristic chemical properties, along with representative examples. Moreover, the challenges and potential directions for further research of optical sensor arrays for NPs are proposed.

Machine Learning-Based Analytical Systems: Food Forensics

Despite a large amount of money being spent on both food analyses and control measures, various food-borne illnesses associated with pathogens, toxins, pesticides, adulterants, colorants, and other contaminants pose a serious threat to human health, and thus food safety draws considerable attention in the modern pace of the world. The presence of various biogenic amines in processed food have been frequently considered as the primary quality parameter in order to check food freshness and spoilage of protein-rich food. Various conventional detection methods for detecting hazardous analytes including microscopy, nucleic acid, and immunoassay-based techniques have been employed; however, recently, array-based sensing strategies are becoming popular for the development of a highly accurate and precise analytical method. Array-based sensing is majorly facilitated by the advancements in multivariate analytical techniques as well as machine learning-based approaches. These techniques allow one to solve the typical problem associated with the interpretation of the complex response patterns generated in array-based strategies. Consequently, the machine learning-based neural networks enable the fast, robust, and accurate detection of analytes using sensor arrays. Thus, for commercial applications, most of the focus has shifted toward the development of analytical methods based on electrical and chemical sensor arrays. Therefore, herein, we briefly highlight and review the recently reported array-based sensor systems supported by machine learning and multivariate analytics to monitor food safety and quality in the field of food forensics.

Fabrication of Printable Colorimetric Food Sensor Based on Hydrogel for Low-Concentration Detection of Ammonia

With the increasing market share of ready-to-cook foods, accurate determination of the food freshness and thus food safety has emerged as a concern. To commercialize and popularize food sensing technologies, food sensors with diverse functionalities, low cost, and facile use must be developed. This paper proposes printable sensors based on a hydrogel-containing pH indicator to detect ammonia gas. The sensors were composed of biocompatible polymers such as 2-hydroxyethyl methacrylate (HEMA) and [2-(methacryloyloxy)ethyl] trimethylammonium chloride (MAETC). The p(HEMA-MAETC) hydrogel sensor with bromothymol blue (BTB) demonstrated visible color change as a function of ammonia concentration during food spoilage. Furthermore, polyacrylonitrile (PAN) was added to improve transport speed of ammonium ions as the matrix in the sensors and optimized the viscosity to enable successful printing. The color changed within 3 min at ammonia concentration of 300 ppb and 1 ppm, respectively. The sensor exhibited reproducibility over 10 cycles and selective exposure to various gases generated during the food spoilage process. In an experiment involving pork spoilage, the color change was significant before and after exposure to ammonia gas within 8 h in ambient conditions. The proposed sensor can be integrated in bar codes and QR codes that are easily mass produced.

Detection of the Inoculated Fermentation Process of Apo Pickle Based on a Colorimetric Sensor Array Method

Apo pickle is a traditional Chinese fermented vegetable. However, the traditional fermentation process of Apo pickle is slow, easy to ruin, and cannot be judged with regard to time. To improve fermentation, LP-165 (L. Plantarum), which has a high salt tolerance, acidification, and growth capacity, was chosen as the starter culture. Meanwhile, a colorimetric sensor array (CSA) sensitive to pickle volatile compounds was developed to differentiate Apo pickles at varying degrees of fermentation. The color components were extracted from each dye in the color change profiles and were analyzed using principal component analysis (PCA) and linear discriminant analysis (LDA). The fermentation process of the Apo pickle was classified into four phases by LDA. The accuracy of backward substitution verification was 99% and the accuracy of cross validation was 92.7%. Furthermore, the partial least squares regression (PLSR) showed that data from the CSA were correlated with pH total acid, lactic acid, and volatile acids of the Apo pickle. These results illustrate that the CSA reacts quickly to inoculated Apo pickle and could be used to detect fermentation.

Recent Progress in Amine Gas Sensors for Food Quality Monitoring: Novel Architectures for Sensing Materials and Systems

The increasing demand for food production has necessitated the development of sensitive and reliable methods of analysis, which allow for the optimization of storage and distribution while ensuring food safety. Methods to quantify and monitor volatile and biogenic amines are key to minimizing the waste of high-protein foods and to enable the safe consumption of fresh products. Novel materials and device designs have allowed the development of portable and reliable sensors that make use of different transduction methods for amine detection and food quality monitoring. Herein, we review the past decade's advances in volatile amine sensors for food quality monitoring. First, the role of volatile and biogenic amines as a food-quality index is presented. Moreover, a comprehensive overview of the distinct amine gas sensors is provided according to the transduction method, operation strategies, and distinct materials (e.g., metal oxide semiconductors, conjugated polymers, carbon nanotubes, graphene and its derivatives, transition metal dichalcogenides, metal organic frameworks, MXenes, quantum dots, and dyes, among others) employed in each case. These include chemoresistive, fluorometric, colorimetric, and microgravimetric sensors. Emphasis is also given to sensor arrays that record the food quality fingerprints and wireless devices that operate as radiofrequency identification (RFID) tags. Finally, challenges and future opportunities on the development of new amine sensors are presented aiming to encourage further research and technological development of reliable, integrated, and remotely accessible devices for food-quality monitoring.

Biogenic Amines in Poultry Meat and Poultry Products: Formation, Appearance, and Methods of Reduction

Simple Summary

Meat consumption is on the rise, including poultry meat. With the storage of meat and the progressing process of food spoilage, the content of biogenic amines increases. Methods to prevent the formation of amines include: starter cultures, packaging methods, high hydrostatic pressure (HHP), ozonisation, radiation, use of essential oils, phytobiotics, and organic acids in food. The aim of this study was to compare the content of biogenic amines in poultry meat on the basis of the latest scientific reports and to present methods for preventing the formation of biogenic amines.The use of herbal extracts can not only reduce the occurrence of biogenic amines, but also improve production results and meat quality.

Abstract

Poultry meat is a source of many important nutrients, micro- and macro-elements, and biologically active substances. During meat storage, many physicochemical changes take place, also affecting the content of biologically active substances, including biogenic amines.They are formed as a result of three processes: decarboxylation of amino acids by microorganisms, reductive amination, and transamination of aldehydes and ketones, and as a result of activity of body tissues. Excessive consumption of biogenic amines shows toxic properties. The increasing consumption of poultry meat and the lack of established limits for biogenic amine content is a major challenge for scientists, producers, and consumer organisations, which have not yet established limits for biogenic amine content in meat (including poultry meat). Analyses of biogenic amine content in meat account for less than 10% of scientific papers, which raises the scope of the problem of limiting biogenic amines in meat. Among the methods of amine reduction are methods of destroying or reducing microorganisms’ high hydrostatic pressure (HHP), ozonisation, radiation, or the use of essential oils.

A colorimetric gas-sensitive array sensor using filter paper for the analysis of fish freshness

We developed a colorimetric array sensor using filter paper (FPCAS) to detect fish freshness. After 16 common indicators sensitive to trimethylamine, aldehydes, and sulfides were screened, they were further sensitized and dotted on filter paper to prepare FPCAS. The results revealed that FPCAS was beneficial in the later detection of fish storage. When we used FPCAS to detect the freshness of bass stored at 30 °C, total discriminant accuracy was 100%, and cross-validation accuracy was 63.5%. When detecting the freshness of bass stored at 4 °C, the total discriminant accuracy reached 100%, and cross validation accuracy was 93.3%. Therefore, FPCAS can distinguish fish freshness under commercial cold storage conditions. In addition, the indicators and filter paper used for FPCAS are low-cost. Consequently, FPCAS is a good freshness indicator of meat and fish.

A review on colorimetric indicators for monitoring product freshness in intelligent food packaging: Indicator dyes, preparation methods, and applications

Intelligent food packaging system exhibits enhanced communication function by providing dynamic product information to various stakeholders (e.g., consumers, retailers, distributors) in the supply chain. One example of intelligent packaging involves the use of colorimetric indicators, which when subjected to external stimuli (e.g., moisture, gas/vapor, electromagnetic radiation, temperature), display discernable color changes that can be correlated with real-time changes in product quality. This type of interactive packaging system allows continuous monitoring of product freshness during transportation, distribution, storage, and marketing phases. This review summarizes the colorimetric indicator technologies for intelligent packaging systems, emphasizing on the types of indicator dyes, preparation methods, applications in different food products, and future considerations. Both food and nonfood indicator materials integrated into various carriers (e.g., paper-based substrates, polymer films, electrospun fibers, and nanoparticles) with material properties optimized for specific applications are discussed, targeting perishable products, such as fresh meat and fishery products. Colorimetric indicators can supplement the traditional "Best Before" date label by providing real-time product quality information to the consumers and retailers, thereby not only ensuring product safety, but also promising in reducing food waste. Successful scale-up of these intelligent packaging technologies to the industrial level must consider issues related to regulatory approval, consumer acceptance, cost-effectiveness, and product compatibility.

Fabrication of a "progress bar" colorimetric strip sensor array by dye-mixing method as a potential food freshness indicator

Colorimetric sensing is a low-cost, intuitive method for monitoring the freshness of food. We prepared a colorimetric strip sensor array by mixing different amounts of bromophenol blue (BPB) and bromocresol green (BCG). As results of NH₃ simulation, the array strip turned from yellow to blue, and the number of blue spots increased with the increasing NH₃, like a progress bar. Although the actual color is quite different, the color-changing trend was consistent with the simulated model calculated by a computer. The progress bar results remained stable under three lighting conditions. Furthermore, in the Cod preservation experiment, the color-changing progress of the strip sensor array is consistent with the simulation and can indicate Cod freshness while providing more distinguish levels. Therefore, a "progress bar" indicator built by this strategy possess the potential of realizing nondestructive, more accurate, and commercially available food quality monitoring through the naked eye and smart equipment recognition.

Fe-Doped polydopamine nanoparticles with peroxidase-mimicking activity for the detection of hypoxanthine related to meat freshness

Rapid and accurate monitoring of food freshness to provide consumers with high-quality meat continues to be of tremendous importance to the food industry. In this report, an efficient Fe-doped polydopamine (Fe-PDA) nanozyme with peroxidase-mimicking activity was synthesized by a high-temperature hydrothermal method, and was applied to a spectrophotometric sensing system, which successfully reports the concentration of hypoxanthine (Hx) related to meat freshness. The Fe-PDA nanozyme showed excellent peroxidase simulation activity, which was primarily verified by steady-state kinetics experiments. In the presence of xanthine oxidase (XOD), Hx can react quantitatively with dissolved O₂ to generate H₂O₂, which can be further catalyzed and produce hydroxyl radicals (•OH) under acidic conditions via the Fe-PDA nanozyme and oxidize colorless TMB to blue oxTMB with absorbance at 653 nm. The absorbance at 653 nm expressed a clear linear relationship with hypoxanthine concentration in the range of 5.13-200 μM, and the detection limit was 1.54 μM. This method was further assessed by measuring the recovery of Hx added to meat samples, which showed promising accuracy. Overall, the developed Fe-PDA nanozyme with excellent peroxidase-mimicking activity is cost-effective, high-performance and easy to produce, offering an efficient and low-cost sensing system based on spectrophotometry for meat freshness determination as an alternative to conventional methods.

Fusion of a low-cost electronic nose and Fourier transform near-infrared spectroscopy for qualitative and quantitative detection of beef adulterated with duck

A low-cost electronic nose (E-nose) based on colorimetric sensors fused with Fourier transform-near-infrared (FT-NIR) spectroscopy was proposed as a rapid and convenient technique for detecting beef adulterated with duck. The total volatile basic nitrogen, protein, fat, total sugar and ash contents were measured to investigate the differences of basic properties between raw beef and duck; GC-MS was employed to analyze the difference of the volatile organic compounds emitted from these two types of meat. For variable selection and spectra denoising, the simple T-test (p < 0.05) separately intergraded with first derivative, second derivative, centralization, standard normal variate transform, and multivariate scattering correction were performed and the results compared. Extreme learning machine models were built to identify the adulterated beef and predict the adulteration levels. Results showed that for recognizing the independent samples of raw beef, beef-duck mixtures, and raw duck, FT-NIR offered a 100% identification rate, which was superior to the E-nose (83.33%) created herein. In terms of predicting adulteration levels, the root means square error (RMSE) and the correlation coefficient (r) for independent meat samples using FT-NIR were 0.511% and 0.913, respectively. At the same time, for E-nose, these two indicators were 1.28% and 0.841, respectively. When the E-nose and FT-NIR data were fused, the RMSE decreased to 0.166%, and the r improved to 0.972. All the results indicated that fusion of the low-cost E-nose and FT-NIR could be employed for rapid and convenient testing of beef adulterated with duck.

Weight and volume estimation of poultry and products based on computer vision systems: a review

The appearance, size, and weight of poultry meat and eggs are essential for production economics and vital in the poultry sector. These external characteristics influence their market price and consumers' preference and choice. With technological developments, there is an increase in the application and importance of vision systems in the agricultural sector. Computer vision has become a promising tool in the real-time automation of poultry weighing and processing systems. Owing to its noninvasive and nonintrusive nature and its capacity to present a wide range of information, computer vision systems can be applied in the size, mass, volume determination, and sorting and grading of poultry products. This review article gives a detailed summary of the current advances in measuring poultry products' external characteristics based on computer vision systems. An overview of computer vision systems is discussed and summarized. A comprehensive presentation of the application of computer vision-based systems for assessing poultry meat and eggs was provided, that is, weight and volume estimation, sorting, and classification. Finally, the challenges and potential future trends in size, weight, and volume estimation of poultry products are reported.

Smart edible films based on mucilage of lallemantia iberica seed incorporated with curcumin for freshness monitoring

The objective of the present work was first to develop a smart packaging system based on Lallemantia iberica seed gum (LISG)/curcumin and, subsequently, investigate its physicochemical characteristics and biological activity. Finally, the response of LISG/curcumin films against pH change and the spoilage of shrimp were tested. The barrier properties and mechanical performance of the films improved as the curcumin concentration increased. FT-IR analysis revealed the formation of physical interaction between LISG and curcumin. LISG/curcumin films showed a continuous and steady release of curcumin. The incorporation of curcumin into LISG matrix imparts antioxidant and antibacterial/mold activity to the films. A strong positive correlation was observed between total volatile base nitrogen (TVBN) content of shrimp and a* (redness) during storage time (Pearson correlation = 0.975). Eventually, LISG/curcumin film could be a promising smart packaging system capable of detecting food spoilage.

A novel near-infrared fluorescent probe based on isophorone for the bioassay of endogenous cysteine

A dicyanoisophorone/acrylate-combined probe (DDP) was synthesized and designed as a near-infrared (NIR) fluorescent sensor for the rapid identification of Cys over Hcy and GSH in aqueous solution with a large Stokes shift (143 nm). The detection limit of Cys was 1.23 μM, which was lower than that of the intracellular Cys concentration. DDP was cell membrane-permeable and had been successfully applied to the detection of intracellular Cys in HeLa cells. The detection mechanism was determined by ¹H NMR titration, MS and DFT calculations.

A critical review on intelligent and active packaging in the food industry: Research and development

The emergence of many new food products on the market with need of consumers to constantly monitor their quality until consuming, in addition to the necessity for reducing food corruption during preservation time, have led to the development of some modern packaging technologies such as intelligent packaging (IP) and active packaging (AP). The benefits of IP are detecting defects, quality monitoring and tracking the packaged food products to control the storage conditions from the production stage to the consumption stage by using various sensors and indicators such as time-temperature indicators (TTIs), gas indicators, humidity sensors, optical, calorimetric and electrochemical biosensors. While, AP helps to increase the shelf-life of products by using absorbing and diffusion systems for various materials like carbon dioxide, oxygen, and ethanol. However, there are some important issues over these emerging technologies including cost, marketability, consumer acceptance, safety and organoleptic quality of the food and emphatically environmental safety concerns. Therefore, future researches should be conducted to solve these problems and to prompt applications of IP and AP in the food industry. This paper reviews the latest innovations in these advanced packaging technologies and their applications in food industry. The IP systems namely indicators, barcoding techniques, radio frequency identification systems, sensors and biosensor are reviewed and then the latest innovations in AP methods including scavengers, diffusion systems and antimicrobial packaging are reviewed in detail.

Risk Mitigation in a Meat Supply Chain with Options of Redirection

The aim of this paper is to present how a higher income can be achieved by developing a broader and more accurate planning framework and control perishability from stable to fork if it is possible to redirect the shipments in the case of increasing perishability dynamics or longer time delays on the roads. It also gives the answer to the question of how such a Supply Chain (SC) can be evaluated using Net Present Value (NPV) approach. The procedures include a real-time calculation and communication about the remaining shelf life (RSL) during transportation and other logistic manipulations from one chain node to another if the time to exceed the contractually stipulated Customer Remaining Shelf Life (CRSL) is distributed by known distribution. Planning and control on the skeleton of the extended material requirements planning (MRP) model are advised, where time delays and their impact on the CRSL can be easily calculated. The changes in the NPV at contractually stipulated CRSL are calculated dynamically in real-time. Smart devices, tracking temperature, humidity, and gas concentration enable such reports immediately after detecting a high probability that CRSL, as stipulated in a contract, will not be achieved, based on the known parameters of the exponential distribution of the remaining shelf life as a time to failure at each node of the graph. The model includes possibilities to deliver the meat to the local market or to the reverse logistics plants in the nodes of the remaining route, if the expected contractually stipulated CRSL becomes too high. On this way, shortening unnecessary routes further contributes to less pollution.

Ionic-liquid doped polymeric composite as passive colorimetric sensor for meat freshness as a use case

A composite membrane containing 1,2-naphthoquinone-4-sulfonic acid sodium salt (NQS) embedded in an ionic liquid (IL)- polydimethylsiloxane (PDMS)- tetraethyl orthosilicate (TEOS)- SiO₂ nanoparticles (NPs) polymeric matrix is proposed. The selected IL was 1-methyl-3-octylimidazolium hexafluorophosphate (OMIM PF6). It is demonstrated that ILs chemical additives of PDMS influenced the sol-gel porosity. The sensor analytical performance for ammonia atmospheres has been tested as a function of sampling time (between 0.5 and 312 h), temperature (25 °C and 4 °C) and sampling volume (between 2L and 22 mL) by means of diffuse reflectance measurements and sensor photos, which can be registered and saved as images by a smartphone, which permit RGB measurements too. Flexible calibration was possible, adapting it to the sampling time, temperature and sampling volume needed for its application. Calibration linear slopes (mA vs ppmv) between 1.7 and 467 ppmv^-1 were obtained for ammonia in function of the several studied conditions. Those slopes were between 48 and 91% higher than those achieved with sensors without ILs. The practical application of this sensing device was demonstrated for the analysis of meat packaging environments, being a potential cost-effective candidate for in situ meat freshness analysis. NQS provided selectivity in reference to other family compounds emitted from meat products, such as sulphides. After 10 days at 4 °C ammonia liberated by the assayed meat was 20 ± 4 μg/kg and 18 ± 3 μg/kg, quantified by using diffuse reflectance and %R measurements, respectively. Homogeneity of the ammonia atmosphere was tested by using two sensors placed in two different positions inside the packages.

Vitamin B6 cofactors guided highly selective fluorescent turn-on sensing of histamine using beta-cyclodextrin stabilized ZnO quantum dots

Histamine, one of the most important biogenic amines (BAs) is considered as food hazard and therefore various agencies have fixed threshold in different food and beverages. In this manuscript, two novel fluorescent turn-on probes were developed for the instantaneous detection of histamine. The β-cyclodextrin (β-CD) capped ZnO quantum dots (QDs) were decorated with the vitamin B₆ cofactors like pyridoxal 5'-phosphate (PLP) and pyridoxal (Py) by forming host-guest inclusion complexation between the capped β-CD and PLP/Py. The cofactors decorated QDs (ZnO@PLP and ZnO@Py) were applied for the sensing of BAs. Addition of histamine to the ZnO@PLP and ZnO@Py solution resulted selective fluorescence enhancement at 473 nm and 460 nm, respectively. Without any interference from the other tested BAs, the fluorescence response of the probes ZnO@PLP and ZnO@Py showed good linearity to histidine concentration from 2.49 to 24.4 μM and 7.44 to 47.6 μM with the detection limit down to 0.59 μM and 0.97 μM, respectively.

Aheto J, Zhang D, Feng F. Detection of Beef Adulterated with Pork Using a Low-Cost Electronic Nose Based on Colorimetric Sensors

The present study was aimed at developing a low-cost but rapid technique for qualitative and quantitative detection of beef adulterated with pork. An electronic nose based on colorimetric sensors was proposed. The fresh beef rib steaks and streaky pork were purchased and used from the local agricultural market in Suzhou, China. The minced beef was mixed with pork ranging at levels from 0%~100% by weight at increments of 20%. Protein, fat, and ash content were measured for validation of the differences between the pure beef and pork used in basic chemical compositions. Fisher linear discriminant analysis (Fisher LDA) and extreme learning machine (ELM) were utilized comparatively for identification of the ground pure beef, beef–pork mixtures, and pure pork. Back propagation-artificial neural network (BP-ANN) models were built for prediction of the adulteration levels. Results revealed that the ELM model built was superior to the Fisher LDA model with higher identification rates of 91.27% and 87.5% in the training and prediction sets respectively. Regarding the adulteration level prediction, the correlation coefficient and the root mean square error were 0.85 and 0.147 respectively in the prediction set of the BP-ANN model built. This suggests, from all the results, that the low-cost electronic nose based on colorimetric sensors coupled with chemometrics has a great potential in rapid detection of beef adulterated with pork.

Overview of the Evolution of Silica-Based Chromo-Fluorogenic Nanosensors

This review includes examples of silica-based, chromo-fluorogenic nanosensors with the aim of illustrating the evolution of the discipline in recent decades through relevant research developed in our group. Examples have been grouped according to the sensing strategies. A clear evolution from simply functionalized materials to new protocols involving molecular gates and the use of highly selective biomolecules such as antibodies and oligonucleotides is reported. Some final examples related to the evolution of chromogenic arrays and the possible use of nanoparticles to communicate with other nanoparticles or cells are also included. A total of 64 articles have been summarized, highlighting different sensing mechanisms.

Development a smart edible nanocomposite based on mucilage of Melissa officinalis seed/montmorillonite (MMT)/curcumin

The aim of the present study was, first to fabricate Melissa officinalis seed gum (MOSG)-based films incorporated with montmorillonite (MMT) at various concentrations and subsequently, evaluate of the physicochemical properties of the developed films. Afterward, the anti-bacterial and anti-mold activities of the developed nanocomposites were assessed. Finally, curcumin was incorporated into formulation of the fabricated film at optimal condition to sense pH changes. Incorporating MMT nanoparticles into MOSG-based films could reduce the thickness, water solubility and moisture content of the samples. Tensile strength (TS) and elongation at break (EB) values significantly increased with increase of MMT concentration. The nanoparticle addition specifically at higher levels resulted in increase of agglomeration. Neither anti-mold and nor anti-microbial activity were observed for the tested nanocomposites. The films containing curcumin had good antibacterial and anti-mold activities and can be used as smart package due to their ability to sense the pH change.

Meat quality evaluation based on computer vision technique: A review

Nowadays people tend to include more meat in their diet thanks to the improvement in standards of living as well as an increase in awareness of meat nutritive values. To ensure public health, therefore, there is a need for a rise in worldwide meat production and consumption. Further attention is also required as to how the safety and the quality of meat production process should be assessed. Classical methods of meat quality assessment, however, have some disadvantages; expensive and time-consuming. This study intends to introduce an alternative method known as Computer Vision (CV) for the assessment of various quality parameters of muscle foods. CV has several advantages over the traditional methods. It is non-destructive, easy, and quick, hence, more efficient in meat quality assessments. This study aims to investigate different quality characteristics of some muscle foods using CV. It closes with a discussion on the future challenges and expected opportunities of the practical application of CV in the meat industry.

Non-destructive characterization of egg odor and fertilization status by SPME/GC-MS coupled with electronic nose

BACKGROUND

Early and non-destructive identification of fertile (F) eggs is a difficult task in the process of breeding laying hens. The odors emitted from unfertilized (UF), infertile (IF), and fertile (F) eggs were characterized by solid-phase microextraction / gas chromatograph-mass spectrometry (SPME/GC-MS) and electronic nose (E-nose) to determine their differences by principal component, partial least squares, and canonical discriminant analyses.

RESULTS

A total of 14 volatiles were identified in unhatched shell white Leghorn eggs, such as nonanal, decanal, 6-methyl-5-hepten-2-one, and 6,10-dimethyl-5,9-undecadien-2-one. Cedrene and decanal contributed greatly to the classification of UF and fertilized (Fd)/IF eggs; cedrene, decanal, 1-octanol and hexanal contributed greatly to the distinction between UF and IF eggs; heptanal might be the potential marker to determine F/IF eggs. P40/1, P10/2, P10/1, TA/2, T40/2 and T30/1, P30/1, P40/2, PA/2, T40/2 mostly contributed to the distinction between UF and Fd eggs and between F and IF eggs, respectively. Canonical discriminant analysis presented superior differentiating efficiency for almost all groups, and the odor differences between UF and Fd eggs were significantly larger than the differences between F and IF eggs.

CONCLUSION

Solid-phase microextraction / gas chromatograph-mass spectrometer combined with E-nose may have the potential to non-destructively distinguish UF, F, and IF eggs, which will provide a new perspective to understand the differences among them. © 2018 Society of Chemical Industry.

Prediction of the Biogenic Amines Index of Poultry Meat Using an Electronic Nose

The biogenic amines index of fresh chicken meat samples during refrigerated storage was predicted based on the headspace analysis using an electronic nose equipped with an array of electrochemical sensors. The reference biogenic amines index values were obtained using dispersive liquid–liquid microextraction–gas chromatography–mass spectrometry. A prototype electronic nose with modular construction and a dedicated sample chamber was used to rapidly analyze the volatile fraction of chicken meat samples, with a single measurement time of five minutes. Back-propagation artificial neural network was used to estimate the biogenic amines index of the samples with a determination coefficient of 0.954 based on ten-fold stratified cross-validation. The results indicate that the determination of the biogenic amines index is a good reference method for studies in which the freshness of meat products is assessed based on headspace analysis and fingerprinting, and that the described electronic device can be used to assess poultry meat freshness based on this value with high accuracy.

Chemosensors for biogenic amines and biothiols

There is burgeoning interest among supramolecular chemists to develop novel molecular systems to detect biogenic amines and bio-thiols in aqueous and non-aqueous media due to their potential role in biological processes. Biogenic amines are biologically important targets because of their involvement in the energy metabolism of human biological systems and their requirement is met through food and nutrition. However, the increasing instances of serious health problems due to food toxicity have raised the quality of food nowadays. Biogenic amines have been frequently considered as the markers or primary quality parameters of foods like antioxidant properties, freshness and spoilage. For instance, these amines such as spermine, spermidine, cadavarine, etc. may originate during microbial decarboxylation of amino acids of fermented foods/beverages. These amines may also react with nitrite available in certain meat products and concomitantly produce carcinogenic nitrosamine compounds. On the other hand, it is also well established that biothiols, particularly, thiol amino acids, provide the basic characteristics to food including flavor, color and texture that determine its acceptability. For instance, the reduction of thiol groups produces hydrogen sulfide which reduces flavour as in rotten eggs and spoiled fish, and the presence of hydrogen sulfide in fish is indicative of spoilage. Thus, biogenic amines and bio-thiols have attracted the profound interest of researchers as analytical tools for their quantification. Much scientific and technological information is issued every year, where the establishment of precise interactions of biogenic amines and bio-thiols with other molecules is sought in aqueous and non-aqueous media. This review summarizes the optical chemosensors developed for the selective detection of biogenic amines and bio-thiols.

Development of a Textile Nanocomposite as Naked Eye Indicator of the Exposition to Strong Acids

Chemical burns, mainly produced by acids, are a topic of concern. A new sensing material for the detection of strong acids able to be incorporated into textiles has been developed. The material is prepared by the covalent attachment of 2,2',4,4',4″-pentamethoxy triphenyl methanol to a mesoporous material which further is included in a nitro resin to obtain a colourless composite. The response of this composite to diverse acid solutions was tested showing the appearance of an intense purple colour (with a colour difference higher than 160) that can be monitored by the naked eye or could be easily digitised to feed an instrumental sensor. Reversibility and resistance to washing cycles were studied with positive results. Finally, the response of the sensing composite to acid vapours was assayed, observing a colour change similar to that found in solution.

Comparison of different chemometric methods in quantifying total volatile basic-nitrogen (TVB-N) content in chicken meat using a fabricated colorimetric sensor array

PSO-SVMR is an efficient chemometric tool to quantify TVB-N content in chicken.

A ratiometric fluorescent probe for detection of biogenic primary amines with nanomolar sensitivity

An ultrasensitive ratiometric fluorescent sensor made of an N,N-dimethylaminonaphthalene anhydride moiety for detection of aliphatic primary amines is reported.

Colorimetric detection of hazardous gases using a remotely operated capturing and processing system

This paper presents an electronic system for the automatic detection of hazardous gases. The proposed system implements colorimetric sensing algorithms, thus providing a low-cost solution to the problem of gas sensing. It is remotely operated and it performs the tasks of image capturing and processing, hence obtaining colour measurements in RGB (Red-Green-Blue) space that are subsequently sent to a remote operator via the internet. A prototype of the system has been built to test its performance. Specifically, experiments have been carried out aimed at the detection of CO, CO2, NO, NO2, SO2 and formaldehyde at diverse concentrations by using a chromogenic array composed by 13 active and 2 inert compounds. Statistical analyses of the results reveal a good performance of the electronic system and the feasibility of remote hazardous gas detection using colorimetric sensor arrays.

Polymer - Nanoparticle Assemblies for Array Based Sensing

Sensing clinically relevant biomolecules is crucial for the detection and prevention of disease. Currently used detection methods tend to be expensive, time intensive, and specific for only one particular biomolecule of interest. Nanoparticle-based arrays using conjugated polymers have emerged as an analytical and potential clinical tool, allowing detection of a wide range of biomolecules using selective, not specific, sensor components. In this report, we highlight recent progress in nanoparticle - polymer sensor arrays in both the fundamental understanding of how the sensor arrays function as well as the detection of clinically relevant bacteria and cells.

Use of plastic-based analytical device, smartphone and chemometric tools to discriminate amines

Amine-based volatile compounds released by microorganisms offer an alternative diagnostic approach for the identification of foodborne pathogens.