Portable Optoelectronic Nose for Monitoring Meat Freshness

Smartphone-based detection and discrimination of amine vapors by a single dye-adsorbed material

Smartphone-assisted analysis has become widely utilized for detecting various species in recent years. In such studies, multiple dyes should be employed to ensure selectivity and analyte discrimination. In our research, we have demonstrated the capability of a specially synthesized dye to selectively detect and discriminate liquid amine vapors. The developed material employs meso-toluene-α,β,α',β'-tetrabromoBODIPY immobilized on a thin-layer chromatography plate, exhibiting structure-specific color changes in response to amine vapors. The hue values of these colors, observed under both ambient and UV light, enable discrimination even among closely related amine structures. A mobile application has also been developed for the rapid interpretation of test results.

Extrusion Printing of Surface-Functionalized Metal-Organic Framework Inks for a High-Performance Wearable Volatile Organic Compound Sensor

Wearable sensors hold immense potential for real-time and non-destructive sensing of volatile organic compounds (VOCs), requiring both efficient sensing performance and robust mechanical properties. However, conventional colorimetric sensor arrays, acting as artificial olfactory systems for highly selective VOC profiling, often fail to meet these requirements simultaneously. Here, a high-performance wearable sensor array for VOC visual detection is proposed by extrusion printing of hybrid inks containing surface-functionalized sensing materials. Surface-modified hydrophobic polydimethylsiloxane (PDMS) improves the humidity resistance and VOC sensitivity of PDMS-coated dye/metal-organic frameworks (MOFs) composites. It also enhances their dispersion within liquid PDMS matrix, thereby promoting the hybrid liquid as high-quality extrusion-printing inks. The inks enable direct and precise printing on diverse substrates, forming a uniform and high particle-loading (70 wt%) film. The printed film on a flexible PDMS substrate demonstrates satisfactory flexibility and stretchability while retaining excellent sensing performance from dye/MOFs@PDMS particles. Further, the printed sensor array exhibits enhanced sensitivity to sub-ppm VOC levels, remarkable resistance to high relative humidity (RH) of 90%, and the differentiation ability for eight distinct VOCs. Finally, the wearable sensor proves practical by in situ monitoring of wheat scab-related VOC biomarkers. This study presents a versatile strategy for designing effective wearable gas sensors with widespread applications.

Transparent, flexible, and eco-friendly starch-based films for reversible optoelectronic noses for food spoilage monitoring in smart packaging

A reversible optoelectronic nose is presented consisting of ten acid-base indicators incorporated into a starch-based film, covering a wide pH range. The starch substrate is odorless, biocompatible, flexible, and exhibits high tensile resistance. This optical artificial olfaction system was used to detect the early stages of food decomposition by exposing it to the volatile compounds produced during the spoialge process of three food products (beef, chicken, and pork). A smartphone was used to capture the color changes caused by intermolecular interactions between each dye and the emitted volatiles over time. Digital images were processed to generate a differential color map, which uses the observed color shifts to create a unique signature for each food product. To effectively discriminate among different samples and exposure times, we employed chemometric tools, including hierarchical cluster analysis (HCA) and principal component analysis (PCA). This approach detects food deterioration in a practical, cost-effective, and user-friendly manner, making it suitable for smart packaging. Additionally, the use of starch-based films in the food industry is preferable due to their biocompatibility and biodegradability characteristics.

Packaged europium/fluorescein-based hydrogen bond organic framework as ratiometric fluorescent probe for visual real-time monitoring of seafood freshness

The freshness of sea food has always been the focus of attention from consumers, and food-safety issues are in urgent need of efficient approaches. A HOF-based ratiometric fluorescence probe (HOF-FITC/Eu) featuring superior amine-response, offers the real-time and visual detection of seafood freshness. Via intermolecular hydrogen bond interaction to form hydrogen-bonded organic frameworks (HOFs), which serve as a structural basis for the conjugate loading of pH-sensitive fluorescein (5-FITC) and coordination doping of lanthanide Eu3+. Amine vapors stimulate the dual-wavelength (525 nm and 616 nm) characteristic fluorescence of HOF-FITC/Eu with an inverse trend, resulting in an increase of the ratio of I525 to I616 accompanied by a distinct color transition from red to green. Prepared HOF-FITC/Eu featuring sensitive red-green color change characteristics of amine response are readily dripped into composite films of filter paper through integrated smartphone and 254 nm UV lamp as mobile observation devices to on-site monitor the freshness of raw fish and shrimp samples. The intelligent food probe HOF-FITC/Eu opens a novel material assembly type for fluorescence sensing and a potential pathway for other functional materials in the field of investigational food.

Machine Learning-Assisted Portable Microplasma Optical Emission Spectrometer for Food Safety Monitoring

To meet the needs of food safety for simple, rapid, and low-cost analytical methods, a portable device based on a point discharge microplasma optical emission spectrometer (μPD-OES) was combined with machine learning to enable on-site food freshness evaluation and detection of adulteration. The device was integrated with two modular injection units (i.e., headspace solid-phase microextraction and headspace purge) for the examination of various samples. Aromas from meat and coffee were first introduced to the portable device. The aroma molecules were excited to specific atomic and molecular fragments at excited states by room temperature and atmospheric pressure microplasma due to their different atoms and molecular structures. Subsequently, different aromatic molecules obtained their own specific molecular and atomic emission spectra. With the help of machine learning, the portable device was successfully applied to the assessment of meat freshness with accuracies of 96.0, 98.7, and 94.7% for beef, pork, and chicken meat, respectively, through optical emission patterns of the aroma at different storage times. Furthermore, the developed procedures can identify beef samples containing different amounts of duck meat with an accuracy of 99.5% and classify two coffee species without errors, demonstrating the great potential of their application in the discrimination of food adulteration. The combination of machine learning and μPD-OES provides a simple, portable, and cost-effective strategy for food aroma analysis, potentially addressing field monitoring of food safety.

Four levels of in-sensor computing in bionic olfaction: from discrete components to multi-modal integrations

Sensing and computing are two important ways in which humans attempt to perceive and understand the analog world through digital devices. Analog-to-digital converters (ADCs) discretize analog signals while the data bus transmits digital data between the components of a computer. With the increase in sensor nodes and the application of deep neural networks, the energy and time consumption limit the increment of data throughput. In-sensor computing is a computing paradigm that integrates sensing, storage, and processing in one device without ADCs and data transfer. According to the integration degree, herein, we summarize four levels of in-sensor computing in the field of artificial olfactory. In the first level, we show that different functions are conducted by using discrete components. Next, the data conversion and transfer are exempt within the in-memory computing architecture with necessary data encoding. Subsequently, in-sensor computing is integrated into a single device. Finally, multi-modal in-sensor computing is proposed to improve the quality and reliability of the classification results. At the end of this minireview, we provide an outlook on the use of metal nanoparticle devices to achieve such in-sensor computing for bionic olfaction.

Miniaturized wireless sensor enables real-time monitoring of food spoilage

Food spoilage results in food waste and food-borne diseases. Yet, standard laboratory tests to determine spoilage (mainly volatile biogenic amines) are not performed regularly by supply chain personnel or end customers. Here we developed a poly(styrene-co-maleic anhydride)-based, miniature (2 × 2 cm²) sensor for on-demand spoilage analysis via mobile phones. To demonstrate a real-life application, the wireless sensor was embedded into packaged chicken and beef; consecutive readings from meat samples using the sensor under various storage conditions enabled the monitoring of spoilage. While samples stored at room temperature showed an almost 700% change in sensor response on the third day, those stored in the freezer resulted in an insignificant change in sensor output. The proposed low-cost, miniature wireless sensor nodes can be integrated into packaged foods, helping consumers and suppliers detect spoilage of protein-rich foods on demand, and ultimately preventing food waste and food-borne diseases.

Cyanostilbene-based fluorescent paper array for monitoring fish and meat freshness via amino content detection

The detection of biogenic amines released from degraded meats is an effective method for evaluating meat freshness. However, existing traditional methods like titration are deemed tedious, while the use of sophisticated analytical instruments is not amenable to field testing. Herein, a cyanostilbene-based fluorescent array was rapidly fabricated using macroarray synthesis on a cellulose paper surface to detect amines liberated from spoiled beef, fish, and chicken. The fluorescence changes of immobilized molecules from the interaction with gaseous amines were used to monitor changes in freshness levels. Thanks to the high-throughput nature of macroarray synthesis, a set of highly responsive molecules such as pyridinium and dicyanovinyl moieties were quickly revealed. Importantly, this method offers flexibility in sensing applications including (1) sensing by individual sensor molecules, where the fluorescence response correlated well with established titration methods, and (2) collective sensing whereby chemometric analysis was used to provide a cutoff of freshness with 73-100% accuracy depending on meat types. Overall, this study paves the way for a robust and cost-effective tool for monitoring meat freshness.

Machine learning methods for the detection of explosives, drugs and precursor chemicals gathered using a colorimetric sniffer sensor

Colorimetric sensing technology for the detection of explosives, drugs, and their precursor chemicals is an important and effective approach. In this work, we use various machine learning models to detect these substances from colorimetric sensing experiments conducted in controlled environments. The detection experiments based on the response of a colorimetric chip containing 26 chemo-responsive dyes indicate that homemade explosives (HMEs) such as hexamethylene triperoxide diamine (HMTD), triacetone triperoxide (TATP), and methyl ethyl ketone peroxide (MEKP) used in improvised explosives devices are detected with true positive rate (TPR) of 70-75%, 73-90% and 60-82% respectively. Time series classifiers such as Convolutional Neural Networks (CNN) are explored, and the results indicate that improvements can be achieved with the use of kinetics of the chemical responses. The use of CNNs is limited, however, to scenarios where a large number of measurements, typically in the range of a few hundred, of each analyte are available. Feature selection of important dyes using the Group Lasso (GPLASSO) algorithm indicated that certain dyes are more important in discrimination of an analyte from ambient air. This information could be used for optimizing the colorimetric sensor and extend the detection to more analytes.

Threshold-Responsive Colorimetric Sensing System for the Continuous Monitoring of Gases

Colorimetric sensors are widely used because of their inherent advantages including accuracy, rapid response, ease-of-use, and low costs; however, they usually lack reusability, which precludes the continuous use of a single sensor. We have developed a threshold-responsive colorimetric system that enables repeated analyte measurements by a single colorimetric sensor. The threshold responsive algorithm automatically adjusts the sensor exposure time to the analyte and measurement frequency according to the sensor response. The system registers the colorimetric sensor signal change rate, prevents the colorimetric sensor from reaching saturation, and allows the sensor to fully regenerate before the next measurement is started. The system also addresses issues common to colorimetric sensors, including the response time and range of detection. We demonstrate the benefits and feasibility of this novel system, using colorimetric sensors for ammonia and carbon dioxide gases for continuous monitoring of up to (at least) 60 detection cycles without signs of analytical performance degradation of the sensors.

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.

Food Freshness Measurements and Product Distinguishing by a Portable Electronic Nose Based on Organic Field-Effect Transistors

Determination of food freshness, which is the most ancient role of the human sense of smell, is still a challenge for compact and inexpensive electronic nose devices. Fast, sensitive, and reusable sensors are long-awaited in the food industry to replace slow, labor-intensive, and expensive bacteriological methods. In this work, we present microbiological verification of a novel approach to food quality monitoring and spoilage detection using an electronic nose based on organic field-effect transistors (OFETs) and its application for distinguishing products. The compact device presented is able to detect spoilage-related gases as early as at the 4 × 10⁴ CFU g^-1 bacteria count level, which is 2 orders of magnitude below the safe consumption threshold. Cross-selective sensor array based on OFETs with metalloporphyrin receptors were made on a single substrate using solution processing leading to a low production cost. Moreover, machine learning methods applied to the sensor array response allowed us to compare spoilage profiles and separate them by the type of food: pork, chicken, fish, or milk. The approach presented can be used to monitor food spoilage and distinguish different products with an affordable and portable device.

Visual-Olfactory Synergistic Perception Based on Dual-Focus Imaging and a Bionic Learning Architecture

The synergistic interaction of vision and olfaction is critical for both natural and artificial intelligence systems to recognize and adapt to complex environments. However, current bioinspired systems with visual and olfactory sensations are mostly assembled with separate and heterogeneous sensors, inevitably leading to bulky systems and incompatible datasets. Here, we demonstrate on-chip integration of visual and olfactory sensations through a dual-focus imaging approach. By combining lens-based visual imaging and lensless colorimetric imaging, a target object and its odor fingerprint can be captured with a single complementary metal-oxide-semiconductor imager, and the obtained multimodal images are analyzed with a bionic learning architecture for information fusion and perception. To demonstrate the capability of this system, we adapted it to food detection and achieved 100% accuracy in identifying meat freshness and category with a 10 s sampling time. In addition to the highly integrated sensor design, our approach exhibits superior accuracy and efficiency in object recognition, providing a promising approach for robotic sensing and perception.

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.

Application of intelligent packaging for meat products: A systematic review

BACKGROUND

Today, in response to consumer demand and market trends, the development of new packaging with better performance such as intelligent packaging has become more important. This packaging system is able to perform intelligent functions to increase shelf life, increase safety and improve product quality.

OBJECTIVES

Recently, various types of packaging systems are available for meat products, especially cooked, fresh and processed meats. But because meat products are very perishable, monitoring their quality and safety in the supply chain is very important. This systematic article briefly reviews some of the recent data about the application of intelligent packaging in meat products.

METHODS

The search was conducted in Google Scholar, Science Direct, Elsevier, Springer, Scopus, and PubMed, from April 1996 to April 2021 using a different combination of the following keyword: intelligent packaging, and meat.

RESULTS

The results showed that the intelligent packaging presents several benefits compared to traditional packaging (e.g., antimicrobial, antioxidant, and shelf life extension) at the industrial processing level. Thus, these systems have been applied to improve the shelf life and textural properties of meat and meat products.

CONCLUSIONS

It is necessary to control the number of intelligent compounds that are included in the packaging as they clearly influence the quality and nutritional properties as well as the final cost of the food products.

Bibliometric Review on the Volatile Organic Compounds in Meat

Meat flavor is an important aspect of meat quality that also influences consumer demand, and is therefore very important for the meat industry. Volatile organic compounds (VOCs) contribute in large part to the flavor of meat, and while increasing numbers of articles are published on this topic, reviews of these articles are very scarce. Therefore, our aim was to perform a bibliometric analysis of the scientific publications on VOCs in meat over the period 2000-2020. We selected 611 scientific sources from the Scopus database related to VOCs in meat (seafood excluded). The bibliometric information retrieved included journals, authors, countries, institutions, keywords, and citations. From this analysis, we drew up a list of the most important journals, authors, countries, and institutions, and the trends in VOC research on meat. We conducted a social network analysis (SNA) to identify the collaborations among the many authors and countries, and a keyword analysis to generate a network map of the authors' keywords. We also determined which meat species were most frequently chosen as research subjects, traced the evolution of the various methods/instruments used, and explored the research tendencies. Finally, we point out the need for further research in defining meat quality, improving meat flavor, identifying adulterants, and certifying the authenticity of meat.

A non-porous Fe(II) complex for the colorimetric detection of hazardous gases and the monitoring of meat freshness

Food quality monitoring and freshness assessment are critical for ensuring food safety at a large scale. Ammonia is used as an important indicator of protein rich food spoilage state. However, current ammonia gas sensors suffer from insufficient sensitivity and selectivity, or sophisticated instrumentation, hindering their practical application in in-situ and real-time food quality monitoring. To overcome such limitations, an innovative nonporous colorimetric complex 1 has been synthesized and investigated for the detection of NH_3(g) and its volatile organic derivatives including aliphatic amines, 1,2-diaminopropane_(g), isobutylamine_(g) and ethylenediamine_(g), etc. The sensor operates colorimetrically at room temperature without energy input, with a detection limit to ammonia_(g) of 105 ppb, and show excellent reusability. The colorimetric detection mechanism involves a partial spin state change of Fe(II) ions upon exposure to amines in the gas phase. In addition, the complex was utilized as real-time monitoring of meat freshness using a smartphone. Thus, chemosensor 1 is considered as a ground breaking new-generation portable electronic nose for vapors of volatile organic compounds discrimination at room temperature.

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.

A novel colorimetric sensor array for real-time and on-site monitoring of meat freshness

Food quality control is essential in industry and daily life. In this work, we developed a novel colorimetric sensor array composed of several pH-sensitive dyes for monitoring meat freshness. A color change in the sensor array was seen after exposure to volatile organic compounds (VOCs), and the images were captured for precise quantification of the VOCs. In conjunction with pattern recognition, meat freshness at different storage periods was readily discerned, revealing that the as-fabricated colorimetric sensor array possessed excellent discrimination ability. The linear range for quantitative analysis of volatiles related to meat spoilage was from 5 ppm to 100 ppm, with a limit of detection at the ppb level (S/N = 3). Furthermore, the testing results obtained by the sensor in assessing meat freshness were validated by a standard method for measuring the total volatile basic nitrogen (TVB-N). The sensing signals showed good agreement with the results obtained in TVB-N when measuring real food samples. The sensor also displayed good reproducibility (RSD < 5%) and long-term stability. The sensor was successfully used for on-site and real-time determination of volatiles emitted from rotting meat, demonstrating its potential application in monitoring the quality and safety of meat products.

Hydrophobic and Rapid-Response Sensor Inks: Array-Based Fingerprinting of Perfumes

Counterfeited perfumes mixed with inexpensive additives for commercial purposes pose a great threat to cosmetic market competition and human health. Herein, a 24-element, solid-state colorimetric sensor array employing chemo-responsive dye inks for accurate discrimination of a variety of fragrance bases and "sniffing out" real perfumes from adulterated samples was first reported. The physiochemical robustness and gas response kinetics of the sensor array were optimized with the streamlined design of the channel geometry and hydrophobic modification of the sensor substrate. A unique and distinguishable color change profile was obtained within 2 min exposure of diluted vapor that enabled clear fingerprinting of chemically similar perfume samples. Four commercial perfume products were successfully distinguished and categorized according to their similarity to relevant perfume bases using chemometric methods including hierarchical clustering and principal component analysis. The sensor array also allows the discrimination of ethanol-diluted fragrance bases from the pristine sample, revealing its potential for quality assurance of perfumes and other cosmetics. Such easy-to-use, disposable, and miniaturized chemical sensing detectors therefore prove exceptionally valuable for fast analysis of luxuries such as perfumes and other industrial products with complex chemical compositions.

Rapid Assessment of Meat Freshness by the Differential Sensing of Organic Sulfides Emitted during Spoilage

In this work, we report the fabrication of a two-member fluorescence sensor array that enables the assessment of three stages (fresh, slightly spoiled, and moderately or severely spoiled) of meat spoilage. The first member of the array, which has strong chalcogen bonding and sulfur-π interactions with organic sulfides, exhibits very high sensitivity, while the second member of the array, which has weak chalcogen bonding and sulfur-π interactions with organic sulfides, exhibits lower sensitivity. On the basis of the combined fluorescence responses of the two members, three stages of meat spoilage, including fresh, slightly spoiled, and moderately or severely spoiled, can be monitored. Notably, using the volatiles collected from 5 g of meat products over a short period of time (1 min), this two-member sensor array achieves sensitive responses to the organic sulfides emitted from the meats. The capacity of this method to rapidly assess meat freshness facilitates its practical application, as illustrated by the monitoring of the freshness of chicken and pork products in the real world.

Sensors for Volatile Organic Compounds

This paper provides an overview of recent developments in the field of volatile organic compound (VOC) sensors, which are finding uses in healthcare, safety, environmental monitoring, food and agriculture, oil industry, and other fields. It starts by briefly explaining the basics of VOC sensing and reviewing the currently available and quickly progressing VOC sensing approaches. It then discusses the main trends in materials' design with special attention to nanostructuring and nanohybridization. Emerging sensing materials and strategies are highlighted and their involvement in the different types of sensing technologies is discussed, including optical, electrical, and gravimetric sensors. The review also provides detailed discussions about the main limitations of the field and offers potential solutions. The status of the field and suggestions of promising directions for future development are summarized.

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.

Metallic Effects on p-Hydroxyphenyl Porphyrin Thin-Film-Based Planar Optical Waveguide Gas Sensor: Experimental and Computational Studies

Metal effects on the gas sensing behavior of metal complexes of 5,10,15,20-tetrakis(4-hydroxyphenyl)porphyrin (THPP) thin film was investigated in terms of detecting NO₂ gas by the planar optical waveguide. For this purpose, several THPP and metal complexes were synthesized with different central metal ions: Co(II), Ni(II), Cu(II), and Zn(II). Planar optical gas sensors were fabricated with the metalloporphyrins deposited on K⁺ ion-exchanged soda-lime glass substrate with the spin coating method serving as host matrices for gas interaction. All of the THPP complex’s films were fully characterized by UV-Vis, IR and XPS spectroscopy, and the laser light source wavelength was selected at 520 and 670 nm. The results of the planar optical waveguide sensor show that the Zn–THPP complex exhibits the strongest response with the lowest detectable gas concentration of NO₂ gas for both 520 nm and 670 nm. The Ni–THPP and Co–THPP complexes display good efficiency in the detection of NO₂, while, on the other hand, Cu–THPP shows a very low interaction with NO₂ gas, with only 50 ppm and 200 ppm detectable gas concentration for 520 nm and 670 nm, respectively. In addition, molecular dynamic simulations and quantum mechanical calculations were performed, proving to be coherent with the experimental results.

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.

μOPTO: A microfluidic paper-based optoelectronic tongue as presumptive tests for the discrimination of alkaloid drugs for forensic purposes

Natural and synthetic alkaloids are widely used for several applications, ranging from clinical purposes to criminal activities. Presumptive color tests are considered a leading tool to reveal on-scene substance identification via rapid chemical reactions that result in visual color changes. Colorimetric tests are popular due to their inherent simplicity, low cost, promptitude and portability; however, in many cases the results of such tests may not be predictable, partly because of the interference from similar species. In this proof-of-concept study, we present a paper-based microfluidic optoelectronic tongue - the so-called μOPTO - comprised of 6 indicators in lieu of one specific test and capable of discriminating 8 different alkaloid drugs (i.e. scopolamine, atropine, cocaine, morphine, ephedrine, caffeine, dipyrone and alprazolam) used for recreational, criminal and medical purposes. The wax printing method was employed to fabricate the microfluidic analytical device with six circular spots for reagent accommodation connected to a centered spot to enable simultaneous reactions with one sample injection. Digital images were obtained using an ordinary flatbed scanner, and the RGB information from before and after sample exposure was extracted using appropriate software. The color changes related to each spot were used to build differential maps with a unique fingerprint for each drug. The chemometric tools (i.e. PCA and HCA) showed suitable discrimination of all studied alkaloids in different quantities. To demonstrate a practical application, different alcoholic beverages spiked with scopolamine - a famous substance that causes drug abuse - were analyzed using the optoelectronic tongue. The results showed that small quantities of the drug were identified in different beverages, demonstrating that our device has the potential to be used in situ to prevent ingestion of contaminated samples.

Detection of aldehydes by gold nanoparticle colorimetric array based on Tollens' reagent

Aldehydes are very common pollutants and many are possible human carcinogens. Herein, we report an easy-to-operate and low-cost method for discrimination of diverse aldehydes. Our colorimetric sensor array based on Tollens' reagent allows discrimination of ten kinds of aldehydes, showing a distinct color change from wine-red to deep yellow. In the presence of aldehydes, Ag shells are coated onto gold nanoparticles (GNPs) functionalized with diverse ligands (including bovine serum albumin, polyvinylpyrrolidone and L-cysteine), forming Au@Ag core-shell nanoparticles. The sensor array has great capacity for differentiating between ten kinds of aldehydes by color change, with accuracy and specificity of over 88%. Under optimal conditions, there is good linear correlation between Euclidean distance and formaldehyde concentrations ranging from 0.1 to 10 000 μM (R² = 0.9908). The sensor was successfully used to determine formaldehyde content in shrimp, with recovery of 85.8% to 114.82%. Our GNPs sensor shows good potential for fast, reliable identification of aldehydes in food.

Narrowly-Distributed Conjugated Polymers Synthesized through Suzuki Polymerization with Palladium(II) N-Heterocyclic Carbene Complex Confined in Dendritic Mesoporous Silica Nanoparticles

A catalytic heterogenous Suzuki polymerization method was developed by confining the Pd(II)-catalyzed cross coupling reactions to take place exclusively in the nanochannels of dendritic mesoporous silica nanoparticles. Conjugated polymers with various monomer combinations, including donor-acceptor structures, were obtained in high yields. The molecular weights of the obtained polymers were well controlled with narrow molecular weight distributions (PDI value down to 1.13). All the polymeric products were highly soluble in common organic solvents, granting them with high processability. All the features of this confined Suzuki polymerization method endow the conjugated polymers great potential in optoelectronic applications.

BioChemPen for a Rapid Analysis of Compounds Supported on Solid Surfaces

We present BioChemPen, a portable wireless biosensor device for rapid analysis of substances adsorbed on solid surfaces. The device takes advantage of (bio)luminescent reactions taking place in a hydrogel matrix. In a typical embodiment, the active element of this device is a hydrogel disk (chemotransducer) containing enzyme(s), electrolyte solution, and all of the necessary substrates. When the hydrogel is exposed to a solid sample surface containing the target analyte, light is produced. A photoresistor (phototransducer), placed in close proximity to the hydrogel disk, detects the light. The operation of the BioChemPen is enabled by a MicroPython PyBoard microcontroller board and other low-cost electronic modules. The obtained results are immediately uploaded to the Internet cloud. In one application, we demonstrate an analysis of hypochlorite-containing cleaning agents present on the surfaces of daily use objects by an assay based on hydrogel embedded with luminol and hydrogen peroxide. In another application, we use hydrogel embedded with luciferin, luciferase, and pyruvate kinase to detect adenosine triphosphate (ATP), and adenosine diphosphate (ADP), and link the ATP content with meat freshness. Lastly, we demonstrate the detection of organophosphate pesticides present on vegetables with the hydrogel containing acetylcholinesterase, choline oxidase, and horseradish peroxidase. The limits of detection for sodium hypochlorite, ATP, ADP, and chlorpyrifos-methyl (a pesticide) were 7.95 × 10^-11, 2.73 × 10^-13, 2.35 × 10^-12, and 2.59 × 10^-10 mol mm^-2, respectively.

Structural Features of a Family of Coumarin-Enamine Fluorescent Chemodosimeters for Ion Pairs

A family of coumarin-enamine chemodosimeters is evaluated for their potential use as fluorescent molecular probes for multiple analytes [cadmium(II), cobalt(II), copper(II), iron(II), nickel(II), lead(II), and zinc(II)], as their chloride and acetate salts. These fluorophores displayed excellent optical spectroscopic modulation when exposed to ion pairs with different Lewis acidic and basic properties in dimethyl sulfoxide (DMSO). The chemodosimeters were designed to undergo excited-state intramolecular proton transfer (ESIPT), which leads to significant Stokes shifts (ca. 225 nm) and lower-energy fluorescence emission (ca. 575 nm). A more basic anion, e.g., acetate, inhibited the ESIPT mechanism by deprotonation of the enol, producing a binding pocket (N^O^- chelate) that can coordinate to an appropriate metal ion. Coordination of the metal ions enhances the fluorescent intensity via the chelation-enhanced fluorescence emission mechanism. Subjecting the spectroscopic data to linear discriminant analysis provided insights into the source of these systems' markedly different behavior toward ion pairs, despite the subtle structural differences in the organic framework. These compounds are examples of versatile, low-molecular-weight, dual-channel fluorescent sensors for ion-pair recognition. This study paves the way for using these probes as practical components of a sensing array for different metal ions and their respective anions.

Fluorescent chameleon labels for bioconjugation and imaging of proteins, nucleic acids, biogenic amines and surface amino groups. a review

Chameleon labels (ChLs) possess the unique property of changing (visible) color and fluorescence on binding to amino groups of biomolecules. MostChLs react with primary aliphatic amino groups such as those in lysine or with amino groups artificially introduced into polynucleic acids or saccharides, but someothers also react with secondary amino groups. Under controlled circumstances, the reactions are fairly specific. The review is subdivided into the following sections: (1) An introduction and classification of fluorescent labels; (2) pyrylium labels that undergo shortwave color changes upon labelling, typically from blue to red; (3) polymethine type of labels (that also undergo shortwave color changes, typically from green to blue; (4) various other (less common) chromogenic and fluorogenic systems; (5) hemicyanine labels that undergolongwavecolor changes, typically from yellow to purple; (6) the application of ChLs to labeling of proteins and oligonucleotides; (7) applications to fluorometric assays and sensing; (8) applications to fluorescence imaging of biomolecules; (9) applications in studies on affinity interactions (receptor-ligand binding); (10) applications in surface and interface chemistry; and (11) applications in chromatography, electrophoresis and isotachophoresis of biomolecules.

Fully integrated ultra-sensitive electronic nose based on organic field-effect transistors

Modern solid-state gas sensors approaching ppb-level limit of detection open new perspectives for process control, environmental monitoring and exhaled breath analysis. Organic field-effect transistors (OFETs) are especially promising for gas sensing due to their outstanding sensitivities, low cost and small power consumption. However, they suffer of poor selectivity, requiring development of cross-selective arrays to distinguish analytes, and environmental instability, especially in humid air. Here we present the first fully integrated OFET-based electronic nose with the whole sensor array located on a single substrate. It features down to 30 ppb limit of detection provided by monolayer thick active layers and operates in air with up to 95% relative humidity. By means of principal component analysis, it is able to discriminate toxic air pollutants and monitor meat product freshness. The approach presented paves the way for developing affordable air sensing networks for the Internet of Things.

Ratiometric Cataluminescence Sensor of Amine Vapors for Discriminating Meat Spoilage

The freshness of meat has always been the focus of attention from consumers and suppliers for health and economic reasons. Usually, amine vapors, as one of the main components of the gas produced in the process of meat spoilage, can be used to monitor meat spoilage. Here, a new ratiometric cataluminescence (CTL) sensor based on energy transfer was developed to identify amine vapors and monitor meat freshness. After Tb doping, amine vapors exhibit a dual-wavelength (490 and 555 nm) property of CTL signals when reacted on the surface of Tb-doped La₂O₂CO₃, and the ratio of I₅₅₅ to I₄₉₀ (R_555/490) is a unique value for a given analyte within a wide range of concentrations. To illustrate the new sensor, 15 amine vapors were successfully identified using R_555/490, including homologues and isomers. Besides, this sensor was used to monitor four meats, and the freshness of meats can be distinguished by cluster analysis successfully. Moreover, further discussion of energy-transfer phenomena and influence factors has facilitating effects on exploring the mechanism of energy transfer at the gas-solid interface.

Fabricating a nano-bionic sensor for rapid detection of H2S during pork spoilage using Ru NPs modulated catalytic hydrogenation conversion

Rapid, sensitive and on-site monitoring of meat spoilage is highly essential for food safety. Hydrogen sulfide (H₂S) a typical volatile, produced during enzymatic hydrolysis is considered as a reliable marker for evaluating meat freshness. Herein, a novel nano-bionic sensor based on the superior catalytic activity of ruthenium nanoparticles (Ru NPs) has been fabricated for H₂S quantification. The activity sites of Ru NPs were poisoned in the presence of H₂S, thereby affecting its catalytic efficiency via reducing the degradation of azo dye. The developed nano-bionic sensor achieved a selective response toward H₂S, with capability for on-site surveillance of the pork freshness in the linear range (0-1800 nM). A higher correlation was obtained between the H₂S content and the total viable count during the 9-period pork spoilage process (R² = 0.9633 and 0.9769). Moreover, the proposed method exhibits high selectivity in the presence of other characteristic volatiles encountered during the pork storage process.

A Diverse Micromorphology of Photonic Crystal Chips for Multianalyte Sensing

The diversity by nano/microstructural material or device constructing can provide the exciting opportunity for sensitivity and selectivity to achieve facile and efficient multianalyte recognition for clinical diagnosis, environment monitoring, etc., in complex system analysis. Colloidal poly(styrene-methyl methacrylate-acrylic acid) (poly(St-MMA-AA)) nanoparticle-assembled photonic crystals (PCs) can achieve manipulative 3D structural colors and approach PC sensor chip for high-efficient multianalysis utilizing simple dye. Focusing on the morphology effects of structural color, a PC microchip is designed and constructed with various geometrical micromorphologies. Based on the angle dependence of colloidal-crystal structural color, the stopband distribution is explored on various morphological PC pixels. Selective fluorescent enhancement is realized for stopband-matched PCs, which approach the successful discrimination of metal ions and complex multianalysis of groundwater. Meanwhile, printed droplet-shaping manipulation can achieve a large-scale structural-color sensor array of chips with designable nano/microstructures via colloidal assembly. It will be the critical puzzle piece between macromorphology and microstructure for the structural-color researches.

Mitigation of Humidity Interference in Colorimetric Sensing of Gases

Colorimetric sensing technologies have been widely used for both quantitative detection of specific analyte and recognition of a large set of analytes in gas phase, ranging from environmental chemicals to biomarkers in breath. However, the accuracy and reliability of the colorimetric gas sensors are threatened by the humidity interference in different application scenarios. Though substantial progress has been made toward new colorimetric sensors development, unless the humidity interference is well addressed, the colorimetric sensors cannot be deployed for real-world applications. Although there are comprehensive and insightful review articles about the colorimetric gas sensors, they have focused more on the progress in new sensing materials, new sensing systems, and new applications. There is a need for reviewing the works that have been done to solve the humidity issue, a challenge that the colorimetric gas sensors commonly face. In this review paper, we analyzed the mechanisms of the humidity interference and discussed the approaches that have been reported to mitigate the humidity interference in colorimetric sensing of environmental gases and breath biomarkers. Finally, the future perspectives of colorimetric sensing technologies are also discussed.

The Optoelectronic Nose

How does one tell the difference between one molecule or mixture of molecules from another? Chemical sensing seeks to probe physical or chemical properties of molecular or ionic species (i.e., analytes) and transform that information into a useful and distinguishable output. The olfactory system of animals is the prototype of chemical sensing. Even for human beings (who are generally more visual than olfactory creatures), the sense of smell is one of our most basic capabilities, and we can discriminate among many thousands, and possibly even billions, of different odors. The chemical specificity of the olfactory system does not come from specific receptors for specific analytes (i.e., the traditional lock-and-key model of enzyme-substrate interactions), but rather olfaction uses pattern recognition of the combined responses of several hundred olfactory receptors.In analogy to olfaction, colorimetric sensor arrays provide high dimensional data from the color changes of chemically responsive colorants as they are exposed to analytes. These colorants include pH responsive dyes, Lewis acid/base indicators, redox dyes, vapochromics, and surface-modified silver nanoparticles. The color difference maps so created provide chemical sensing with high sensitivity (often down to ppb levels), impressive discrimination among very similar analytes, and exquisite fingerprinting of extremely similar mixtures over a wide range of analyte types, both in the gas and liquid phases. Such colorimetric arrays probe a wide range of the chemical reactivity of analytes, rather than the limited dimensionality of physical properties (e.g., mass) or physisorption (e.g., traditional electronic noses). Our sensor arrays are disposable and simple to produce by either inkjet or robotic dip-pen printing onto the surface of porous polymer membranes or even paper.Design of both sensor arrays and optical readers for their analysis has advanced to a fully self-contained pocket-sized instrument, the optoelectronic nose. Quantitative analysis requires appropriate chemometric methods for pattern recognition of data with inherently high dimensionality, e.g., hierarchical cluster analysis and support vector machines. A wide range of applications for the colorimetric sensor arrays has been developed, including personal dosimetry of toxic industrial chemicals, detection of explosives or fire accelerants, monitoring pollutants for artwork and cultural heritage preservation, quality control of foods and beverages, rapid identification of bacteria and fungi, and detection of disease biomarkers in breath or urine. The development of portable, high-accuracy instrumentation using standard imaging devices with the capability of onboard, real-time analysis has had substantial progress and increasingly meets the expectations for real-world use.

Chemical QR Code: A simple and disposable paper-based optoelectronic nose for the identification of olive oil odor

Olive oil is an appreciated food product with high nutritional value, besides being an essential component in many culture diets. In this study, we present for the first time the application of a simple and non-invasive paper-based optoelectronic nose designed in a QR code configuration to evaluate the odor of olive oils. The chemical QR code was fabricated by the addition of 12 dyes, which provided high dimensional data resulting from the interaction between the volatile compounds and the colorimetric array. The color changes were employed to build differential maps with a unique fingerprint (i) to discriminate between olive oil and other edible oil samples; (ii) to quantify nonanaldehyde as an oxidation marker; and (iii) to identify oxidized oils through principal component analysis (PCA) and hierarchical component analysis (HCA). By developing suitable mobile apps, we anticipate the employment of the chemical QR code for portable, low-cost, and in-situ evaluation of food product quality.

Application of bromocresol purple nanofilm and laser light to detect mutton freshness

Optical waveguide gas sensor with bromocresol purple (BCP) nano-film (70-80 nm) composited with silicone deposited on surface of K⁺-ion exchanged glass slide was fabricated and applied to detect amine gases released during mutton spoilage to test mutton freshness with the help of laser light (632 m). Gas sensing measurements (output light intensity vs. time) proved its high selectivity and good sensitivity (0.01 ppm) toward amines among volatile organic compounds. The optimal fabricating condition (2600 rpm, 0.10% BCP, 5.17% silicone) was selected experimentally, displaying 1 s and 12 s response-recovery time toward gases released from mutton samples stored at 5 °C and 25 °C respectively. The sensing mechanism was explained by combination and competition of diffusion-reaction, considering deprotonating reaction of bromocresol purple molecules and molecular size of analyte gases in diffusion process. UV-vis spectroscopy was used to select the specific wavelength of laser light source in optical waveguide performance and to detect the total volatile basic nitrogen contents in mutton sample to confirm the practicability of as-prepared optical waveguide sensor in detecting mutton freshness. The fabricated sensor is able to detect 7.2 mg/100 g gases released from mutton decomposition, providing a simple, fast, and cheap method to detect meat freshness.

User-friendly lab-on-paper optical sensor for the rapid detection of bacterial spoilage in packaged meat products

A lab-on-paper colorimetric sensor for detection and quantification of bacterial meat spoilage is reported.

Paper-Based Enzyme Biosensor for One-Step Detection of Hypoxanthine in Fresh and Degraded Fish

Food freshness monitoring, which can reflect the quality of the product at the time of use, remains a great challenge for consumers and the food industry. Herein, we report the development of a cost-effective enzyme-based paper biosensor, which can monitor fish freshness and predict spoilage. The biosensor measures the release of hypoxanthine (HX), an indicator of meat and fish degradation, using the enzymatic conversion of HX by xanthine oxidase (XOD). We demonstrate that the entrapment of XOD and an organic dye, nitro blue tetrazolium chloride (NBT), within a sol-gel biohybrid enables their stabilization on paper and promotes the enzymatic reaction with further retention of the reaction products within the cellulosic network . Linearity in the micromolar concentration range with a detection limit of 3.7 μM for HX is obtained. The biosensor has high selectivity toward HX and is manufactured in few steps from inexpensive widely available materials. The applicability of the biosensor is demonstrated by following fish degradation over time and measuring HX concentrations ranging from 117 (±9) to 198 (±5) μM within 24 h of degradation, at levels that are comparable with those measured by a commercial enzymatic kit for HX detection. As compared to the commercial kit, our biosensors are more cost-effective, do not require addition of exogenous reagents and are portable, having all of the reagents needed for analysis embedded within the sensing platform. This proof-of-concept work demonstrates that the paper-based HX biosensor has potential as a robust reagentless device for real-time monitoring of food freshness and for other applications in which HX plays an important role.

Paper-based optoelectronic nose for identification of indoor air pollution caused by 3D printing thermoplastic filaments

Commercial printers based on fused deposition modeling (FDM) are widely adopted for 3D printing applications. This method consists of the heating of polymeric filaments over the melting point followed by their deposition onto a solid base to create the desirable 3D structure. Prior investigation using chromatographic techniques has shown that chemical compounds (e.g. VOCs), which can be harmful to users, are emitted during the printing process, producing adverse effects to human health and contributing to indoor air pollution. In this study, we present a simple, inexpensive and disposable paper-based optoelectronic nose (i.e. colorimetric sensor array) to identify the gaseous emission fingerprint of five different types of thermoplastic filaments (ABS, TPU, PETG, TRITAN and PLA) in the indoor environment. The optoelectronic nose is comprised of selected 15 dyes with different chemical properties deposited onto a microfluidic paper-based device with spots of 5 mm in diameter each. Digital images were obtained from an ordinary flatbed scanner, and the RGB information collected before and after air exposure was extracted by using an automated routine designed in MATLAB, in which the color changes provide a unique fingerprint for each filament in 5 min of printing. Reproducibility was obtained in the range of 2.5-10% (RSD). Hierarchical clustering analysis (HCA) and principal component analysis (PCA) were successfully employed, showing suitable discrimination of all studied filaments and the non-polluted air. Besides, air spiked with vapors of the most representative VOCs were analyzed by the optoelectronic nose and visually compared to each filament. The described study shows the potential of the paper-based optoelectronic nose to monitor possible hazard emissions from 3D printers.

Development of a Dye-Based Device to Assess the Poultry Meat Spoilage. Part II: Array on Act

This work presents a colorimetric dye-based array for naked-eye detection of chicken meat spoilage. The array is obtained by fixing five acid-base indicators, m-cresol purple (1), o-cresol red (2), bromothymol blue (3), thymol blue (4), and chlorophenol red (5), and a sensing molecule specific for thiols, 5,5'-dithiobis(2-nitrodibenzoic acid), called Ellman's reagent (6), on a cellulose-based support. The dyes, being permanently charged, are fixed on the support via ion-exchange. The entire degradation process of beast poultry meat, at ambient temperature and in a domestic fridge, is followed by the change of the color of the array, placed in the headspace over the meat samples. The device is set after selection of the most suitable starting form, which could be the acidic or the basic color of indicators, being the proper dye concentration and the dimension of the spots already established. Basing on sensors colors, we identified three levels of the degradation process of chicken meat, named SAFE, WARNING, and HAZARD. By instrumental analysis, we demonstrated that sensors response was correlated to volatile organic compounds (VOCs) composition in the headspace and, thus, to meat spoilage progress. We demonstrated that biogenic amines (BAs), commonly considered a critical spoilage marker, are indeed produced into the samples but never present in the headspace, even in traces, during the investigated time-lapse. The VOC evolution nevertheless allows one to assign the sample as WARNING and further HAZARD. Some indicators turned out to be more informative than others, and the best candidates for a future industrial application resulted in a bromothymol blue (3)-, chlorophenol red (5)-, and Ellman's reagent (6)-based array.

Portable Food-Freshness Prediction Platform Based on Colorimetric Barcode Combinatorics and Deep Convolutional Neural Networks

Artificial scent screening systems (known as electronic noses, E-noses) have been researched extensively. A portable, automatic, and accurate, real-time E-nose requires both robust cross-reactive sensing and fingerprint pattern recognition. Few E-noses have been commercialized because they suffer from either sensing or pattern-recognition issues. Here, cross-reactive colorimetric barcode combinatorics and deep convolutional neural networks (DCNNs) are combined to form a system for monitoring meat freshness that concurrently provides scent fingerprint and fingerprint recognition. The barcodes-comprising 20 different types of porous nanocomposites of chitosan, dye, and cellulose acetate-form scent fingerprints that are identifiable by DCNN. A fully supervised DCNN trained using 3475 labeled barcode images predicts meat freshness with an overall accuracy of 98.5%. Incorporating DCNN into a smartphone application forms a simple platform for rapid barcode scanning and identification of food freshness in real time. The system is fast, accurate, and non-destructive, enabling consumers and all stakeholders in the food supply chain to monitor food freshness.

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.