Fish freshness detection by a computer screen photoassisted based gas sensor array

Discrimination of toxigenic and non-toxigenic Aspergillus flavus in wheat based on nanocomposite colorimetric sensor array

A novel method was developed for the early detection of wheat infected with Aspergillus flavus (A. flavus) using a nanocomposite colorimetric sensors array (CSA). LC-MS analysis revealed the presence of Aflatoxin B1 (AFB1) and Aflatoxin B2 (AFB2) on day seven, demonstrating mycotoxin variabilities in infected wheat. HS-SPME-GC-MS analysis detected 2-methylbutyral, a gas exclusively associated with toxigenic A. flavus. The CSA was modified using three nanoparticles of MOF and successfully used to detect the wheat infected with A. flavus. Discrimination of different types of infected wheat samples was achieved using the RGB difference map and Principal Component Analysis (PCA) model. Additionally, the Linear Discriminant Analysis (LDA) model accurately predicted the presence of toxigenic A. flavus at various stages of infection. These findings highlight the promising capabilities of nanocomposite CSA for early-stage detection of A. flavus infection in wheat.

Drying kinetics and quality dynamics of ultrasound-assisted dried selenium-enriched germinated black rice

Black rice is a functional food due to its higher protein, fiber, iron, antioxidant compounds, and other health benefits than traditional rice. The ultrasonic (US) pretreatments (10, 20, and 50 min) followed by hot-air drying (50, 60, and 70 °C) were applied to study the drying kinetics, mathematical modeling, thermodynamics, microstructure, bioactive profile, volatile compounds and to lock the nutritional composition of selenium-enriched germinated black rice (SeGBR). Ultrasonic-treated samples exhibited a 20.5% reduced drying time than control ones. The Hii model accurately describes the drying kinetics of SeGBR with the highest R2 (>0.997 to 1.00) among the fifteen studied models. The activation energy values in US-SeGBR varied from 3.97 to 13.90 kJ/mol, while the specific energy consumption ranged from 6.45 to 12.32 kWh/kg, which was lower than untreated. The obtained thermodynamic attributes of dried black rice revealed that the process was endothermic and non-spontaneous. Gallic acid, kaempferol, and cyanidin 3-glucoside were present in high concentrations in phenolics, flavonoids, and anthocyanins, respectively. The HS-SPME-GC-MS investigation detected and quantified 55 volatile compounds. The US-treated SeGBR had more volatile compounds, which may stimulate the release of more flavorful substances. The scanning electronic micrograph shows that the US-treated samples absorbed high water through several micro-cavities. Selenium concentration was significantly higher in US-treated samples at 50 °C than in control samples. In conclusion, ultrasound-assisted hot-air drying accelerated drying and improved SeGBR quality, which is crucial for the food industry and global promotion of this healthiest rice variety.

Construction of a simple dual-mode ATP-sensing system for reliable fish freshness evaluation

Adenosine triphosphate (ATP), the main carrier of chemical energy, plays a key role in various biochemical reactions such as cellular metabolism. Currently, ATP levels are considered important indicators of microbial content in food safety, and food freshness can be determined by detecting ATP content. Some ATP sensing strategies have been applied to evaluate food freshness. However, cumbersome nanomaterial preparation, low sensitivity, and low reliability hamper their widespread application. Herein, a simple, high-performance, and reliable dual-mode sensing system based on hemin-G-quadruplex (G4) DNAzyme was established to detect ATP and assess fish freshness. Two nucleic acid probes, including subunits of the hemin-G4 DNAzyme in inactive structures and anti-ATP aptamer, self-assemble upon the input of ATP into the active hemin-G4 DNAzyme unit. The generated DNAzyme acts as a biocatalyst for colorimetric or fluorescent readout of the sensing process. The colorimetric and fluorescent dual-mode sensing system enables highly sensitive and reliable analysis of target ATP with detection limits of 71 nM and 73 nM, respectively. Moreover, the biosensor exhibited good selectivity for differentiating ATP from other interfering analytes. The proposed system was used to detect ATP in perch samples, and a linear correlation between ATP level and microbial content was confirmed. The established ATP-sensing system reliably evaluated fish freshness. Notably, in comparison with microbiological counts, the proposed DNAzyme-based dual-mode strategy for freshness evaluation is facile, highly efficient, and cost-effective, thus providing a promising method for food safety and quality monitoring.

Emerging Approach for Fish Freshness Evaluation: Principle, Application and Challenges

Affected by micro-organisms and endogenous enzymes, fish are highly perishable during storage, processing and transportation. Efficient evaluation of fish freshness to ensure consumer safety and reduce raw material losses has received an increasing amount of attention. Several of the conventional freshness assessment techniques have plenty of shortcomings, such as being destructive, time-consuming and laborious. Recently, various sensors and spectroscopic techniques have shown great potential due to rapid analysis, low sample preparation and cost-effectiveness, and some methods are especially non-destructive and suitable for online or large-scale operations. Non-destructive techniques typically respond to characteristic substances produced by fish during spoilage without destroying the sample. In this review, we summarize, in detail, the principles and applications of emerging approaches for assessing fish freshness including visual indicators derived from intelligent packaging, active sensors, nuclear magnetic resonance (NMR) and optical spectroscopic techniques. Recent developments in emerging technologies have demonstrated their advantages in detecting fish freshness, but some challenges remain in popularization, optimizing sensor selectivity and sensitivity, and the development of algorithms and chemometrics in spectroscopic techniques.

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.

Overview of advanced technologies for volatile organic compounds measurement in food quality and safety

Food quality and nutrition have received much attention in recent decades, thanks to changes in consumer behavior and gradual increases in food consumption. The demand for high-quality food necessitates stringent quality assurance and process control measures. As a result, appropriate analytical tools are required to assess the quality of food and food products. VOCs analysis techniques may meet these needs because they are nondestructive, convenient to use, require little or no sample preparation, and are environmentally friendly. In this article, the main VOCs released from various foods during transportation, storage, and processing were reviewed. The principles of the most common VOCs analysis techniques, such as electronic nose, colorimetric sensor array, migration spectrum, infrared and laser spectroscopy, were discussed, as well as the most recent research in the field of food quality and safety evaluation. In particular, we described data processing algorithms and data analysis captured by these techniques in detail. Finally, the challenges and opportunities of these VOCs analysis techniques in food quality analysis were discussed, as well as future development trends and prospects of this field.

Advanced applications of chemo-responsive dyes based odor imaging technology for fast sensing food quality and safety: A review

Public attention to foodquality and safety has been increased significantly. Therefore, appropriate analytical tools are needed to analyze and sense the food quality and safety. Volatile organic compounds (VOCs) are important indicators for the quality and safety of food products. Odor imaging technology based on chemo-responsive dyes is one of the most promising methods for analysis of food products. This article reviews the sensing and imaging fundamentals of odor imaging technology based on chemo-responsive dyes. The aim is to give detailed outlines about the theory and principles of using odor imaging technology for VOCs detection, and to focus primarily on its applications in the field of quality and safety evaluation of food products, as well as its future applicability in modern food industries and research. The literatures presented in this review clearly demonstrated that imaging technology based on chemo-responsive dyes has the exciting effect to inspect such as quality assessment of cereal , wine and vinegar flavored foods , poultry meat, aquatic products, fruits and vegetables, and tea. It has the potential for the rapid, reliable, and inline assessment of food safety and quality by providing odor-image-basedmonitoring tool. Practical Application: The literatures presented in this review clearly demonstrated that imaging technology based on chemo-responsive dyes has the exciting effect to inspect such as quality assessment of cereal , wine and vinegar flavored foods, poultry meat, aquatic products, fruits and vegetables, and tea.

A Multi-Sensor System for Sea Water Iodide Monitoring and Seafood Quality Assurance: Proof-of-Concept Study

Iodine is a trace chemical element fundamental for a healthy human organism. Iodine deficiency affects about 2 billion people worldwide causing from mild to severe neurological impairment, especially in children. Nevertheless, an adequate nutritional intake is considered the best approach to prevent such disorders. Iodine is present in seawater and seafood, and its common forms in the diet are iodide and iodate; most iodide in seawater is caused by the biological reduction of the thermodynamically stable iodate species. On this basis, a multisensor instrument which is able to perform a multidimensional assessment, evaluating iodide content in seawater and seafood (via an electrochemical sensor) and discriminating when the seafood is fresh or defrosted quality (via a Quartz Micro balance (QMB)-based volatile and gas sensor), is strategic for seafood quality assurance. Moreover, an electronic interface has been opportunely designed and simulated for a low-power portable release of the device, which should be able to identify seafood over or under an iodide threshold previously selected. The electrochemical sensor has been successfully calibrated in the range 10–640 μg/L, obtaining a root mean square error in cross validation (RMSECV) of only 1.6 μg/L. Fresh and defrosted samples of cod, sea bream and blue whiting fish have been correctly discriminated. This proof-of-concept work has demonstrated the feasibility of the proposed application which must be replicated in a real scenario.

Freshness Classification of Horse Mackerels with E-Nose System Using Hybrid Binary Decision Tree Structure

The aim of this study is to test the freshness of horse mackerels by using a low cost electronic nose system composed of eight different metal oxide sensors. The process of freshness evaluation covers a scala of seven different classes corresponding to 1, 3, 5, 7, 9, 11, and 13 storage days. These seven classes are categorized according to six different classifiers in the proposed binary decision tree structure. Classifiers at each particular node of the tree are individually trained with the training dataset. To increase success in determining the level of fish freshness, one of the k-Nearest Neighbors (k-NN), Support Vector Machines (SVM), Linear Discriminant Analysis (LDA) and Bayes methods is selected for every classifier and the feature spaces change in every node. The significance of this study among the others in the literature is that this proposed decision tree structure has never been applied to determine fish freshness before. Because the freshness of fish is observed under actual market storage conditions, the classification is more difficult. The results show that the electronic nose designed with the proposed decision tree structure is able to determine the freshness of horse mackerels with 85.71% accuracy for the test data obtained one year after the training process. Also, the performances of the proposed methods are compared against conventional methods such as Bayes, k-NN, and LDA.

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.

Analysis of volatiles in brown rice, germinated brown rice, and selenised germinated brown rice during storage at different vacuum levels

BACKGROUND

The quality of nutritionally enhanced foods can be determined by evaluating changes in the volatile compounds produced in these foods over time. In this work, selenium-enriched germinated brown rice (Se-GBR), germinated brown rice (GBR), and brown rice (BR) stored under 90% relative humidity, 38 °C, and various vacuum levels were investigated. The relative abundance and differences of volatile compounds in Se-GBR, GBR, and BR over various storage periods were detected. The correlation of volatile compound abundance with vacuum level and storage time was analysed using principal component analysis (PCA).

RESULTS

Volatile compounds in the three samples were quantified at various storage periods (0, 90 and 150 days). Approximately 100 volatile compounds and eight species were identified and classified. Various proportions or types of volatile compounds were found in each sample at different sampling times. PCA results showed an isolation of volatile compounds in terms of sampling day and vacuum level at each storage period.

CONCLUSION

Changes in volatile compounds over time and vacuum levels can provide bases for assessing of the nutritional quality of Se-GBR, GBR, and BR. © 2017 Society of Chemical Industry.

Development of a novel colorimetric sensor based on alginate beads for monitoring rainbow trout spoilage

Alginate is a non-toxic, renewable, and linear copolymer obtained from the brown algae Laminaria digitata that can be easily shaped into beads. Its good gel forming properties have made it useful for entrapping food and pharmaceutical ingredients. In this study, alginate beads were used in a novel application as a colorimetric sensor in food intelligent packaging. Colorimetric sensor was developed through entrapping red cabbage extract as a pH indicator in alginate beads. The pH indicator beads were used in rainbow trout packaging for monitoring fillets spoilage. Color change of beads during fish storage was measured using the CIELab method. The alginate bead colorimetric sensor is validated by measuring total volatile basic nitrogen (TVB-N) levels and microbial populations in fish samples. Moreover, peroxide value (PV) and thiobarbituric acid reactive substances (TBARS) were evaluated during storage. Results indicated that increasing the bacterial population during storage and production of proteolytic enzymes resulted in protein degradation, accumulation of volatile amine compounds, increase in the pH and finally color change of alginate beads. The values of TVB-N, pH, PV and TBARS increased with time of storage. The results of TVB-N and microbial growth were in accordance with color change of beads and CIELab data. Therefore, the proposed system enjoys a high sensitivity to pH variations and is capable of monitoring the spoilage of fish or other protein-rich products through its wide range of color changes. The alginate beads containing the red cabbage extract can, thus, be used as a low-cost colorimetric sensor for intelligent packaging applications.

Porphyrins for olfaction mimic: The Rome Tor Vergata approach

The impressive chemistry shown by porphyrins in natural systems is particularly attractive for exploitation in chemical sensors. In these devices the sensing mechanisms can mimic most of the porphyrin biological reactivity, such as reversible binding, activation of small molecules, redox activity, and photoactivated processes. The simultaneous presence of multiple binding mechanisms allows porphyrins to interact with a large variety of analytes. This feature reduces the selectivity, but prompts the development of sensor arrays, where the cross-selectivity of more sensors is used to classify and identify samples characterized by a complex composition. Since 1995 the Sensors Group of the University of Rome Tor Vergata has exploited these features to prepare sensor arrays based on different transducers and aimed at several applications. These kinds of devices have been reported as electronic noses (gaseous phase analytes) and electronic tongues (liquid phase analytes) to underline that their working mechanisms are tentatively similar to that of biological senses. We report here some of the results obtained.

Tilapia fish microbial spoilage monitored by a single optical gas sensor

As consumption of fish and fish-based foods increases, non-destructive monitoring of fish freshness also becomes more prominent. Fish products are very perishable and prone to microbiological growth, not always easily detected by organoleptic evaluation. The analysis of the headspace of fish specimens through gas sensing is an interesting approach to monitor fish freshness. Here we report a gas sensing method for monitoring Tilapia fish spoilage based on the application of a single gas sensitive gel material coupled to an optical electronic nose. The optical signals of the sensor and the extent of bacterial growth were followed over time, and results indicated good correlation between the two determinations, which suggests the potential application of this simple and low cost system for Tilapia fish freshness monitoring.

Porphyrinoids for Chemical Sensor Applications

Porphyrins and related macrocycles have been intensively exploited as sensing materials in chemical sensors, since in these devices they mimic most of their biological functions, such as reversible binding, catalytic activation, and optical changes. Such a magnificent bouquet of properties allows applying porphyrin derivatives to different transducers, ranging from nanogravimetric to optical devices, also enabling the realization of multifunctional chemical sensors, in which multiple transduction mechanisms are applied to the same sensing layer. Potential applications are further expanded through sensor arrays, where cross-selective sensing layers can be applied for the analysis of complex chemical matrices. The possibility of finely tuning the macrocycle properties by synthetic modification of the different components of the porphyrin ring, such as peripheral substituents, molecular skeleton, coordinated metal, allows creating a vast library of porphyrinoid-based sensing layers. From among these, one can select optimal arrays for a particular application. This feature is particularly suitable for sensor array applications, where cross-selective receptors are required. This Review briefly describes chemical sensor principles. The main part of the Review is divided into two sections, describing the porphyrin-based devices devoted to the detection of gaseous or liquid samples, according to the corresponding transduction mechanism. Although most devices are based on porphyrin derivatives, seminal examples of the application of corroles or other porphyrin analogues are evidenced in dedicated sections.

Recent advances in methods and techniques for freshness quality determination and evaluation of fish and fish fillets: a review

The freshness quality of fish plays an important role in human health and the acceptance of consumers as well as in international fishery trade. Recently, with food safety becoming a critical issue of great concern in the world, determination and evaluation of fish freshness is much more significant in research and development. This review renovates and concentrates recent advances of evaluating methods for fish freshness as affected by preharvest and postharvest factors and highlights the determination methods for fish freshness including sensory evaluation, microbial inspection, chemical measurements of moisture content, volatile compounds, protein changes, lipid oxidation, and adenosine triphosphate (ATP) decomposition (K value), physical measurements, and foreign material contamination detection. Moreover, the advantages and disadvantages of these methods and techniques are compared and discussed and some viewpoints about the current work and future trends are also presented.

Non-invasive sensing for food reassurance

The main food quality traits of interest using non-invasive sensing techniques are sensory characteristics, chemical composition, physicochemical properties, health-protecting properties, nutritional characteristics and safety. A wide range of non-invasive sensing techniques, from optical, acoustical, electrical, to nuclear magnetic, X-ray, biosensor, microwave and terahertz, are organized according to physical principle.

Bioelectronic nose combined with a microfluidic system for the detection of gaseous trimethylamine

A bioelectronic nose based on a novel microfluidic system (μBN) was fabricated to detect gaseous trimethylamine (TMA) in real-time. Single-walled carbon nanotube-field effect transistors (SWNT-FETs) were functionalized with olfactory receptor-derived peptides (ORPs) that can recognize the TMA molecules. The ORP-coated SWNT-FETs were assembled with a microfluidic channel and were sealed with top and bottom frames. This simple process was used to complete the μBNs, and a well-defined condition was achieved to detect the gaseous molecules. The μBNs allowed us to detect gaseous TMA molecules down to 10 parts per trillion (ppt) in real-time and showed high selectivity when distinguishing gaseous TMA from other gaseous odorants. The sensor was used to determine the quality of seafood (oysters), and spoiled seafood and other types of spoiled foods were also successfully discriminated without any pretreatment processes. These results indicate that portable-scale platforms can be manufactured by using μBNs and can be applicable for real-time on-site gas analysis.

Non-destructive prediction of thiobarbituricacid reactive substances (TBARS) value for freshness evaluation of chicken meat using hyperspectral imaging

This study examined the potential of hyperspectral imaging (HSI) for rapid prediction of 2-thiobarbituric acid reactive substances (TBARS) content in chicken meat during refrigerated storage. Using the spectral data and the reference values of TBARS, a partial least square regression (PLSR) model was established and yielded acceptable results with regression coefficients in prediction (Rp) of 0.944 and root mean squared errors estimated by prediction (RMSEP) of 0.081. To simplify the calibration model, ten optimal wavelengths were selected by successive projections algorithm (SPA). Then, a new SPA-PLSR model based on the selected wavelengths was built and showed good results with Rp of 0.801 and RMSEP of 0.157. Finally, an image algorithm was developed to achieve image visualization of TBARS values in some representative samples. The encouraging results of this study demonstrated that HSI is suitable for determination of TBARS values for freshness evaluation in chicken meat.

Development of a colorimetric sensor array for squid spoilage assessment

The aim of this work was to develop and evaluate a rapid, easy-to-use optoelectronic system for the shelf-life assessment of squid in cold storage. For this purpose, an optoelectronic nose was designed, which consisted of an array containing six sensing materials prepared by combining different dyes and two inorganic supports (aluminium oxide and silica gel). Samples were packaged with the colorimetric array and kept in cold storage for 12 days. Squid spoilage was monitored simultaneously by the colorimetric array and by the physico-chemical and microbial analyses during storage. Samples exceeded the acceptability limits for microbial counts on the third day. PCA analysis carried out with CIELab showed that the colorimetric array was able to discriminate between fresh squid fit for consumption and spoiled squid. The statistical models obtained by PLS, with the optoelectronic nose, successfully predicted CO2 and O2 content in the headspace as well as microbial growth.

Sensing the quality parameters of Chinese traditional Yao-meat by using a colorimetric sensor combined with genetic algorithm partial least squares regression

Yao-meat is a traditional Chinese salted meat. Total volatile basic nitrogen content (TVB-N), total viable bacterial count (TVC), and residual nitrite (RN) level are important indexes of freshness for Yao-meat. This paper attempted the feasibility to determine TVB-N content, TVC and RN level in Yao-meat by a colorimetric sensor array chip. A color change profile for each sample was obtained by differentiating the image of sensor array before and after exposure to Yao-meat's volatile organic compounds. Genetic algorithm partial least squares regression (GA-PLS) was proposed to build the relationship between the TVB-N content, TVC, RN and the color change profiles of sensor array, and to select informative chemically responsive dyes for the three quality parameters. The GA-PLS models were achieved with RTVB-N=0.812, RTVC=0.856, RRN=0.855, in prediction set. This study demonstrated that colorimetric sensory array with GA-PLS algorithm could be used successfully to analyze the quality of Chinese traditional Yao-meat.

Evaluation of sea bream (Sparus aurata) shelf life using an optoelectronic nose

A new optoelectronic nose for the shelf-life assessment of fresh sea bream in cold storage has been developed. The chromogenic array used eight sensing materials (based on aluminium oxide and silica gel) containing pH indicators, Lewis acids and an oxidation-reduction indicator. The colour changes of the sensor array were characteristic of sea bream spoilage. Colour modulations were measured on day 0 and for the samples held in cold storage for 2, 4, 7, 9 and 11 days. Determination of moisture content, pH, total volatile basic nitrogen (TVB-N), drip loss, ATP-related compounds and K(1)-value and microbial (mesophilic bacteria and Enterobacteriaceae) analyses were carried out on the same days. The changes in the chromogenic arrays data were processed by statistical analysis (PCA). Moreover, PLS statistical studies allowed the creation of models to correlate the chromogenic data with concentrations of mesophilic and Enterobacteriaceae. The results suggest the feasibility of this system to help develop optoelectronic noses for fish freshness monitoring.

Electronic nose and GC-MS analysis of volatile compounds in Tuber magnatum Pico: evaluation of different storage conditions

The characteristic aromatic composition of white truffles (Tuber magnatum Pico) determines its culinary and commercial value. However modifications of truffle organoleptic proprieties occur during preservation. A study of headspace of white truffles by using Electronic nose (E-nose), gas chromatography-mass spectrometry (GC-MS) and sensory analyses was performed. Truffles were stored at different conditions for 7 days: +4 and +8°C wrapped in blotting paper or covered by rice or none of the above. Headspace E-nose measurements and sensory analyses were performed each day. Statistical multivariate analysis of the data showed the capability of E-nose to predict sensorial analysis scores and to monitor aroma profile changes during storage. Truffle's volatile molecules were also extracted by headspace solid phase microextraction technique and separated and identified by GC-MS. Partial Components Analysis of data was performed. E-nose and GC-MS results were in agreement and showed that truffle storage in paper at +8°C seemed to be the best storage condition.

A peptide receptor-based bioelectronic nose for the real-time determination of seafood quality

We herein report a peptide receptor-based bioelectronic nose (PRBN) that can determine the quality of seafood in real-time through measuring the amount of trimethylamine (TMA) generated from spoiled seafood. The PRBN was developed using single walled-carbon nanotube field-effect transistors (SWNT-FETs) functionalized with olfactory receptor-derived peptides (ORPs) which can recognize TMA and it allowed us to sensitively and selectively detect TMA in real-time at concentrations as low as 10fM. Utilizing these properties, we were able to not only determine the quality of three kinds of seafood (oyster, shrimp, and lobster), but were also able to distinguish spoiled seafood from other types of spoiled foods without any pretreatment processes. Especially, the use of small synthetic peptide rather than the whole protein allowed PRBNs to be simply manufactured through a single-step process and to be reused with high reproducibility due to no requirement of lipid bilayers. Furthermore, the PRBN was produced on a portable scale making it effectively useful for the food industry where the on-site measurement of seafood quality is required.

Spectral fingerprinting of porphyrins for distributed chemical sensing

Recent progress in spectral fingerprinting of fluorescent indicators using distributed instrumentation based on consumer electronic devices is reviewed. In particular, the evaluation of disposable assays using a computer screen photo-assisted technique (CSPT) is discussed. Sample identification and optimization strategies are analyzed as well as the underlying theoretical background for polychromatic spectral fingerprinting.

A novel chemical detector using colorimetric sensor array and pattern recognition methods for the concentration analysis of NH3

With a colorimetric sensor array comprising chemoresponsive dyes, a simple, rapid, and cost-effective integrated system for differentiating low-concentration gases was described. The system could be used to identify gases by detecting the color change information of the chemoresponsive dyes based on porphyrins before and after reaction with the target gas; the colorimetric sensor array images were collected by a charge coupled device and processed with image analysis to get the color changes of the dyes in the array. Temperature, humidity, and flux of the chamber could be detected and displayed on the personal computer screen. A low-concentration [30-210 ppb (parts per 10(9))] NH(3) was detected by the system. This prototype successfully differentiated four concentration levels of NH(3) in less than 1 min. Pattern recognition methods, such as the backpropagation neural network and the radial basis function neural network, validated the effect of the developed sensor system both with 100% classification with feature vectors at single time point as inputs.

Validation of selective ion flow tube mass spectrometry for fast quantification of volatile bases produced on Atlantic cod (Gadus morhua)

Selective ion flow tube mass spectrometry (SIFT-MS) is a direct mass spectrometric technique that allows qualitative and quantitative analysis of a large number of volatile organic compounds. Because of its speed and ease of use, this nondestructive technique could be considered as a practical tool for quality control. This research focuses on the possibilities of direct headspace sampling by SIFT-MS for the quantification of the volatile basic nitrogen content (TVB-N) of fish fillets. These volatile bases [trimethylamine (TMA), dimethylamine (DMA), and ammonia] give additional information in conjunction with the sensory scoring and microbiological analysis about the quality of the fish fillets. This research validates in a first part the SIFT-MS method for the quantification of the volatile bases in mixed cod samples. With regard to the investigated linearity, repeatability, reproducibility, recovery, limit of detection, and limit of quantification, SIFT-MS appeared to be an adequate technique for measuring volatile bases spiked on cod. In the second part of this research, the technique was validated for the analysis of volatile bases on cod fillets during a storage experiment under ice. A good correlation was obtained between the proposed direct headspace sampling and traditional methods. The sensitivity of the SIFT-MS method can be improved when cod fillets are made more alkaline (pH >11) during sampling.

Polymers with embedded chemical indicators as an artificial olfactory mucosa

Physiological investigations suggest that the olfactory mucosa probably plays an ancillary role in the recognition of odours introducing a sort of chromatographic separation that, together with the zonal distribution of olfactory receptors, gives place to selective spatio-temporal response patterns. It has been recently suggested that this behaviour may be simulated by chemical sensors embedded in continuous polymer layers. In this paper, in analogy to the biology of olfaction, a simple and compact platform able to separate and detect gases and vapours on the basis of their diffusion properties is proposed. In such a system, broadly selective colour indicators, such as metalloporphyrins, are embedded in continuous layers of polymers with different sorption properties. The exposure to various alcohols and amines shows that the porphyrins are mainly responsible for the recognition of the molecular family, while the occurring spatio-temporal signal patterns make possible the identification of the individual chemical species.

Direct determination of volatile analytes from solid samples by UV-ion mobility spectrometry

A simple, reliable, inexpensive sample introduction system (SIS) coupled to an ion mobility spectrometry (IMS) equipment was used for the determination of volatile analytes present in solid samples. Following minimal pretreatment, the solid sample (e.g. fish) is directly placed in a membrane unit and released analytes (trimethylamine, dimethylamine and ammonia) pass through the membrane into a nitrogen acceptor stream; finally, passing the gaseous stream trough the UV-IMS system allows the analytes to be readily determined. Volatiles are released by heating the sample at 75 degrees C for 5 min following addition of a few drops of NaOH solution. This method is quite expeditious and uses small amounts of sample. The calibration graph is linear over the concentration range 5-225 microg mL(-1). The proposed SIS-IMS method is quite repeatable (RSD<4%) and reproducible (RSD<9%). Also, it provides acceptable analyte recoveries (111+/-17%) from spiked fish samples. The results of this study testify to the potential of IMS for qualitative and quantitative analytical determinations.

Direct quantitative evaluation of complex substances using computer screen photo-assisted technology: The case of red wine

The combination of computer monitors and webcams has been recently demonstrated to behave as a sort of spectrophotometer able to classify and recognize substances according to their light absorption and emission properties. This measurement technique is known as computer screen photoassisted technique (CSPT). In this paper, it is demonstrated for the first time and in the case of a complex sample such as red wine, that also quantification of integral parameters (colour indicators) and specific compounds (total anthocyanins and polyphenols) is possible through a multivariate analysis of CSPT fingerprints. Most of the properties of the method are due to the combination of light emission and absorption properties that are captured by the CSPT platform. Thanks to this combination, a CSPT fingerprint may contain a comparable amount of information with respect to standard spectrophotometers. Wine measurements were performed on intact samples without the intervention of chemical mediators. The regression models, built by Partial Least Squares, obtained errors of estimation of colour parameters, total polyphenols and anthocyanines that are comparable with those typical of the standard methods in use. Since computation functionalities, video capture and display are embedded in a steadily growing number of ubiquitously distributed equipment (from portable computers to cellular phones), these results indicate a viable methodology for low-cost and largely diffused analytical capabilities.