Rapid discrimination of Micrococcaceae species using semiconductor gas sensors

Recording the Presence of Peanibacillus larvae larvae Colonies on MYPGP Substrates Using a Multi-Sensor Array Based on Solid-State Gas Sensors

American foulbrood is a dangerous disease of bee broods found worldwide, caused by the Paenibacillus larvae larvae L. bacterium. In an experiment, the possibility of detecting colonies of this bacterium on MYPGP substrates (which contains yeast extract, Mueller-Hinton broth, glucose, K2HPO4, sodium pyruvate, and agar) was tested using a prototype of a multi-sensor recorder of the MCA-8 sensor signal with a matrix of six semiconductors: TGS 823, TGS 826, TGS 832, TGS 2600, TGS 2602, and TGS 2603 from Figaro. Two twin prototypes of the MCA-8 measurement device, M1 and M2, were used in the study. Each prototype was attached to two laboratory test chambers: a wooden one and a polystyrene one. For the experiment, the strain used was P. l. larvae ATCC 9545, ERIC I. On MYPGP medium, often used for laboratory diagnosis of American foulbrood, this bacterium produces small, transparent, smooth, and shiny colonies. Gas samples from over culture media of one- and two-day-old foulbrood P. l. larvae (with no colonies visible to the naked eye) and from over culture media older than 2 days (with visible bacterial colonies) were examined. In addition, the air from empty chambers was tested. The measurement time was 20 min, including a 10-min testing exposure phase and a 10-min sensor regeneration phase. The results were analyzed in two variants: without baseline correction and with baseline correction. We tested 14 classifiers and found that a prototype of a multi-sensor recorder of the MCA-8 sensor signal was capable of detecting colonies of P. l. larvae on MYPGP substrate with a 97% efficiency and could distinguish between MYPGP substrates with 1–2 days of culture, and substrates with older cultures. The efficacy of copies of the prototypes M1 and M2 was shown to differ slightly. The weighted method with Canberra metrics (Canberra.811) and kNN with Canberra and Manhattan metrics (Canberra. 1nn and manhattan.1nn) proved to be the most effective classifiers.

Nanotechnology for Food Packaging and Food Quality Assessment

Nanotechnology has paved the way to innovative food packaging materials and analytical methods to provide the consumers with healthier food and to reduce the ecological footprint of the whole food chain. Combining antimicrobial and antifouling properties, thermal and mechanical protection, oxygen and moisture barrier, as well as to verify the actual quality of food, e.g., sensors to detect spoilage, bacterial growth, and to monitor incorrect storage conditions, or anticounterfeiting devices in food packages may extend the products shelf life and ensure higher quality of foods. Also the ecological footprint of food chain can be reduced by developing new completely recyclable and/or biodegradable packages from natural and eco-friendly resources. The contribution of nanotechnologies to these goals is reviewed in this chapter, together with a description of portable devices ("lab-on-chip," sensors, nanobalances, etc.) which can be used to assess the quality of food and an overview of regulations in force on food contact materials.

Bacterial culture detection and identification in blood agar plates with an optoelectronic nose

Clinical microbiology automation is currently limited by the lack of an in-plate culture identification system. Using an inexpensive, printed, disposable colorimetric sensor array (CSA) responsive to the volatiles emitted into plate headspace by microorganisms during growth, we report here that not only the presence but the species of bacteria growing in plate was identified before colonies are visible. In 1894 trials, 15 pathogenic bacterial species cultured on blood agar were identified with 91.0% sensitivity and 99.4% specificity within 3 hours of detection. The results indicate CSAs integrated into Petri dish lids present a novel paradigm to speciate microorganisms, well-suited to integration into automated plate handling systems.

The detection of foodborne bacteria on beef: the application of the electronic nose

This study aims to investigate the application of a fast electronic nose system (Cyranose 320) for detecting foodborne bacteria. The system proved to be very efficient in detecting microbes in beef and sausage samples. In the first part of the study, the total viable counts (TVC) from fresh and frozen beef samples were determined using the standard microbiological method and by the application of the electronic nose. The second part applied the electronic nose to beef before and after contamination with different bacterial pathogens separately: E. coli O157: H7, Salmonellatyphimurium 857, Staphylococcus aureus 29213 and Pseudomonas aeruginosa 27853. The results revealed that the Cyranose 320 can detect the TVC in different beef and sausage samples and quantify the volatile organic compounds produced at concentrations from 50 ppb to > 350 ppb. The concentrations of gases collected from the samples before and after separate contamination with these pathogenic bacteria were highly significantly correlated (P < 0.005). From this study one can conclude that the electronic nose system is a rapid way for detecting volatile organic compounds produced by foodborne bacteria that contaminate beef.

The use of colorimetric sensor arrays to discriminate between pathogenic bacteria

A colorimetric sensor array is a high-dimensional chemical sensor that is cheap, compact, disposable, robust, and easy to operate, making it a good candidate technology to detect pathogenic bacteria, especially potential bioterrorism agents like Yersinia pestis and Bacillus anthracis which feature on the Center for Disease Control and Prevention's list of potential biothreats. Here, a colorimetric sensor array was used to continuously monitor the volatile metabolites released by bacteria in solid media culture in an Advisory Committee on Dangerous Pathogen Containment Level 3 laboratory. At inoculum concentrations as low as 8 colony-forming units per plate, 4 different bacterial species were identified with 100% accuracy using logistic regression to classify the kinetic profile of sensor responses to culture headspace gas. The sensor array was able to further discriminate between different strains of the same species, including 5 strains of Yersinia pestis and Bacillus anthracis. These preliminary results suggest that disposable colorimetric sensor arrays can be an effective, low-cost tool to identify pathogenic bacteria.

Invited review article: an odor-sensing system--powerful technique for foodstuff studies

This work examines gas sensor array technology combined with multivariate data processing methods and demonstrates a promising potential for rapid, non-destructive analysis of food. Main attention is focused on detailed description of sensor used in e-nose instruments, construction, and principle of operation of these systems. Moreover, this paper briefly reviews the progress in the field of artificial olfaction and future trends in electronic nose technology, namely, e-nose based on mass spectrometry. Further discussion concerns a comparison of artificial nose with gas chromatography-olfactometry and the application of e-nose instruments in different areas of food industry.

Rapid identification of bacteria with a disposable colorimetric sensing array

Rapid identification of both species and even specific strains of human pathogenic bacteria grown on standard agar has been achieved from the volatiles they produce using a disposable colorimetric sensor array in a Petri dish imaged with an inexpensive scanner. All 10 strains of bacteria tested, including Enterococcus faecalis and Staphylococcus aureus and their antibiotic-resistant forms, were identified with 98.8% accuracy within 10 h, a clinically important time frame. Furthermore, the colorimetric sensor arrays also proved useful as a simple research tool for the study of bacterial metabolism and as an easy method for the optimization of bacterial production of fine chemicals or other fermentation processes.

Metal oxide sensors for electronic noses and their application to food analysis

Electronic noses (E-noses) use various types of electronic gas sensors that have partial specificity. This review focuses on commercial and experimental E-noses that use metal oxide semi-conductors. The review covers quality control applications to food and beverages, including determination of freshness and identification of contaminants or adulteration. Applications of E-noses to a wide range of foods and beverages are considered, including: meat, fish, grains, alcoholic drinks, non-alcoholic drinks, fruits, milk and dairy products, olive oils, nuts, fresh vegetables and eggs.

Meat quality assessment by electronic nose (machine olfaction technology)

Over the last twenty years, newly developed chemical sensor systems (so called "electronic noses") have made odor analyses possible. These systems involve various types of electronic chemical gas sensors with partial specificity, as well as suitable statistical methods enabling the recognition of complex odors. As commercial instruments have become available, a substantial increase in research into the application of electronic noses in the evaluation of volatile compounds in food, cosmetic and other items of everyday life is observed. At present, the commercial gas sensor technologies comprise metal oxide semiconductors, metal oxide semiconductor field effect transistors, organic conducting polymers, and piezoelectric crystal sensors. Further sensors based on fibreoptic, electrochemical and bi-metal principles are still in the developmental stage. Statistical analysis techniques range from simple graphical evaluation to multivariate analysis such as artificial neural network and radial basis function. The introduction of electronic noses into the area of food is envisaged for quality control, process monitoring, freshness evaluation, shelf-life investigation and authenticity assessment. Considerable work has already been carried out on meat, grains, coffee, mushrooms, cheese, sugar, fish, beer and other beverages, as well as on the odor quality evaluation of food packaging material. This paper describes the applications of these systems for meat quality assessment, where fast detection methods are essential for appropriate product management. The results suggest the possibility of using this new technology in meat handling.

Electronic noses in food analysis

Gas sensor array technology combined with multivariate data processing methods as artificial neural network has been demonstrated to have a promising potential for rapid non-destructive analysis of food quality. It may be applicable in quality control of raw material, food processing or products. This technique cannot completely replace reference methods like the use of sensory panels as the technique requires a frequent calibration against some valid reference method. As with all new techniques there remain some basic problems to be solved concerning sample handling and instrumental performance. The emerging research activity in the development of chemical sensors including hardware and software combined with applied research makes it realistic to expect applications with this technique implemented on-line in the food industry in near future. In particular, promising applications on meat seem to be within the field of spoilage, off-flavor, sensory analysis and fermentation processes.