A novel wearable electronic nose for armpit odor analysis is proposed by using a low-cost chemical sensor array integrated in a ZigBee wireless communication system. We report the development of a carbon nanotubes (CNTs)/polymer sensor array based on inkjet printing technology. With this technique both composite-like layer and actual composite film of CNTs/polymer were prepared as sensing layers for the chemical sensor array. The sensor array can response to a variety of complex odors and is installed in a prototype of wearable e-nose for monitoring the axillary odor released from human body. The wearable e-nose allows the classification of different armpit odors and the amount of the volatiles released as a function of level of skin hygiene upon different activities.

https://www.mdpi.com/1424-8220/14/10/19700/pdf

A novel wearable electronic nose for healthcare based on flexible printed chemical sensor array.

A comprehensive review on freshness of fish and assessment: Analytical methods and recent innovations

Background Fishery plays an important role in providing abundant nutrition for consumers as well as in international trade and foreign exchange earner. Due to the abundant endogenous enzymes and psychrophilic bacteria in fish bodies and the fragile organization of fish, fish and fish products are easily perishable and are affected by pre-harvest and postmortem factors, thus decreasing their value. It is thus significant to evaluate fish freshness in an effective and timely manner. Scope and approach In the current review, the principles and applications of novel techniques including enzyme biosensor, electrochemical biosensor, electronic nose, colorimetric sensor, electronic tongue, computer vision techniques, Vis/NIR spectroscopy, HSI spectroscopy and fluorescence spectroscopy as reliable and rapid evaluation tools complementing traditional time-consuming, expensive and cumbersome techniques are highlighted and the advantages and disadvantages of these methods are discussed. Moreover, challenges and future research trends are also proposed. Key findings and conclusions Although recent development of novel technologies has demonstrated their superiority for time-saving, rapid, economic, and even nondestructive and on-line detection of fish freshness, some challenges still remain in optimizing and simplifying bionics techniques, developing algorithms and chemometrics in spectroscopic technologies and improving selectivity and sensitivity in biosensor methods. Further studies are still needed to facilitate the applications of these new evaluation technologies in the fish industry.

Novel techniques for evaluating freshness quality attributes of fish: A review of recent developments

The effect of emodin on cytotoxicity, apoptosis and antioxidant capacity in the hepatic cells of grass carp (Ctenopharyngodon idellus).

A new method was developed to detect fish freshness nondestructively by combining electronic nose (E-nose) and electronic tongue (E-tongue) in conjunction with chemometric methods. An E-nose with nine metal oxide semiconductor gas sensors and a commercial E-tongue were employed in this research. Pseudosciaena crocea stored at 4 °C for different days were used as experimental samples. Total viable counts (TVC) of the fish were detected by the conventional method. E-nose and E-tongue data were analyzed by principal component analysis. Three-layer radial basis function neural network (RBF-NN) models were established for qualitative discrimination of the fish freshness. Performances of RBF-NN models with different numbers of principal components (PCs) as the input were compared. Experimental results revealed that the best RBF-NN model was acquired at seven PCs of E-nose data with an optimal performance of 87.9% and 80.0% in the training set and prediction set respectively. While, the best RBF-NN model of E-tongue data analysis was at five PCs with an optimal performance of 86.3% in the training set and 81.8% in prediction set. Another RBF-NN model was built with the combination of E-nose and E-tongue. The result shows that the discrimination rates improved to 94.0% and 93.9% in the training set and prediction set respectively. A support vector machine regression model was applied to establish a relationship between the combined data from E-nose and E-tongue and from TVC values for quantitative determination. A high correlation was found between the merged data and the parameter of TVC with correlation coefficients more than 0.91. The results proved that, a single system of E-nose and E-tongue was enough to classify samples stored on different days at 4 °C, while a higher discrimination rate was acquired by the combination of the two sensors. The combined system could also be used to quantitatively evaluate the fish freshness. In conclusion, the combined system of E-nose and E-tongue in conjunction with appropriate chemometric analysis methods can conveniently and nondestructively evaluate the freshness of fish stored at 4 °C.

Nondestructive detection of fish freshness during its preservation by combining electronic nose and electronic tongue techniques in conjunction with chemometric analysis

An electronic nose based quality predictive model of grass carp (Ctenopharyngodon idellus) stored at 277 K temperature was proposed in this paper. The changes of sensor array response to samples were caused by the new-generated gas species released by microbial propagations. Principal component analysis method discriminated fresh grass carp samples from medium samples and aged samples. Stochastic resonance signal-to-noise ratio maximums distinguished fresh, medium, and aged grass carp samples successfully. The quality predicting model was developed based on signal-to-noise ratio maximums non-linear fitting regression. Validating experiments demonstrated that the predicting accuracy of this model was 87.5%. This method presented some advantages including easy operation, quick response, high accuracy, good repeatability, etc. This method is promising in aquatic food products quality evaluating applications.

Mo Yanhong

Papers

Study of grass carp (Ctenopharyngodon idellus) quality predictive model based on electronic nose

Study on dynamic stiffness of supporting structure and its influence on vibration of rotors