Penaeus orientolis prawn freshness rapid determination method based on electronic nose and non-linear stochastic resonance technique

Effects of Annona muricata Extract on Trypsin, Cathepsin B and Collagenase Activities and Textural Changes in Chilled Macrobrachium rosenbergii

Texture is an important sensory attribute for overall quality and consumer acceptance of prawns. However, texture is affected during cold storage due to the proteolytic activity of endogenous proteases, resulting in poor quality and a short shelf life. The objective of this study is to determine the inhibitory effects of Annona muricata leaves extract (AMLE) (0, 3, 10 and 20%) on the trypsin, cathepsin B and collagenase activities extracted from the cephalothorax of Macrobrachium rosenbergii. In addition, the textural changes in M. rosenbergii during 20 days of cold storage (4 °C) were also determined. M. rosenbergii were soaked in four different treatments: 0, 3, 10 and 20% AMLE and 1.25% sodium metabisulphate for 10 min at 4 °C. Protease activity was significantly (p < 0.05) reduced at 10 and 20% AMLE. Similarly, cathepsin B showed a significant (p < 0.05) low after treatment at 20% AMLE. The maximum inhibitory activity of trypsin was achieved at 20% AMLE and the standard inhibitor (Tosyl-L-lysyl-chloromethane hydrochloride (TLCK)) compared to the control. Whereas, the lowest collagenase activity was obtained at 20% AMLE compared to the control. These inhibitory effects further maintain the firmness of M. rosenbergii coated with 20% AMLE up to the eighth day of storage when compared to the control. Meanwhile, the highest penetration work was found in the M. rosenbergii coated with 20% AMLE at the twentieth day of storage. In conclusion, treatment at 20% AMLE could be used as a natural preservative to inhibit protease, trypsin and collagenase activity of M. rosenbergii and thus can maintain firmness for up to 8 days of storage.

Analysis of volatile organic compounds and metabolites of three cultivars of asparagus (Asparagus officinalis L.) using E-nose, GC-IMS, and LC-MS/MS

Asparagus (A. officinalis L.) is a perennial herb of the genus Asparagus that is rich in nutrients. This study aimed to distinguish three cultivars of asparagus (Paladin, Grace, and Jinggang red) based on their volatile organic compounds (VOCs) and metabolic profiles. VOCs in the three cultivars were separated and identified using electronic nose (E-nose) and gas chromatography–ion mobility spectrometry (GC–IMS). Differences in metabolites among the three cultivars were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). E-nose and GC-IMS showed that the VOCs in asparagus differed significantly among the three groups. E-nose result showed that purple asparagus (Jinggang red) was connected to a stronger earthy odor; green asparagus (Paladin and Grace) were shown characteristic dill flavor. Moreover, 50 VOCs were detected by using GC–IMS. Ketones and alcohols were most abundant in Paladin; methyl benzoate and dimethyl sulfide were most abundance in Grace; aldehydes and acids were most abundance in Jinggang red. Moreover, 130 and 71 different metabolites were detected in the positive and negative modes among three cultivars, such as quercetin and rutin. Functional analysis revealed that these metabolites were involved in beta-alanine metabolism and ATP-binding cassette (ABC) transporters. In summary, E-nose combined with GC-IMS and LC-MS/MS methods has good application prospects in evaluating and identifying VOCs and metabolites of different cultivars of asparagus. The identified VOCs and metabolites can provide guidelines for the development of functional asparagus products.

Application of Electronic Nose Systems on Animal-Source Food

Electronic nose, which is designed to perceive artificially the odour-active molecules in a sample headspace, has seen an increased use in the food industry as a rapid and reliable tool for quality assessment, classification, and authentication of several food items. The use of chemometrics and pattern recognition methods, together with gas sensors, emerged to be a very powerful analytical approach. In this chapter, an overview of the recent achievements in the field of electronic nose applications on animal-source food is given. Moreover, the authors deal with the recent research trends to overcome the actual sensor shortcomings, including sensor fusion techniques and their applications to evaluate animal-source foods and novel electronic nose systems.

Study of detecting mechanism of carbon nanotubes gas sensor based on multi-stable stochastic resonance model

The detecting mechanism of carbon nanotubes gas sensor based on multi-stable stochastic resonance (MSR) model was studied in this paper. A numerically stimulating model based on MSR was established. And gas-ionizing experiment by adding electronic white noise to induce 1.65 MHz periodic component in the carbon nanotubes gas sensor was performed. It was found that the signal-to-noise ratio (SNR) spectrum displayed 2 maximal values, which accorded to the change of the broken-line potential function. The experimental results of gas-ionizing experiment demonstrated that periodic component of 1.65 MHz had multiple MSR phenomena, which was in accordance with the numerical stimulation results. In this way, the numerical stimulation method provides an innovative method for the detecting mechanism research of carbon nanotubes gas sensor.