Background and Objectives
The eating quality of fresh instant rice differ significantly owing to its geographical origins. However, the method of geographical discrimination is still lacking. In this study, the determination of flavor profiles and multivariate statistical analysis have been applied for discriminating the geographical origins of 18 fresh instant rice from three provinces in Northeast China.
Findings
The principal component analysis (PCA) of electronic nose (E‐nose) data could rapidly distinguish the samples from three different provinces. The solid phase microextraction‐gas chromatograph‐mass spectrometer (SPME‐GC‐MS) results of samples from different provinces were clearly distinguished in PCA and hierarchical cluster analysis (HCA). The orthogonal partial least squares discriminant analysis (OPLS‐DA) model showed good discriminating ability (R2 = 0.894, Q2 = 0.845, and accuracy = 1.0). Nonanal, 2,4‐di‐tert‐butylphenol, 2,3‐dihydro‐benzofuran, 2‐pentylfuran, indole, pentadecane, 2‐pentadecanone, trans‐farnesol, isopropyl palmitate, and farnesyl acetone were identified as 10 marker compounds. Moreover, their good discrimination was verified in an additional nine samples.
Conclusions
The strategy of applying flavor profiles for discriminating the geographical origin of fresh instant rice has been proven to be an efficient and non‐destructive method.
Significance and Novelty
Our study is helpful to control the quality of fresh instant rice and provides a methodological reference for the geographical discrimination of foods.
Tourism destination image perception aims to depict the urban tourism image from the perspective of the perception of tourists, which, therefore, sheds new light on the advancement and innovation of urban tourism. The model proposed in this study can effectively describe the image perception of a tourism destination, with its research conclusions providing a vital referential basis for the sustainable development of urban tourism. Combined with LDA, we construct the research framework of tourism destination image perception and then take the online comments of popular scenic spots in Wuhan on Ctrip Travel as an example. The results show that four aspects are included in tourists’ perception of the city image of Wuhan: experience, history culture, leisure service, and tourist destination. Among them, the social network of the experience dimension is most closely related. In addition, emotion analysis illustrates that tourists’ emotional tendencies tend to be positive under the four perceptual dimensions.
AbstractPolyphenylene sulfide (PPS) is easily oxidized at high temperature, which greatly limits its applications. In this study, a nano-SiO2 compound antioxidant (SiO2-g-AO) was prepared and incorporated into PPS by melt compounding to obtain PPS/SiO2-g-AO composites. SiO2-g-AO was prepared by reacting 3-(3,5-di-tert-butyl-4-hydroxyphenyl) (antioxidant AO) with an aminosilane coupling agent (KH792). Fourier transform infrared (FTIR) spectroscopy, energy dispersive spectroscopy (EDS) and thermogravimetric analysis (TGA) confirmed that the antioxidant AO was successfully immobilized on the surface of SiO2 and the thermal stability was improved. Scanning electron microscopy (SEM) images showed that SiO2-g-AO was uniformly dispersed in PPS. It has been found that the crystallinity and mechanical properties of PPS composites improved, and the dynamic oxidation induction temperature (OIT) increased in the range of 16.7°C–21.1°C. A synergistic anti-oxidation model of nanoparticles and antioxidants, namely a multi-stage antioxidant system, was established by comprehensive analysis of experimental results. The synergistic anti-oxidation model provides a new idea for the antioxidant modification of polymer composites.
Abstract. With the development of market economy, the management system of power supply enterprise gradually improved, and the "line loss rate", which affects its comprehensive technical and economic indicators, is becoming increasingly significant, especially driven by the interests, criminals use a variety of high-tech methods to steal electricity than caused the high rate of line loss. In this paper, a method that analysis the user exception data and monitor the key users using electricity information acquisition and analysis platform based on SG186 system is proposed. This method provides a guarantee to achieve the goal of the user's electricity information management and building a green grid.
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