scholarly journals Effective discrimination of flavours and tastes of Chinese traditional fish soups made from different regions of the silver carp using an electronic nose and electronic tongue

2020 ◽  
Vol 38 (No. 2) ◽  
pp. 84-93
Author(s):  
Zhengyi Hu ◽  
Yao Tong ◽  
Anne Manyande ◽  
Hongying Du
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Electronic Nose ◽  
Theoretical Basis ◽  
Silver Carp ◽  
Electronic Tongue ◽  
Principal Component ◽  
Chemical Components ◽  
Sds Page ◽  
Carp Fish

Silver carp is a one of the most important freshwater fish species in China, and is popular when making soup in the Chinese dietary culture. In order to investigate the profile of fish soup tastes and flavours cooked using different regions of the same fish, the silver carp was cut into four different regions: head, back, abdomen, and tail. The differences in taste and flavour of the four kinds of homemade fish soup were investigated by an electronic nose and electronic tongue. The basic chemical components of the different fish regions and the SDS-PAGE profile of the fish soup samples were investigated. Two chemometrics methods (principal component analysis and discriminant factor analysis) were used to classify the odour and taste of the fish soup samples. The results showed that the electronic tongue and nose performed outstandingly in discriminating the four fish soups even though the samples were made from different regions of the same fish. The taste and flavour information of different regions of the silver carp fish could provide the theoretical basis for food intensive processing.<br /><br />

Evaluation of Sweet Sauce Characteristic Taste Based on Electronic Tongue Technology

2012 ◽  
Vol 554-556 ◽  
pp. 1593-1601
Author(s):  
Ming Quan Huang ◽  
Lu Wang ◽  
Bao Guo Sun ◽  
Hong Yu Tian
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Reducing Sugars ◽  
Electronic Tongue ◽  
Amino Nitrogen ◽  
Physicochemical Characterization ◽  
Principal Component ◽  
On Line

A commercial electronic tongue (ET) with specific sensors was applied on taste distinction and physicochemical characterization of seven kinds of sweet sauces. The response signals of ET sensors were analyzed by Principal Component Analysis (PCA) and Discriminant Factor Analysis (DFA). Meanwhile, these signals were transformed into the four relative taste scores (sourness, saltiness, umami and sweetness) by macro operation, followed by comparing with the corresponding four physiochemical indexes (total acids, sodium chloride, amino nitrogen and reducing sugars) which were determined by the methods in GB/T. The results show that ET can be used to distinguish different kinds of sweet sauces according to overall taste. Moreover, the intensity order of taste scores that obtained from ET is basically matched with the sequence of the corresponding physicochemical indexes, which proves that ET technique can be an effective approach to monitor and guarantee the quality of sweet sauce on line.

Detection of the Chinese Rice Wine Using an Electronic Tongue

2014 ◽  
Vol 1044-1045 ◽  
pp. 937-940
Author(s):  
Xiao Li Lu ◽  
Xiao Qing Cai
Keyword(s):  
Neural Network ◽  
Principal Component Analysis ◽  
Artificial Neural Network ◽  
Factor Analysis ◽  
Electronic Tongue ◽  
Principal Component ◽  
Rice Wine ◽  
Chinese Rice Wine ◽  
Artificial Neural Network Ann ◽  
Accuracy Of Prediction

An electronic tongue was employed to detect different brands of Chinese rice wine. The results showed that all of the seven classes of Chinese rice wine can be discriminated by Discriminant Factor Analysis (DFA) and Principal Component Analysis (PCA). Based on Artificial Neural Network (ANN), the electronic tongue can predict the marked age of Chinese rice wine, and the accuracy of prediction was above 90% averagely.

scholarly journals Freshness Evaluation of Three Kinds of Meats Based on the Electronic Nose

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 605 ◽  
Author(s):  
Jun Chen ◽  
Juanhong Gu ◽  
Rong Zhang ◽  
Yuezhong Mao ◽  
Shiyi Tian
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Sensory Evaluation ◽  
Electronic Nose ◽  
Storage Time ◽  
Principal Component ◽  
Component Analysis ◽  
Set Up ◽  
Storage Times

The aim of this study was to use an electronic nose set up in our lab to detect and predict the freshness of pork, beef and mutton. Three kinds of freshness, including fresh, sub-fresh and putrid, was established by human sensory evaluation and was used as a reference for the electronic nose’s discriminant factor analysis. The principal component analysis results showed the electronic nose could distinguish well pork, beef and mutton samples with different storage times. In the PCA figures, three kinds of meats samples all presented an approximate parabola trend during 7 days’ storage time. The discriminant factor analysis showed electronic nose could distinguish and judge well the freshness of samples (accuracy was 89.5%, 84.2% and 94.7% for pork, beef and mutton, respectively). Therefore, the electronic nose is promising for meat fresh detection application.

scholarly journals Metacognitive Rating Scale: A Study Applying a Korean Translation to Individuals with Schizophrenia

2021 ◽  
Vol 18 (13) ◽  
pp. 6853
Author(s):  
Mihwa Han ◽  
Kyunghee Lee ◽  
Mijung Kim ◽  
Youngjin Heo ◽  
Hyunseok Choi
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Mental Status ◽  
Rating Scale ◽  
Anger Expression ◽  
Principal Component ◽  
Negative Beliefs ◽  
Five Factors ◽  
Metacognitive Beliefs

Metacognition is a higher-level cognition of identifying one’s own mental status, beliefs, and intentions. This research comprised a survey of 184 people with schizophrenia to verify the reliability of the metacognitive rating scale (MCRS) with the revised and supplemented metacognitions questionnaire (MCQ) to measure the dysfunctional metacognitive beliefs of people with schizophrenia by adding the concepts of anger and anxiety. This study analyzed the data using principal component analysis and the varimax method for exploratory factor analysis. To examine the reliability of the extracted factors, Cronbach’s α was used. According to the results, reliability was ensured for five factors: positive beliefs about worry, negative beliefs about uncontrollability and danger of worry, cognitive confidence, need for control, and cognitive self-consciousness. The negative beliefs about uncontrollability and danger of worry and the need for control on anger expression, which were both added in this research, exhibited the highest correlation (r = 0.727). The results suggest that the MCRS is a reliable tool to measure the metacognition of people with schizophrenia.

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