STUDY ON PLANKTON OF DIFFERENT CATEGORIES OF LAKES IN SUMMER BY MEANS OF PRINCIPAL COMPONENT ANALYSIS, FACTOR ANALYSIS AND CLUSTER ANALYSIS

2010 ◽  
Vol 36 (1) ◽  
pp. 43-50
Author(s):  
Luo-Jun GONG ◽  
Shi-Ping ZHANG ◽  
Bang-Xi XIONG ◽  
Ding-Zhu LIU ◽  
Jin-Zhong LI ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Factor Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
And Cluster Analysis

Study on Nitrogen, Phosphor and Chemical Oxygen Demand of Differnt Categories of Aquaculture Lakes by Means of Principal Component Analysis, Factor Analysis and Cluster Analysis

2011 ◽  
Vol 340 ◽  
pp. 369-377 ◽  
Author(s):  
Luo Jun Gong ◽  
Xue Fen Yang ◽  
Bang Xi Xiong ◽  
Gui Ping Li ◽  
Xian Li Chen
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Factor Analysis ◽  
Oxygen Demand ◽  
Score Function ◽  
Principal Component ◽  
Component Analysis ◽  
Cluster Result ◽  
Function Expression ◽  
And Cluster Analysis

The author measured TN, NH4+-N, NO2--N, NO3--N, TP, PO43--P and CODMn of the five aquaculture lakes that is, Liangzi Lake, Futou Lake, Chaipo Lake, Nanhu Lake and Yezhi Lake, in Wuhan in 2007, and had analyzed the results by means of Principal Component Analysis (PCA), Factor Analysis (FA) and Cluster Analysis (CA). The PCA result showed that the two principal components were nutrient factor (including TN, NO2--N, NO3--N, TP, PO43--P and CODMn) and ammonium absorption factor (NH4+-N), with their function expression integrated. The results of FA and PCA were in conformity, with their factor score function expression integrated. R-mode cluster result indicated that the seven hydrochemical indexes could be divided into four categories, i.e. NO3 - -N, TP, TN and NO2--N make up of one category, and another three categories were PO43--P, NH4+-N and CODMn, respectively. Q-mode cluster result showed that the five lakes can be divided into two categories, Futou Lake and Liangzi Lake is one category, and Chaipo Lake, Yezhi Lake and Nanhu Lake is the other, which has been caused by urban waste water, domestic sewage and aquaculture production.

scholarly journals Assessment of Physicochemical Properties of Tequila Brands: Authentication and Quality

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Alejandra Carreon-Alvarez ◽  
Amaury Suárez-Gómez ◽  
Florentina Zurita ◽  
Sergio Gómez-Salazar ◽  
J. Felix Armando Soltero ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Refractive Index ◽  
Physicochemical Properties ◽  
Analysis Of Variance ◽  
Principal Component ◽  
Component Analysis ◽  
Total Variability ◽  
And Cluster Analysis ◽  
Physicochemical Data

Several physicochemical properties were measured in commercial tequila brands: conductivity, density, pH, sound velocity, viscosity, and refractive index. Physicochemical data were analyzed by Principal Component Analysis (PCA), cluster analysis, and the one-way analysis of variance to identify the quality and authenticity of tequila brands. According to the Principal Component Analysis, the existence of 3 main components was identified, explaining the 87.76% of the total variability of physicochemical measurements. In general, all tequila brands appeared together in the plane of the first two principal components. In the cluster analysis, four groups showing similar characteristics were identified. In particular, one of the clusters contains some tequila brands that are not identified by the Regulatory Council of Tequila and do not meet the quality requirements established in the Mexican Official Standard 006. These tequila brands are characterized by having higher conductivity and density and lower viscosity and refractive index, determined by one-way analysis of variance. Therefore, these economical measurements, PCA, and cluster analysis can be used to determinate the authenticity of a tequila brand.

Study on Identification Method of 'Pingli' Gynostemma with Near-Infrared Spectroscopy

2013 ◽  
Vol 781-784 ◽  
pp. 1464-1468
Author(s):  
Xiu Hua Liu ◽  
Xiao Ting Li ◽  
Jing Wang ◽  
Rui Ying Li ◽  
Guang Chen Wu ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Diffuse Reflectance Spectroscopy ◽  
Principal Component ◽  
Component Analysis ◽  
Qualification Testing ◽  
And Cluster Analysis

In order to identify the authentic Pingli Gynostemma, a geographical indication products, diffuse reflectance spectroscopy of Gynostemma came from eight different origins were collected by the Fourier near-infrared spectrometer. The spectroscopy was analyzed with Chemometrics method, and the spectroscopy was pretreated by the vector normalization condition. The range of spectra was 4800-10096 cm-1. The Calibration models of Gynostemma were established by the principal component analysis, qualification testing and cluster analysis, respectively, and each model was verified. The results show that the optimal model established by the principal component analysis, qualification testing and cluster analysis can effectively identify authentic Pingli Gynostemma, and accuracy rate was 100%. In conclusion, Pingli Gynostemma can be identified accurately and quickly by the near-infrared spectroscopy technique.

Study on Identification Method of Zherong Radix Pseudostellariae with Near-Infrared Spectroscopy

2014 ◽  
Vol 989-994 ◽  
pp. 4028-4031
Author(s):  
Yan Ping Pang ◽  
Kun Liu ◽  
Li Ya Xia ◽  
Shao Long Yu
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Diffuse Reflectance Spectroscopy ◽  
Principal Component ◽  
Component Analysis ◽  
Qualification Testing ◽  
And Cluster Analysis

In order to identify the Zherong Radix Pseudostellariae, a geographical indication products, diffuse reflectance spectroscopy of came from ten different origins were collected by the Fourier near-infrared spectrometer. The spectroscopy was analyzed with Chemometrics method,and the spectroscopy was pretreated by the second derivative, first derivation and minus a straight line condition. The range of spectra was 3996.1-7282.5 cm-1. The Calibration models of Radix Pseudostellariae were established by the qualification testing, principal component analysis, and cluster analysis respectively, and each model was verified. The results show that the optimal model established by the qualification testing, principal component analysis and cluster analysis can effectively identify authentic Zherong Radix Pseudostellariae , and accuracy rate was more than 97.5%. In conclusion, Zherong Radix Pseudostellariae can be identified accurately and quickly by the near-infrared spectroscopy technique.

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