Presentation is loading. Please wait.

Presentation is loading. Please wait.

Journal of Food and Drug Analysis

Published byLindsay Carson Modified over 6 years ago

Similar presentations

Presentation on theme: "Journal of Food and Drug Analysis"— Presentation transcript:

1 Journal of Food and Drug Analysis
Comprehensive analysis of Polygoni Multiflori Radix of different geographical origins using ultra-high-performance liquid chromatography fingerprints and multivariate chemometric methods  Li-Li Sun, Meng Wang, Hui-Jie Zhang, Ya-Nan Liu, Xiao-Liang Ren, Yan-Ru Deng, Ai-Di Qi  Journal of Food and Drug Analysis  DOI: /j.jfda Copyright © Terms and Conditions

2 Figure 1 UPLC–PDA chromatographic fingerprints at 260 nm of 24 samples from six different geographical regions as listed in Table 1. PDA = photodiode array detection; UPLC = ultra-high-performance liquid chromatograph. Journal of Food and Drug Analysis DOI: ( /j.jfda ) Copyright © Terms and Conditions

3 Figure 2 MCR–ALS results of chromatographic segment k. (A) The resolved elution profiles of augmented MCR–ALS, (B) pure elution profile of sample AH11, and (C) the resolved spectral profiles. ALS = alternating least squares; MCR = multivariate curve resolution. Journal of Food and Drug Analysis DOI: ( /j.jfda ) Copyright © Terms and Conditions

4 Figure 3 Two-dimensional PCA score plot (PC1 vs. PC2) of all chromatographic fingerprints of Polygoni Multiflori Radix samples as listed in Table 1. PCA = principal component analysis. Journal of Food and Drug Analysis DOI: ( /j.jfda ) Copyright © Terms and Conditions

5 Figure 4 The variance-weighted distances between cluster centers of (A) 72 Polygoni Multiflori Radix samples and (B) 22 components obtained from Ward's method. Journal of Food and Drug Analysis DOI: ( /j.jfda ) Copyright © Terms and Conditions

6 Figure 5 Kohonen map of 72 samples. (A) Distribution of 72 Polygoni Multiflori Radix samples on the map and (B) assigned group distribution on the map. Journal of Food and Drug Analysis DOI: ( /j.jfda ) Copyright © Terms and Conditions

7 Figure 6 The weights of five main vectors in each class obtained from CP-ANN analysis. (A) Cluster I, (B) Cluster II, (C) Cluster III, and (D) Cluster IV. CP-ANN = counter-propagation artificial neural network. Journal of Food and Drug Analysis DOI: ( /j.jfda ) Copyright © Terms and Conditions

8 Journal of Food and Drug Analysis DOI: (10.1016/j.jfda.2016.11.009)
Copyright © Terms and Conditions

Download ppt "Journal of Food and Drug Analysis"

Similar presentations

Self-Organizing Map (SOM) = Kohonen Map

Self-Organizing Map (SOM) = Kohonen Map
Artificial Neural Networks

Artificial Neural Networks
A Comprehensive Study on Third Order Statistical Features for Image Splicing Detection Xudong Zhao, Shilin Wang, Shenghong Li and Jianhua Li Shanghai Jiao.

A Comprehensive Study on Third Order Statistical Features for Image Splicing Detection Xudong Zhao, Shilin Wang, Shenghong Li and Jianhua Li Shanghai Jiao.
Initial estimates for MCR-ALS method: EFA and SIMPLISMA

Initial estimates for MCR-ALS method: EFA and SIMPLISMA
I.1 ii.2 iii.3 iv.4 1+1=. i.1 ii.2 iii.3 iv.4 1+1=

I.1 ii.2 iii.3 iv.4 1+1=. i.1 ii.2 iii.3 iv.4 1+1=
PATTERN RECOGNITION : PRINCIPAL COMPONENTS ANALYSIS Prof.Dr.Cevdet Demir

PATTERN RECOGNITION : PRINCIPAL COMPONENTS ANALYSIS Prof.Dr.Cevdet Demir
I.1 ii.2 iii.3 iv.4 1+1=. i.1 ii.2 iii.3 iv.4 1+1=

I.1 ii.2 iii.3 iv.4 1+1=. i.1 ii.2 iii.3 iv.4 1+1=
Projection methods in chemistry Autumn 2011 By: Atefe Malek.khatabi M. Daszykowski, B. Walczak, D.L. Massart* Chemometrics and Intelligent Laboratory.

Projection methods in chemistry Autumn 2011 By: Atefe Malek.khatabi M. Daszykowski, B. Walczak, D.L. Massart* Chemometrics and Intelligent Laboratory.
The Tutorial of Principal Component Analysis, Hierarchical Clustering, and Multidimensional Scaling Wenshan Wang.

The Tutorial of Principal Component Analysis, Hierarchical Clustering, and Multidimensional Scaling Wenshan Wang.
Chapter 2 Dimensionality Reduction. Linear Methods

Chapter 2 Dimensionality Reduction. Linear Methods
Metabolomics 5/2/2014. ‘Omics Family Tree W. M. Claudino, et al., Journal of Clinical Oncology, 2007, 25(19), pp. 2840-2846 5/2/2014.

Metabolomics 5/2/2014. ‘Omics Family Tree W. M. Claudino, et al., Journal of Clinical Oncology, 2007, 25(19), pp /2/2014.
Line detection Assume there is a binary image, we use F(ά,X)=0 as the parametric equation of a curve with a vector of parameters ά=[α 1, …, α m ] and X=[x.

Line detection Assume there is a binary image, we use F(ά,X)=0 as the parametric equation of a curve with a vector of parameters ά=[α 1, …, α m ] and X=[x.
Place, date, unit, occasion etc. Slide 1 Nikoline Juul Nielsen, Post Doc Soil and Environmental Chemistry (present) Bioorganic Chemistry (previous) Exploratory.

Place, date, unit, occasion etc. Slide 1 Nikoline Juul Nielsen, Post Doc Soil and Environmental Chemistry (present) Bioorganic Chemistry (previous) Exploratory.
CLASSIFICATION. Periodic Table of Elements 1789 Lavosier 1869 Mendelev.

CLASSIFICATION. Periodic Table of Elements 1789 Lavosier 1869 Mendelev.
In the name of GOD. Zeinab Mokhtari 1-Mar-2010 In data analysis, many situations arise where plotting and visualization are helpful or an absolute requirement.

In the name of GOD. Zeinab Mokhtari 1-Mar-2010 In data analysis, many situations arise where plotting and visualization are helpful or an absolute requirement.
PATTERN RECOGNITION : PRINCIPAL COMPONENTS ANALYSIS Richard Brereton

PATTERN RECOGNITION : PRINCIPAL COMPONENTS ANALYSIS Richard Brereton
1 Statistics & R, TiP, 2011/12 Multivariate Methods  Multivariate data  Data display  Principal component analysis Unsupervised learning technique 

1 Statistics & R, TiP, 2011/12 Multivariate Methods  Multivariate data  Data display  Principal component analysis Unsupervised learning technique 
Multivariate statistical methods. Multivariate methods multivariate dataset – group of n objects, m variables (as a rule n>m, if possible). confirmation.

Multivariate statistical methods. Multivariate methods multivariate dataset – group of n objects, m variables (as a rule n>m, if possible). confirmation.
Primary Small Cell Carcinoma of the Esophagus Jima Lv, MD, Jun Liang, MD, Jinwan Wang, MD, Luhua Wang, MD, Jie He, MD, Zefen Xiao, MD, Weibo Yin, MD Journal.

Primary Small Cell Carcinoma of the Esophagus Jima Lv, MD, Jun Liang, MD, Jinwan Wang, MD, Luhua Wang, MD, Jie He, MD, Zefen Xiao, MD, Weibo Yin, MD Journal.
Date of download: 6/21/2016 Copyright © 2016 SPIE. All rights reserved. Cellular and functional characterization of hepatocyte cells at the last stage.

Date of download: 6/21/2016 Copyright © 2016 SPIE. All rights reserved. Cellular and functional characterization of hepatocyte cells at the last stage.

Similar presentations

Ads by Google