A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 176

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016

File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

Determination of HPLC-UV Fingerprints of Spanish Paprika ( L.) for Its Classification by Linear Discriminant Analysis. | LitMetric

AI Article Synopsis

  • The study reports a newly developed HPLC-UV method to analyze and classify the phenolic compounds in Spanish paprika using C reversed-phase chromatography and linear discriminant analysis (LDA).
  • The method involves optimizing extraction procedures through sonication and centrifugation to enhance the quality of the chromatographic data for better classification.
  • A total of 96 paprika samples were analyzed, achieving a perfect classification rate of 100% for the testing group, showcasing the effectiveness of the method in distinguishing different paprika varieties based on their phenolic profiles.

Article Abstract

The development of a simple HPLC-UV method towards the evaluation of Spanish paprika's phenolic profile and their discrimination based on the former is reported herein. The approach is based on C reversed-phase chromatography to generate characteristic fingerprints, in combination with linear discriminant analysis (LDA) to achieve their classification. To this aim, chromatographic conditions were optimized so as to achieve the separation of major phenolic compounds already identified in paprika. Paprika samples were subjected to a sample extraction stage by sonication and centrifugation; extracting procedure and conditions were optimized to maximize the generation of enough discriminant fingerprints. Finally, chromatograms were baseline corrected, compressed employing fast Fourier transform (FFT), and then analyzed by means of principal component analysis (PCA) and LDA to carry out the classification of paprika samples. Under the developed procedure, a total of 96 paprika samples were analyzed, achieving a classification rate of 100% for the test subset (n = 25).

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308838PMC
http://dx.doi.org/10.3390/s18124479DOI Listing

Publication Analysis

Top Keywords

paprika samples
12
linear discriminant
8
discriminant analysis
8
conditions optimized
8
paprika
5
determination hplc-uv
4
hplc-uv fingerprints
4
fingerprints spanish
4
spanish paprika
4
classification
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!