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: 3122
Function: getPubMedXML
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
Fourier transform infrared (FTIR) attenuated total reflectance (ATR) spectroscopy was used in combination with multivariate statistic analysis for identification of soil-borne fungi that causes severe economic damage to agriculture: Fusarium monili forme, Fusarium semitectum, Fusarium oxysporum, Fusarium solani, Rhizoctonia solani, Sclerotinia sclerotiorum, Pythium aphanidermatum and Phytophthora capsici. The original FTIR spectra were normalized, and the second derivatives were calculated, from which the peak wave numbers showing greatest variability were selected: 2924, 2854, 1745, 1641, 1547, 1466, 1406, 1376, 1306, 1240, 1201, 1152, 1109 and 1028 cm(-1). To discriminate different fungal strains, canonical discriminant analysis and cluster analysis were performed at these characteristic wave numbers. Results showed that the classification accuracies achieved 100% for different species of fungi, and classification accuracies for different fusarium strains achieved 95.56%, demonstrating the high potential of this technique for fungi identification.
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