Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&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
subsp. () is a quarantine-worthy pest in México. The implementation and validation of new technologies is necessary to reduce the time for bacterial detection in laboratory conditions and Raman spectroscopy is an ambitious technology that has all of the features needed to characterize and identify bacteria. Under controlled conditions a contagion process was induced with , the disease epidemiology was monitored. Micro-Raman spectroscopy (532 nm λ laser) technique was evaluated its performance at assisting on detection through its characteristic Raman spectrum fingerprint. Our experiment was conducted with tomato plants in a completely randomized block experimental design (13 plants × 4 rows). The infection was confirmed by 16S rDNA and plants showed symptoms from 48 to 72 h after inoculation, the evolution of the incidence and severity on plant population varied over time and it kept an aggregated spatial pattern. The contagion process reached 79% just 24 days after the epidemic was induced. Micro-Raman spectroscopy proved its speed, efficiency and usefulness as a non-destructive method for the preliminary detection of . Carotenoid specific bands with wavelengths at 1146 and 1510 cm were the distinguishable markers. Chemometric analyses showed the best performance by the implementation of PCA-LDA supervised classification algorithms applied over Raman spectrum data with 100% of performance in metrics of classifiers (sensitivity, specificity, accuracy, negative and positive predictive value) that allowed us to differentiate from other endophytic bacteria ( and ). The unsupervised KMeans algorithm showed good performance (100, 96, 98, 91 y 100%, respectively).
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6200046 | PMC |
http://dx.doi.org/10.5423/PPJ.OA.02.2018.0019 | DOI Listing |
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