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
In the present study, alfalfa canopy reflectance was researched at alfalfa squaring period under different irrigation amount at the hutubi county grassland ecological station. Determining the spectral diagnostic model of alfalfa leaf moisture content was determined by spectrometry. The results showed that (1) The spectral reflectance of alfalfa canopy gradually decreases with the increase in the leaf water content in the near infrared. (2) The spectral inversion model of alfalfa leaf moisture content established by normalized reflectance spectra is superior to the original reflectance spectra, and the prediction model established in the 1,344-1,660 nm band has the lowest average relative error (7.8%). (3) In this study, the spectral diagnostic model of the leaf moisture content is: Y=0.962 - 7.560X1451 + 5.295X1473. The spectral prediction model of the alfalfa leaf moisture content can provide a basis for decision making for scientific irrigation of alfalfa.
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