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
To fully exploit selenium-rich land resources and ensure crop safety, the phenomenon of "double high" of Se and heavy metals in reclaimed soil of mining wasteland was studied. Soil and maize samples collected from "point-to-point" were weighted by the inverse distance weighted (IDW) method; multiple linear regression (MLR), partial least squares regression (PLSR), random forest regression (RFR), and other methods were used to predict selenium uptake by maize in a sulfur mine reclamation area in southwest China. Meanwhile, the antagonistic effects of selenium (Se) on heavy metals (Hg, As, Cd, and Cr) were analyzed. The results showed that the soil in the study area was rich in selenium resources. The average Se content in the soil reached 0.83 mg·kg, which was 2.87 times that of the average Se content in Chinese soil. The Se content in maize grains ranged from 0.02 mg·kg to 0.16 mg·kg. According to correlation analysis and model prediction, the main influencing factors of selenium content in maize grains in the study area were soil selenium, pH value, organic matter, and heavy metal As. Multivariate linear regression (MLR) was the most effective method for predicting selenium content in maize grains, and the determinant coefficient was 0.52. By comparing the enrichment characteristics of maize to heavy metals (Hg, As, Cd, and Cr) under different concentration gradients of Se in the soil of the study area, the results showed that Se had antagonistic effects on Hg, As, Cd, and Cr. The results can provide a basis for the development of selenium-rich agriculture in similar mining wasteland reclamation in the future.
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Source |
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http://dx.doi.org/10.13227/j.hjkx.201910034 | DOI Listing |
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