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
Production of amylases by fungi under solid-state fermentation is considered the best methodology for commercial scaling that addresses the ever-escalating needs of the worldwide enzyme market. Here response surface methodology (RSM) was used for the optimization of process variables for α-amylase enzyme production from Trichoderma virens using watermelon rinds (WMR) under solid-state fermentation (SSF). The statistical model included four variables, each detected at two levels, followed by model development with partial purification and characterization of α-amylase. The partially purified α-amylase was characterized with regard to optimum pH, temperature, kinetic constant, and substrate specificity. The results indicated that both pH and moisture content had a significant effect (P < 0.05) on α-amylase production (880 U/g) under optimized process conditions at a 3-day incubation time, moisture content of 50%, 30 °C, and pH 6.98. Statistical optimization using RSM showed R values of 0.9934, demonstrating the validity of the model. Five α-amylases were separated by using DEAE-Sepharose and characterized with a wide range of optimized pH values (pH 4.5-9.0), temperature optima (40-60 °C), low Km values (2.27-3.3 mg/mL), and high substrate specificity toward large substrates. In conclusion, this study presents an efficient and green approach for utilization of agro-waste for production of the valuable α-amylase enzyme using RSM under SSF. RSM was particularly beneficial for the optimization and analysis of the effective process parameters.
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Source |
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http://dx.doi.org/10.1007/s12223-021-00929-2 | DOI Listing |
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