A PHP Error was encountered

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: 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

Comparative analysis of prediction models for methane potential based on spent edible fungus substrate. | LitMetric

In this study, ten spent edible fungus (SEF) with different compositional features were used for the maximum methanogenic potential (P) evaluation, and the prediction models including regression and kinetics based on this were developed separately. The results showed that the regression model with more chemical components had a good correlation with the P, and at least three chemical compositions could reach the threshold of sensitivity. The Cone model showed the best fitting effect on P in all kinetic models, which had higher R-square (>0.994) and lower error (1.004-5.672%). Meanwhile, the minimum digestive testing time (14 days) was determined by the evaluation of sensitivity via statistical indicators. It is concluded that the determination of the prediction model of P should be evaluated with the combination of statistical indicators and specific requirements.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.biortech.2020.124052DOI Listing

Publication Analysis

Top Keywords

prediction models
8
spent edible
8
edible fungus
8
statistical indicators
8
comparative analysis
4
analysis prediction
4
models methane
4
methane potential
4
potential based
4
based spent
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!