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Quantitative structure–retention relationships for mycotoxins and fungal metabolites in LC‐MS/MS
Author(s) -
Ji Caihong,
Li Yanwei,
Su Li,
Zhang Xiaoyun,
Chen Xingguo
Publication year - 2009
Publication title -
journal of separation science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.72
H-Index - 102
eISSN - 1615-9314
pISSN - 1615-9306
DOI - 10.1002/jssc.200900441
Subject(s) - correlation coefficient , mycotoxin , chromatography , test set , mean squared error , chemistry , biological system , mathematics , statistics , food science , biology
Quantitative structure–retention relationship (QSRR) models were used to predict the retention time ( t R ) of mycotoxins and fungal metabolites. Heuristic method and radial basis function neural networks (RBFNN) were utilized to construct the linear and non‐linear QSRR models, respectively. The optimal QSRR model was developed based on a 5‐21‐1 RBFNN architecture using molecular descriptors calculated from molecular structure alone. The RBFNN model gave a square of correlation coefficient ( R 2 ) of 0.8709 and root mean square error of 1.2892 for the test set. This article provided a useful tool for predicting the t R of other mycotoxins when experiment data are unknown.