QSPR Prediction of Chromatographic Retention Times of Tea Compounds by Bioplastic Evolution

Abstract

Structure-property relationships model the ultrahigh-performance liquid chromatographic retention times of tea compounds. Bioplastic evolution presents a viewpoint in evolutionary science. It conjugates the result of acquired characters and associations rising between three rules: evolutionary indeterminacy, morphological determination,andnatural selection. It is used to propose the coordination index, which is utilized to describe the retentions of tea constituents. In molecules, three properties allow computing the coordination descriptor: the molar formation enthalpy, molecular weight, and surface area. The result of dissimilar kinds of characteristics is examined: thermodynamic, steric, geometric, lipophilic, etc. The features are molar formation enthalpy, molecular weight, hydrophobic solvent-accessible surface area, decimal logarithm of the 1-octanol/water partition coefficient, etc. in linear and quadratic associations. The formation enthalpy, molecular weight, hydrophobic surface, partition, etc. differentiate the molecular structures of tea components. Feeble quadratic associations result between partition, hydrophobic surface and retention. The morphological and coordination descriptors complete the associations.

Elemental Classification of Tea Leaves Infusions: Principal Component, Cluster and Meta-analyses

“…Antimicrobial activity of tea tree oil vs. pathogenic bacteria and comparison of its effectiveness with eucalyptus oil, lemongrass oil and conventional antibiotics were informed [26]. Earlier publications in Nereis classified yams [27], lactic acid bacteria (LABs) [28], fruits [29], food spices [30], chlorogenic acids (CGAs) in coffee [31], methylxanthines, cotinine [32], caffeine (caff), its metabolites, nicotine metabolite [33] and tea compounds [34] by PCA, CA and meta-analysis. The main aim of the present report is to develop code learning potentialities, and since tea elements are more naturally described via varying size-structured representation, find general approaches to information processing.…”