Full-Length HPLC Signal Clustering and Biomarker Identification in Tomato Plants

Abstract

High resolution HPLC data of a tomato germplasm collection are studied: Analysis of the molecular constituents of tomato peels from 55 experiments is conducted with focus on the visualization of the plant interrelationships, and on biomarker extraction for the identification of new and highly abundant substances at a wavelength of 280nm. 3000-dimensional chromatogram vectors are processed by state-of-the-art and novel methods for baseline correction, data alignment, biomarker retrieval, and data clustering. These processing methods are applied to the tomato data set and the results are presented in a comparative manner, thereby focusing on interesting clusters and retention times of nutritionally valuable tomato lines.