In vivo Electrochemical Monitoring of Signaling Transduction of Plant Defense Against Stress in Leaves of Aloe vera L.

In situ recording of the voltammetric response of Aloe vera L. leaves using graphite and platinum microelectrodes inserted in the subcuticular region is described. The plant response against the mechanical stress results in changes of the voltammetric signals associated to signal transduction compounds salicylic and jasmonic acids and hydrogen peroxide, which were separately monitored. A kinetic model is proposed to describe the time variation of the respective voltammetric signatures, denoting the possibility of in vivo electrochemical monitoring of biochemical processes in plants. The obtained results suggest that two defense pathways with different participation of ROS are operative.     

Analytical investigation of secondary metabolites extracted from Camellia sinensis L. leaves using a HPLC‐DAD‐ESI/MS data fusion strategy and chemometric methods

Considerable attention has been paid to the study of green tea leaves because of their high consume and beneficial effects on human health. In this work, an appropriate strategy is proposed to investigate and resolve the major metabolites extracted from Camellia sinensis tea leaves. Statistical design mixtures of ethanol, ethyl acetate, dichloromethane, and chloroform were used to study the effects of different solvents and their mixtures on the extraction of the secondary metabolites of C. sinensis tea leaves from two different harvest seasons. Extracted samples were analyzed by high performance liquid chromatography‐diode array detection‐electrospray ionization mass spectrometer allowing the resolution of a large amount of tea metabolites with high relative abundances, especially when their extraction was performed in pure ethanol and with solvent mixtures with ethanol. Resolution of the more relevant metabolites was achieved by the simultaneous analysis of the fused diode array detection and mass spectrometer detectors data from the same samples using the multivariate curve resolution‐alternating least squares chemometric method. Peak areas finally resolved were further analyzed by orthogonal signal correction and partial least squares‐discrimination analysis to discriminate among C. sinensis tea samples. Using the Variable Importance in Projection variable selection method, epigallocatechin and caffeine were finally selected as the two more important chemical constituents of tea leaves that were discriminating more between the tea samples from two different harvest seasons. Copyright © 2016 John Wiley & Sons, Ltd.