Integrated chemometric approach to optimize sample preparation for detecting metabolic changes provoked by abiotic stress in coffea arabica L. leaf fingerprints

Abstract

The effects of water-deficit stress on irrigated and unirrigated field plants of Coffea arabica L. genotype IAPAR 59 were investigated. Plant extracts were obtained following an ethanol-dichloromethane-hexane statistical mixture design. Proton nuclear magnetic resonance (H-1 NMR) fingerprints of the extracts were discriminated using factor analysis (FA) and hierarchical clustering techniques. Extracts from the 1:1:1 ternary mixture presented the largest discriminations compared with those from the pure solvents or their 1:1 binary mixtures. Metabolites resulting from fermentation processes and nutritional deficiencies as well as senescence and abscission precursors such as lactate, arginine and methionine were prevalent in unirrigated plants that can provoke expressive decreases in bean productivity as well as premature plant aging. Amino acids that control regulatory, physiological processes and soil sal inization have higher concentrations in the irrigated plants. The NMR assignments of eighteen substances observed here were confirmed by electrospray ionization mass spectrometry