Ecometabolic mixture design-fingerprints from exploratory multi-block data analysis in Coffea arabica beans from climate changes: Elevated carbon dioxide and reduced soil water availability

Abstract

Ecometabolic mixture design-fingerprinting in coffee cultivated under climate change was chemically explored using ComDim. Multi-blocks were formed using UV, NIRS, 1H NMR, SWV, and FT-IR data. ComDim investigated all these different fingerprints according to the extractor solvent and in virtue of atmospheric CO2 increase. Ethanol and ethanol-dichloromethane showed the best separations due to CO2 environment. 1H NMR loading indicate increases of fatty acids, caffeine, trigonelline, and glucose in beans under current CO2 levels, whereas quinic acid/chlorogenic acids, malic acid, and kahweol/cafestol increased in beans under elevated CO2 conditions. SWV indicated quercetin and chlorogenic acid as important compounds in coffee beans cultivated under current and elevated CO2, respectively. Based on the ethanol and ethanol-dichloromethane fingerprints, k-NN correctly classified the beans cultivated under different carbon dioxide environments and water availabilities, confirming the existence of metabolic changes due to climate changes. SWV proved to be promising compared with widely used spectrometric methods.