Ecometabolic mixture design-fingerprints from exploratory multi-block data analysis in Coffea arabica beans from...

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.