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

A Systematic Review on the Impacts of Climate Change on Coffee Agrosystems

“…Simultaneously, [CO 2 ] and irrigation conditions (pertaining to carbohydrates, chlorogenic acids, and caffeine) induce metabolic changes [ 96 ]. The CO 2 factor had a greater influence on the metabolome of Coffea arabica beans than on water availability, resulting in elevated levels of quinic acid/chlorogenic acids, malic acid, and kahweol/cafestol [ 97 ]. The CO 2 -enriched plants were found to contain significantly higher concentrations of phenolic acids and caffeine-like compounds, indicating the successful metabolic adaptation of CO 2 -enriched Arabica coffee beans to future droughts [ 98 ].…”

Comprehensive HPLC fingerprint analysis based on a two-step extraction method for quality evaluation of Perilla frutescens (L.) Britt

“…30,31 Marcheafave et al used a mixture design of four different extraction solvents to maximize the extraction of metabolites from Coffea arabica beans, combined with a specic chemometric method to explore the chemical differences in ecometabolic ngerprints in coffee under climate change. 32 To extract medicinal materials selectively, in addition to the solvent selection, the different techniques and their physical parameters can inuence the extraction results. 33 Lefebvre et al developed a method for the selective sequential extraction of different polar chemical components of rosemary by adjusting the type and proportion of organic modiers in the SFE.…”

1H NMR Mixture Design–Fingerprints and ASCA Analysis in Ilex paraguariensis: Model Stability in Search of a Global Metabolome

“…1 Metabolic fingerprinting research has shown that the chemical domain extracted from plant materials depends on the chemical properties of the extracting solvent and the analytical technique employed to detect the chemical profile. 2,3 Sample preparation is one of the main challenges, as no extractive process guarantees the complete extraction of chemical compounds from plant materials. 4 Different solvents can be expected to extract different but not necessarily disjoint sets of chemical compounds from plant tissues.…”

“…6 The chemical set is registered by spectroscopic or chromatographic techniques, 7 and statistical analysis alternatives can be performed for the chemical compounds of a multivariateoptimized extraction process, 8 passing through unsupervised machine learning for exploratory data analysis and supervised methods. 9,10 Data sets of mixture design−fingerprints, using different solvents in the extraction, have been analyzed simultaneously with PCA, 11 common dimensions analysis (ComDim), 2 exploratory factor analysis (EFA), 12 and partial least-squaresdiscriminant analysis (PLS-DA), 3 among others, as a procedure to maximize the range of metabolites analyzed simultaneously in mathematical modeling. This procedure has been successfully applied for various plant materials, such as Coffea arabica leaves and beans, 6,9 yerba mate leaves, 13 Rollinia mucosa leaves, 14 Mikania laevigata leaves, 15 and several other plant species.…”

“…Data sets of mixture design–fingerprints, using different solvents in the extraction, have been analyzed simultaneously with PCA, common dimensions analysis (ComDim), exploratory factor analysis (EFA), and partial least-squares-discriminant analysis (PLS-DA), among others, as a procedure to maximize the range of metabolites analyzed simultaneously in mathematical modeling. This procedure has been successfully applied for various plant materials, such as Coffea arabica leaves and beans, , yerba mate leaves, Rollinia mucosa leaves, Mikania laevigata leaves, and several other plant species.…”