Untargeted metabolomic approach based on UHPL-ESI-HRMS to investigate metabolic profiles of different Coffea species and terroir

Abstract Coffee ( Coffea spp) has evolved from an agricultural commodity to a specialty beverage, regarding the product’s trading, appreciation, philosophies, and purposes of consumption. Consequently, part of the coffee industry has focused on the sensory complexion and high-quality to meet engaged consumers. To evaluate the chemical profiles and distinctiveness of natural products from plants, metabolomics has emerged as a valuable tool. In this work, we carried out an untargeted metabolomic approach based on reversed-phase liquid chromatography coupled with mass spectrometry, followed by multivariate statistical analysis to obtain the metabolic fingerprints of 21 coffee samples belonging to two species and five botanical varieties, as follows: C. arabica (var. yellow catuai , yellow bourbon , and yellow obata ) and C. canephora (var. conilon , and robusta ). The samples were obtained in the 2022 Edition of the “Brazilian International Conference of Coffee Tasters”, state of Rondônia, Brazil. Principal Component Analysis and Orthogonal Projections Latent Structures Discriminant Analysis were performed using the metabolomic data, resulting in the discrimination of coffee samples based on their chemical profiles. Caffeine, DIMBOA-Gl, roemerine, and cajanin were determined as chemical markers for C. canephora samples, and toralactone, cnidilide, LysoPC(18:2(9Z,12Z)), Lysophosphatidylcholine(16:0/0:0), and 2,3-Dehydrosilybin for C. arabica samples. In addition to the genetic variability, our results show the possible influence of a terroir factor in the production of secondary metabolites of coffee samples, mainly for individuals of C. canephora .