Integrated metabolomics of Brazilian canephora coffees: implications on the chemical composition of coffees cultivated in Amazon, Espírito Santo and Bahia

• Grant number: 24/23102-8
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: June 01, 2025
• End date: May 31, 2028
• Field of knowledge: Agronomical Sciences - Food Science and Technology - Food Science
• Principal Investigator: Alessandra Sussulini
• Grantee: Michel Rocha Baqueta
• Host Institution: Instituto de Química (IQ). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil

Abstract

Brazil has stood out for its production of canephora coffee, which is more resistant to climatic variations and diseases than Arabica coffee and has the potential to become the most widely grown coffee in the world. This species is cultivated mainly in Espírito Santo, in the Amazon, by both indigenous and non-indigenous coffee growers, as well as in Bahia. However, there is little knowledge about their chemical composition. Currently, Rondônia and Espírito Santo hold the first registered geographical indications for their canephora coffees in the world. In indigenous areas, coffee is grown in diversified agroforestry systems, intercropped with native species and other food crops, while in other regions traditional cultivation systems predominate. It is known that the botanical varieties (conilon and robusta) and the geographical origin of canephora coffee influence the coffee's characteristics from a chemical point of view, but the chemical compounds responsible for these variations are not yet fully known. In view of this, this study proposes a metabolomic evaluation of the volatile and non-volatile organic compounds present in canephora coffees grown in the Amazon, Espírito Santo and Bahia, with an emphasis on compounds such as caffeine, trigonelline, chlorogenic acids, phenolic acids and sugars. To do this, liquid and gas chromatography techniques coupled with mass spectrometry (LC-MS and GC-MS) will be used. Multivariate analysis will be used to individually investigate the data obtained by each technique in order to identify metabolomic and compositional differences and similarities between canephora coffees. In addition, a multi-block multivariate approach will be applied to integrate the LC-MS and GC-MS data in order to assess the synergy and complementarity of the information.