Author(s): BAQUETA, M. R.; ALVES, E. A.; VALDERRAMA, P.; PALLONE, J. A. L.

Summary: High-quality Brazilian Canephora coffees are rising to the level of specialty coffees in the face of a new industry perception. In this framework, spectra from 527 coffees were analyzed in the near-infrared (NIR) region. Prin- cipal component analysis distinguished Brazilian Canephora producing states, botanical varieties, low and high- quality Canephora, Canephora and Arabica, and Canephora with geographical indication (GI) from those without GI. Also, Canephora coffee cultivars from Western Brazilian Amazon were distinguished. Three multi-class PLS- DA (traditional, hard, and soft versions) were compared to discriminate 5 classes: Robusta Amaz?onico from traditional (1) and indigenous (2) producers of Rond?onia, Conilon from Espírito Santo (3), Conilon from Bahia (4), and specialty Arabica (5). Binary PLS-DA discriminated GI Canephora and non-GI Canephora with 100% sensitivity and specificity. Carbohydrates, chlorogenic acids, lipids, caffeine, and proteins were dominant ab- sorption bands in coffee classifications. The proposed method is objective, simple, fast, and could be used in the routine analysis of coffee to verify claims of identity, variety, and origin.

Publication year: 2023

Types of publication: Journal article

Unit: Embrapa Rondônia

Keywords: Amazonian robusta, Conilon, Geographical origin, Multivariate classification, NIR spectroscopy, PLS-DA