Multivariate Assessment of Ground Coffee Samples from Bahia, Brazil on the Basis of Mineral Composition
Year: 2025
Type: article
Abstract: This study determined metals in ground coffee samples from different producing regions in Bahia and used Principal Component Analysis (PCA) and Kohonen neural networks as multivariate techniques to assess sample similarity based on their mineral composition. The samples were prepared using a decomposition method with dilute acid and hydrogen peroxide in a closed system under high pressure. Microwave Induced Plasma Optical Emission Spectrometry (MIP OES) was used to quantify the elements Al, Co, Cr, Cu, Fe, Mn, Ni, V and Zn. For all samples, the elements with the highest concentrations were Mn, Fe, Al, Zn and Cu; and the lowest concentrations were obtained for the elements Cr, Ni, Co and V. The results of this study provide and aggregate relevant nutritional information about coffee produced in the Southwest and Chapada Diamantina regions of Bahia.
Authors: Naiara Brandão, Priscilla da Rocha, Victor Amazonas, Wilson Rocha, Nuno Nascimento, Marcio dos Santos, Allison Silva, Erik da Silva, Marcos Bezerra, Cleber Novaes
Institution: Instituto Federal da Bahia
Language: English
Topic: Heavy Metals in Plants
Subfield: Analytical Chemistry
Field: Chemistry
Domain: Physical Sciences
SDG: Zero hunger
Open Access status: diamond
Awards: G29316538, G6461375938, G6756993358
OpenAlex ID: W4413825087