Accurate Differentiation of Green Beans of Arabica and Robusta Coffee Using Nanofluidic Array of Single Nucleotide Polymorphism (SNP) Markers. (20th April 2020)

• Record Type: Journal Article
• Authors: Zhang, Dapeng; Vega, Fernando E; Infante, Francisco; Solano, William; Johnson, Elizabeth S; Meinhardt, Lyndel W
• Is Part Of: Journal of AOAC International. Volume 103:Number 2(2020)
• Page Start: 315
• Page End: 324
• Publication Date: 2020-04-20
• Subjects: Agricultural chemistry -- Periodicals; Food -- Analysis -- Periodicals; 543
• DOI: 10.1093/jaocint/qsz002
• Languages: English
• ISSNs: 1060-3271

Abstract

Abstract: Green (unroasted) coffee is one of the most traded agricultural commodities in the world. The Arabica ( Coffea arabica L.) and Robusta ( Coffea canephora Pierre ex A. Froehner) species are the two main types of coffees for commercial production. In general, Arabica coffee is known to have better quality in terms of sensory characteristics; thus, it has a higher market value than Robusta coffee. Accurate differentiation of green beans of the two species is, therefore, of commercial interest in the coffee industry. Using the newly developed single nucleotide polymorphism (SNP) markers, we analyzed a total of 80 single green bean samples, representing 20 Arabica cultivars and four Robusta accessions. Reliable SNP fingerprints were generated for all tested samples. Unambiguous differentiation between Robusta and Arabica coffees was achieved using multivariate analysis and assignment test. The SNP marker panel and the genotyping protocol are sufficiently robust to detect admixture of green coffee in a high-throughput fashion. Moreover, the multilocus SNP approach can differentiate every single bean within Robusta and 55% of Arabica samples. This advantage, together with the single-bean sensitivity, suggests a significant potential for practical application of this technology in the coffee industry.