Accurate Differentiation of Green Beans of Arabica and Robusta Coffee Using Nanofluidic Array of Single Nucleotide Polymorphism (SNP) Markers

Author:

Zhang Dapeng1,Vega Fernando E1,Infante Francisco2,Solano William3,Johnson Elizabeth S4,Meinhardt Lyndel W5

Affiliation:

1. Sustainable Perennial Crops Laboratory, U.S. Department of Agriculture (USDA), Agricultural Research Service (ARS), Beltsville, MD 20705, USA

2. El Colegio de la Frontera Sur (ECOSUR), Carretera Antiguo Aeropuerto Km. 2.5, Tapachula, 30700 Chiapas, Mexico

3. Centro Agronómico Tropical de Investigación y Enseñanza, Turrialba, Costa Rica

4. The Inter-American Institute for Cooperation on Agriculture (IICA), Hope Gardens, Kingston 6, Jamaica

5. Sustainable Perennial Crops Laboratory, USDA, Agricultural Research Service, Beltsville, MD 20705, USA

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.

Publisher

Oxford University Press (OUP)

Subject

Pharmacology,Agronomy and Crop Science,Environmental Chemistry,Food Science,Analytical Chemistry

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