Vista normal Vista MARC

Accurate differentiation of green beans of arabica and robusta coffee using anofluidic array of single nucleotide polymorphism (SNP) markers

Zhang, Dapeng [autor] | Vega, Fernando E [autor] | Infante, Francisco [autor] | Solano, William [autor] | Johnson, Elizabeth S [autora] | Meinhardt, Lyndel W [autor].
Tipo de material: Artículo en línea Artículo en línea Tipo de contenido: texto Tipo de medio: computadora Tipo de portador: recurso en líneaTema(s): Coffea arabica | Coffea canephora | Polimorfismo de nucleótido simple | Productividad agrícola | Industria del caféTema(s) en inglés: Coffea arabica | Coffea canephora | Single nucleotide polymorphism | Agricultural productivity | Coffee industryNota de acceso: Disponible para usuarios de ECOSUR con su clave de acceso En: Journal of AOAC International. Volumen 103, número 2 (March-April 2020), páginas 315–324. --ISSN: 1944-7922Número de sistema: 60880Resumen:
Inglés

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.

Recurso en línea: https://doi.org/10.1093/jaocint/qsz002
Lista(s) en las que aparece este ítem: Bibliografía DEAMP
Etiquetas de esta biblioteca: No hay etiquetas de esta biblioteca para este título. Ingresar para agregar etiquetas.
Star ratings
    Valoración media: 0.0 (0 votos)
Existencias
Tipo de ítem Biblioteca actual Colección Signatura Estado Fecha de vencimiento Código de barras
Artículos Biblioteca Electrónica
Recursos en línea (RE) 		ECOSUR Recurso digital ECO40000060880

Disponible para usuarios de ECOSUR con su clave de acceso

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. eng

Con tecnología Koha