SHS-GC-MS applied in <i>Coffea arabica</i> and <i>Coffea canephora</i> blend assessment

Vieira Lyrio, Marcos Valério; Pereira da Cunha, Pedro Henrique; Debona, Danieli Grancieri; Agnoletti, Bárbara Zani; Araújo, Bruno Quirino; Frinhani, Roberta Quintino; Filgueiras, Paulo Roberto; Pereira, Lucas Louzada; Ribeiro de Castro, Eustáquio Vinicius

doi:10.1039/d3ay00510k

Anal. Methods

2023

DOI: 10.1039/d3ay00510k

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SHS-GC-MS applied in Coffea arabica and Coffea canephora blend assessment

Marcos Valério Vieira Lyrio,

Pedro Henrique Pereira da Cunha,

Danieli Grancieri Debona

et al.

Abstract: Considering the great economic significance of Coffea arabica (arabica) associated with lower production cost of C. canephora (conilon), blends of these coffees are commercially available to reduce costs and combine...

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2024

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Cited by 2 publications

References 68 publications

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An overview on the Brazilian Coffea canephora scenario and the current chemometrics-based spectroscopic research

Baqueta,

Diniz,

Pereira

et al. 2024

Food Research International

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An overview on the Brazilian Coffea canephora scenario and the current chemometrics-based spectroscopic research

Baqueta,

Diniz,

Pereira

et al. 2024

Food Research International

View full text Add to dashboard Cite

Quality in beans: tracking and tracing coffee through automation and machine learning

Agnusdei,

Miglietta,

Agnusdei

2024

EMJB

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PurposeCoffee is one of the most consumed beverages in the world and the global coffee industry is worth over $100bn. However, the industry faces significant sustainability challenges. Developing a quality traceability system to select the coffee beans and to ensure their authentication would result in economic advantages, because it allows for fraud to be avoided and increases consumer confidence.Design/methodology/approachTraceability is one of the key elements of sustainability in the coffee sector. The literature reveals that near-infrared (NIR) approaches have a huge potential for gaining rapid information about the origin and properties of coffee beans, without invasive procedures. This study demonstrates the scalability potential of automated methods of manipulation and image acquisition of coffee beans, from experimental scale to industrial lines.FindingsA solution based on the interaction of a manipulation system, a NIR spectrometer acquisition station integrated with a machine learning infrastructure and a compressed air classifier allows for the automatic separation of coffee beans into different classes of origin.Originality/valueApart from traceability, the wide industrialization of this system offers further advantages, including reduced workforce, decreased subjectivity in the evaluation and the acquisition of real-time data for labeling.

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SHS-GC-MS applied in Coffea arabica and Coffea canephora blend assessment

Abstract: Considering the great economic significance of Coffea arabica (arabica) associated with lower production cost of C. canephora (conilon), blends of these coffees are commercially available to reduce costs and combine...

Cited by 2 publications

References 68 publications

An overview on the Brazilian Coffea canephora scenario and the current chemometrics-based spectroscopic research

An overview on the Brazilian Coffea canephora scenario and the current chemometrics-based spectroscopic research

Quality in beans: tracking and tracing coffee through automation and machine learning

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