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Evaluation of green coffee beans quality using near infrared spectroscopy: a quantitative approach.
Food Chem. 2012 Dec 01; 135(3):1828-35.FC

Abstract

Characterisation of coffee quality based on bean quality assessment is associated with the relative amount of defective beans among non-defective beans. It is therefore important to develop a methodology capable of identifying the presence of defective beans that enables a fast assessment of coffee grade and that can become an analytical tool to standardise coffee quality. In this work, a methodology for quality assessment of green coffee based on near infrared spectroscopy (NIRS) is proposed. NIRS is a green chemistry, low cost, fast response technique without the need of sample processing. The applicability of NIRS was evaluated for Arabica and Robusta varieties from different geographical locations. Partial least squares regression was used to relate the NIR spectrum to the mass fraction of defective and non-defective beans. Relative errors around 5% show that NIRS can be a valuable analytical tool to be used by coffee roasters, enabling a simple and quantitative evaluation of green coffee quality in a fast way.

Authors+Show Affiliations

CBQF/Escola Superior de Biotecnologia, Universidade Católica Portuguesa, Rua Dr. António Bernardino de Almeida, 4200-072 Porto, Portugal.No affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Evaluation Study
Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

22953929

Citation

Santos, João Rodrigo, et al. "Evaluation of Green Coffee Beans Quality Using Near Infrared Spectroscopy: a Quantitative Approach." Food Chemistry, vol. 135, no. 3, 2012, pp. 1828-35.
Santos JR, Sarraguça MC, Rangel AO, et al. Evaluation of green coffee beans quality using near infrared spectroscopy: a quantitative approach. Food Chem. 2012;135(3):1828-35.
Santos, J. R., Sarraguça, M. C., Rangel, A. O., & Lopes, J. A. (2012). Evaluation of green coffee beans quality using near infrared spectroscopy: a quantitative approach. Food Chemistry, 135(3), 1828-35. https://doi.org/10.1016/j.foodchem.2012.06.059
Santos JR, et al. Evaluation of Green Coffee Beans Quality Using Near Infrared Spectroscopy: a Quantitative Approach. Food Chem. 2012 Dec 1;135(3):1828-35. PubMed PMID: 22953929.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Evaluation of green coffee beans quality using near infrared spectroscopy: a quantitative approach. AU - Santos,João Rodrigo, AU - Sarraguça,Mafalda C, AU - Rangel,António O S S, AU - Lopes,João A, Y1 - 2012/07/01/ PY - 2012/01/10/received PY - 2012/06/08/revised PY - 2012/06/15/accepted PY - 2012/9/8/entrez PY - 2012/9/8/pubmed PY - 2013/2/7/medline SP - 1828 EP - 35 JF - Food chemistry JO - Food Chem VL - 135 IS - 3 N2 - Characterisation of coffee quality based on bean quality assessment is associated with the relative amount of defective beans among non-defective beans. It is therefore important to develop a methodology capable of identifying the presence of defective beans that enables a fast assessment of coffee grade and that can become an analytical tool to standardise coffee quality. In this work, a methodology for quality assessment of green coffee based on near infrared spectroscopy (NIRS) is proposed. NIRS is a green chemistry, low cost, fast response technique without the need of sample processing. The applicability of NIRS was evaluated for Arabica and Robusta varieties from different geographical locations. Partial least squares regression was used to relate the NIR spectrum to the mass fraction of defective and non-defective beans. Relative errors around 5% show that NIRS can be a valuable analytical tool to be used by coffee roasters, enabling a simple and quantitative evaluation of green coffee quality in a fast way. SN - 1873-7072 UR - https://www.unboundmedicine.com/medline/citation/22953929/Evaluation_of_green_coffee_beans_quality_using_near_infrared_spectroscopy:_a_quantitative_approach_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S0308-8146(12)01032-1 DB - PRIME DP - Unbound Medicine ER -