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Evaluation of green coffee beans quality using near infrared spectroscopy: A quantitative approach

Publication . Santos, João Rodrigo; Sarraguça, Mafalda C.; Rangel, António O.S.S.; Lopes, João A.

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.

2012Journal article

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Authenticity control of roasted coffee brands using near-infrared spectroscopy

Publication . Sarraguça, Mafalda Cruz; Santos, João Rodrigo; Rangel, António O. S. S.; Lopes, João Almeida

In this work, a methodology based on near-infrared spectroscopy (NIRS) was exploited in order to discriminate between commercial coffee brands. The main advantages of this approach compared to other strategies (e.g., wet chemistry methods) are its lower cost, less labor, and lower time per analysis. Two commercial brands were discriminated among several others present in the Portuguese market. The chemometric method used to estimate discriminant models was partial least squares discriminant analysis (PLSDA). Results show that it is possible to discriminate coffee brands using this strategy with a correct classification of 100 %. The spectral region, more favorable to discrimination of roasted coffee brands, can be related with differences in the concentrations of compounds, such as, chlorogenic acid and sucrose, and also due to differences on lipid fraction. This methodology is adequate for field implementation, namely, adopting handheld NIRS instruments.

2013Journal article

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