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

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.

[1]  R. Carlson,et al.  Design of Experiments, Principles and Applications, L. Eriksson, E. Johansson, N. Kettaneh‐ Wold, C. Wikström and S. Wold, Umetrics AB, Umeå Learnways AB, Stockholm, 2000, ISBN 91‐973730‐0‐1, xii + 329 pp. , 2001 .

[2]  Leandro S. Oliveira,et al.  Physical and chemical attributes of defective crude and roasted coffee beans , 2005 .

[3]  Tormod Næs,et al.  A user-friendly guide to multivariate calibration and classification , 2002 .

[4]  Consuelo Pizarro,et al.  Prediction of sensory properties of espresso from roasted coffee samples by near-infrared spectroscopy , 2004 .

[5]  J. Lopes,et al.  Quality control of pharmaceuticals with NIR: From lab to process line , 2009 .

[6]  J. S. Ribeiro,et al.  Chemometric models for the quantitative descriptive sensory analysis of Arabica coffee beverages using near infrared spectroscopy. , 2011, Talanta.

[7]  Andrea Illy,et al.  Espresso coffee : the science of quality , 2005 .

[8]  Adriana S. Franca,et al.  A comparative study of chemical attributes and levels of amines in defective green and roasted coffee beans , 2007 .

[9]  A. S. Franca,et al.  Discrimination between defective and non-defective Brazilian coffee beans by their volatile profile , 2008 .

[10]  Ana Paula Craig,et al.  Evaluation of the potential of FTIR and chemometrics for separation between defective and non-defective coffees. , 2012, Food chemistry.

[11]  Authentication of Whole and Ground Coffee Beans by near Infrared Reflectance Spectroscopy , 1994 .

[12]  B. Kowalski,et al.  Partial least-squares regression: a tutorial , 1986 .

[13]  Hein Putter,et al.  The bootstrap: a tutorial , 2000 .

[14]  R. Wehrens,et al.  Bootstrapping principal component regression models , 1997 .

[15]  Eric R. Ziegel,et al.  Tsukuba Meeting: Largest Attendance Ever , 2004, Technometrics.

[16]  A. S. Franca,et al.  Physical characterization of non-defective and defective Arabica and Robusta coffees before and after roasting , 2009 .

[17]  A. Farah,et al.  Volatile compounds as potential defective coffee beans' markers. , 2008, Food chemistry.

[18]  Adriana S. Franca,et al.  Composition of green and roasted coffees of different cup qualities , 2005 .

[19]  J. Prodolliet,et al.  Water content determination in green coffee – Method comparison to study specificity and accuracy , 2006 .

[20]  Charles E. Miller,et al.  Chemometrics for on‐line spectroscopy applications—theory and practice , 2000 .

[21]  D. Pot,et al.  Genetics of coffee quality , 2006 .

[22]  M Blanco,et al.  Influence of the procedure used to prepare the calibration sample set on the performance of near infrared spectroscopy in quantitative pharmaceutical analyses. , 2001, The Analyst.

[23]  Santina Romani,et al.  Near infrared spectroscopy: an analytical tool to predict coffee roasting degree. , 2008, Analytica chimica acta.

[24]  Yoshinori Fujimura,et al.  High-Throughput Metabolic Profiling of Diverse Green Coffea arabica Beans Identified Tryptophan as a Universal Discrimination Factor for Immature Beans , 2013, PloS one.

[25]  Heng Tao Shen,et al.  Principal Component Analysis , 2009, Encyclopedia of Biometrics.

[26]  R. Leardi Genetic algorithms in chemometrics and chemistry: a review , 2001 .