Affordable Access

Publisher Website

Detection of addition of barley to coffee using near infrared spectroscopy and chemometric techniques

Authors
Journal
Talanta
0039-9140
Publisher
Elsevier
Publication Date
Volume
99
Identifiers
DOI: 10.1016/j.talanta.2012.05.036
Keywords
  • Coffee
  • Barley
  • Near Infrared (Nir) Spectroscopy
  • D-Optimal Design
  • Partial Least Squares (Pls) Regression
Disciplines
  • Computer Science
  • Design
  • Mathematics
  • Physics

Abstract

Abstract The current study presents an application of near infrared spectroscopy for identification and quantification of the fraudulent addition of barley in roasted and ground coffee samples. Nine different types of coffee including pure Arabica, Robusta and mixtures of them at different roasting degrees were blended with four types of barley. The blending degrees were between 2 and 20wt% of barley. D-optimal design was applied to select 100 and 30 experiments to be used as calibration and test set, respectively. Partial least squares regression (PLS) was employed to build the models aimed at predicting the amounts of barley in coffee samples. In order to obtain simplified models, taking into account only informative regions of the spectral profiles, a genetic algorithm (GA) was applied. A completely independent external set was also used to test the model performances. The models showed excellent predictive ability with root mean square errors (RMSE) for the test and external set equal to 1.4%w/w and 0.8%w/w, respectively.

There are no comments yet on this publication. Be the first to share your thoughts.