J.S. Ribeiro
State University of Campinas
14 Papers
18 Citations
J.S. Ribeiro is an academic researcher from State University of Campinas. The author has contributed to research in topics: Chemistry & Partial least squares regression. The author has an hindex of 6, co-authored 12 publications.
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Papers
Chemometric models for the quantitative descriptive sensory analysis of Arabica coffee beverages using near infrared spectroscopy.
TL;DR: Mathematical models based on chemometric analyses of the coffee beverage sensory data and NIR spectra of 51 Arabica roasted coffee samples were generated aiming to predict the scores of acidity, bitterness, flavour, cleanliness, body and overall quality of coffee beverage.
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Prediction of sensory properties of Brazilian Arabica roasted coffees by headspace solid phase microextraction-gas chromatography and partial least squares.
J.S. Ribeiro,Fabio Augusto,Terezinha de Jesus Garcia Salva,R.A. Thomaziello,Márcia M. C. Ferreira +4 more
TL;DR: Calibration models for each sensory attribute based on chromatographic profiles were developed by using partial least squares (PLS) regression and demonstrate the feasibility of using this methodology in on-line or routine applications to predict the sensory quality of unknown Brazilian Arabica coffee samples.
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Chemometric studies for quality control of processed Brazilian coffees using drifts
TL;DR: In this paper, the potential of mid-infrared diffuse reflectance spectroscopy with Fourier transform for discrimination of 29 commercial Brazilian coffee samples with different industrial processing, i.e., caffeine extraction and roasting degree, was evaluated.
Prediction of a wide range of compounds concentration in raw coffee beans using NIRS, PLS and variable selection
TL;DR: In this article, partial least squares regression (PLSR) was used as a multivariate analysis to build the calibration model for each compound using 7, 6 and 5 latent variables, the prediction models constructed for caffeine, trigonelline and 5-CQA contents resulted in a RMSEP of 0.08, 0.07 and 0.27.
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