Prediction of sensory properties of espresso from roasted coffee samples by near-infrared spectroscopy

Esteban‐Díez, I.; González-Sáiz, J.M.; Pizarro, Consuelo

doi:10.1016/j.aca.2004.08.057

Cited by 107 publications

(69 citation statements)

References 33 publications

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“…Recently, wavelength selection procedures for the multivariate factor based methods of hybrid linear analysis (HLA) [42,97,98] and interactive variable selection for PLS (IVS-PLS) [82,91,[99][100][101] have been discussed in many literatures.…”

Section: Interval Selection Based On Other Methodsmentioning

confidence: 99%

Variables selection methods in near-infrared spectroscopy

Zhang

Zhao

Povey

et al. 2010

Analytica Chimica Acta

861

363

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Section: Interval Selection Based On Other Methodsmentioning

confidence: 99%

Variables selection methods in near-infrared spectroscopy

Zhang

Zhao

Povey

et al. 2010

Analytica Chimica Acta

861

363

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“…high energy and water consumptions) and final product quality (Barreiro et al 2010). Research efforts are being exerted to develop novel, fast, non-destructive and accurate sensing techniques suitable for on-line process optimisation to provide information that is highly correlated to quality properties (Esteban-Diez et al 2004).…”

Section: Introductionmentioning

confidence: 99%

Advanced Characterisation of a Coffee Fermenting Tank by Multi-distributed Wireless Sensors: Spatial Interpolation and Phase Space Graphs

Hernando

Jiménez-Ariza

Díaz-Barcos

et al. 2014

Food Bioprocess Technol

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The fermentation stage is considered to be one of the critical steps in coffee processing due to its impact on the final quality of the product. The objective of this work is to characterise the temperature gradients in a fermentation tank by multi-distributed, low-cost and autonomous wireless sensors (23 semi-passive TurboTag ® radio-frequency identifier (RFID) temperature loggers). Spatial interpolation in polar coordinates and an innovative methodology based on phase space diagrams are used. A real coffee fermentation process was supervised in the Cauca region (Colombia) with sensors submerged directly in the fermenting mass, leading to a 4.6°C temperature range within the fermentation process. Spatial interpolation shows a maximum instant radial temperature gradient of 0.1°C/cm from the centre to the perimeter of the tank and a vertical temperature gradient of 0.25°C/cm for sensors with equal polar coordinates. The combination of spatial interpolation and phase space graphs consistently enables the identification of five local behaviours during fermentation (hot and cold spots).

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“…The results of various instrumental analytical measurements can be related to sensory panel scores. It was shown that chromatograms [7,22,23], various spectra [24][25][26][27] and electropherograms [28] can be employed for prediction of taste attributes in various food samples. These methods are able to predict taste parameters in the analyzed samples due to their high sensitivity towards particular substances responsible for specific taste sensation (e.g.…”

Section: Introductionmentioning

confidence: 99%

Exploring bitterness of traditional Chinese medicine samples by potentiometric electronic tongue and by capillary electrophoresis and liquid chromatography coupled to UV detection

Yaroshenko

Kirsanov

Карцова

et al. 2016

Talanta

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a b s t r a c tInstrumental bitterness assessment of traditional Chinese herbal medicine (TCM) preparations was addressed in this study. Three different approaches were evaluated, high-performance liquid chromatography coupled to UV detector (HPLC), capillary electrophoresis coupled to UV detector (CE) and a potentiometric multisensor system -electronic tongue (ET). Most studies involving HPLC and CE separations use these as selective instruments for quantification of individual substances. However we employed these techniques to provide chromatographic or electrophoretic sample profiles. These profiles are somewhat analogous to the profiles produced by the ET. Profiles from all instruments were then related to professional sensory panel evaluations using projections on latent structures (PLS) regression. It was found that all three methods allow for bitterness assessment in TCM samples in terms of human sensory panel with root mean squared errors of prediction ca. 0.9 within bitterness scale from 0 (no bitterness) to 6 (maximal bitterness).

show abstract

Prediction of sensory properties of espresso from roasted coffee samples by near-infrared spectroscopy

Cited by 107 publications

References 33 publications

Variables selection methods in near-infrared spectroscopy

Variables selection methods in near-infrared spectroscopy

Advanced Characterisation of a Coffee Fermenting Tank by Multi-distributed Wireless Sensors: Spatial Interpolation and Phase Space Graphs

Exploring bitterness of traditional Chinese medicine samples by potentiometric electronic tongue and by capillary electrophoresis and liquid chromatography coupled to UV detection

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