Quantification of  Coffea arabica  and  Coffea canephora var. robusta  concentration in blends by means of synchronous fluorescence and UV-Vis spectroscopies

Dankowska, Anna; Domagała, Anna; Kowalewski, Wojciech

doi:10.1016/j.talanta.2017.05.036

Cited by 70 publications

(33 citation statements)

References 18 publications

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“…14 Among the quantitative studies, Dankowska et al showed fluorescence and UV-visible spectroscopy to have a complementary effect on the quantification of roasted Arabica and Robusta in blends. 15 Among the qualitative studies, UV-visible spectroscopy with PLS-DA and SIMCA has been used to discriminate between pure peaberry and pure normal ground roasted coffee. 16 PLS-DA is the most widely used supervised method for classification in chemometrics.…”

Section: Both Species Differ Not Only In Relation To Their Botanical mentioning

confidence: 99%

Partial least squares with discriminant analysis and UV– visible spectroscopy for qualitative evaluation of Arabica and Robusta coffee in Lampung

Yulia¹,

Asnaning²,

Waluyo

et al. 2018

AIP Conference Proceedings

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Arabica coffee is considered to be of better quality than Robusta coffee. It has superior taste and aroma, better than Robusta coffee. To develop an authentication system for Arabica coffee, it is highly necessary to discriminate between pure Arabica coffee and Arabica adulterated with Robusta coffee. Ground roasted coffee samples are most difficult to discriminate from each other: visual inspection by the naked eye or even machine vision methods becomes very problematic. For this reason, we here propose a relatively new analytical method based on UV-visible spectroscopy for discrimination the pure and adulterated Arabica ground roasted coffee. In this study, 100 samples were used as samples with different degrees of adulteration (0%-60% of Robusta concentration in an Arabica-Robusta coffee blend). Spectral data of samples were acquired using a UV-visible spectrometer in the range of 190-1100 nm (Genesys 10s, Thermo Scientific, USA). Partial least square discriminant analysis (PLS-DA) was applied to discriminate between the pure and adulterated Arabica coffee based on UV-visible spectra data. Several pre-processing spectra were also tested to determine which one provides an appropriate discrimination model. The PLS-DA model has coefficient of correlation 0.89 (R 2 = 0.79) with low Root mean square error of calibration (RMSEC) 0.226. The full-cross validation resulted in Q 2 = 0.74 and low Root mean squared error of cross-validation (RMSECV) 0.254. Using this PLS-DA model, a total rate of correct classification of 97.5% was obtained in the prediction set. In conclusion, UV-visible spectroscopy in tandem with PLS-DA is a promising analytical method for differentiating between pure and adulterated Arabica ground roasted coffee.

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Section: Both Species Differ Not Only In Relation To Their Botanical mentioning

confidence: 99%

Partial least squares with discriminant analysis and UV– visible spectroscopy for qualitative evaluation of Arabica and Robusta coffee in Lampung

Yulia¹,

Asnaning²,

Waluyo

et al. 2018

AIP Conference Proceedings

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“…Zinc hydrometallurgy mainly includes grinding, leaching, purification and electrolysis processes [2]. As the metal zinc ores are often accompanied by copper (Cu) and cobalt (Co) metal ions, so the purification process is a key process to control the concentration of impurity ions [3][4][5][6]. When the concentration of trace amounts of copper and cobalt exceeds production standard, it will seriously affect the electrolytic process, even cause burning plates, and finally seriously affect product quality, production efficiency and energy utilization [7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimized Overlapping Peak Separation Algorithm for Simultaneous Detection of Copper and Cobalt by Ultraviolet-Visible Spectroscopy

Zhou

Zhu

2020

IEEE Access

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In the zinc hydrometallurgy, the excessive impurity ions of copper and cobalt are very harmful to the electrolysis process, which affects product quality and wastes resources. In order to solve the problems of low sensitivity, severe spectral overlap and narrow effective band, an overlapping peak separation algorithm based on multi-objective optimization was proposed for simultaneous detection of copper and cobalt in high concentration zinc solution by ultraviolet-visible spectroscopy. First, according to the characteristics of the spectral signal, the derivative spectroscopy by continuous wavelet transform was used to separate the spectral overlapping peaks of copper and cobalt and shield the zinc interference. Then, taking decomposition scale as decision variable, and the information occupancy and peak separation as the optimization targets, a multi-objective optimization model was established and solved using the particle swarm multi-objective optimization method. Finally, derivative spectroscopy combined with zero-crossing method was used to establish calibration curves for simultaneous detection of copper and cobalt. The experimental results show that the proposed method is suitable for simultaneous detection of trace amounts of copper and cobalt in high concentration zinc solution.

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“…For example, Dankowska et al . 13 demonstrated that fluorescence combined with ultraviolet and visible (UV-Vis) spectroscopies could give a complementary effect for the quantification of roasted Coffea canephora var. robusta and Coffea arabica concentration in blends.…”

Section: Introductionmentioning

confidence: 99%

Differentiation and comparison of Wolfiporia cocos raw materials based on multi-spectral information fusion and chemometric methods

Wang

2018

Sci Rep

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In order to achieve the target of deeper insight into the differentiation and comparison of Wolfiporia cocos, a total of 350 samples including distinct growth patterns, various collection regions and different medicinal parts were investigated using multi-spectral information fusion based on ultraviolet (UV) and Fourier transform infrared (FT-IR) spectroscopies coupled with chemometrics. From the results, the discrimination of samples was obtained successfully and good classification performances were shown according to partial least squares discriminant analysis (PLS-DA) models. Comparatively, the distinctness of chemical information in the two medicinal parts of W. cocos were much more than that in the same part with different growth patterns and collection areas. Meanwhile, an interesting finding suggested that growth patterns rather than geographical origins could be the dominant factor to effect the chemical properties of the same part samples, especially for the epidermis. Compared with the epidermis samples, there were better quality consistency for the inner part of W. cocos. Totally, this study demonstrated that the developed method proved to be reliable to perform comparative analysis of W. cocos. Moreover, it could provide more comprehensive chemical evidence for the critical supplement of quality assessment on the raw materials of W. cocos.

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Quantification of Coffea arabica and Coffea canephora var. robusta concentration in blends by means of synchronous fluorescence and UV-Vis spectroscopies

Cited by 70 publications

References 18 publications

Partial least squares with discriminant analysis and UV– visible spectroscopy for qualitative evaluation of Arabica and Robusta coffee in Lampung

Partial least squares with discriminant analysis and UV– visible spectroscopy for qualitative evaluation of Arabica and Robusta coffee in Lampung

Multi-Objective Optimized Overlapping Peak Separation Algorithm for Simultaneous Detection of Copper and Cobalt by Ultraviolet-Visible Spectroscopy

Differentiation and comparison of Wolfiporia cocos raw materials based on multi-spectral information fusion and chemometric methods

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