Quantification of coffee blends for authentication of Asian palm civet coffee (Kopi Luwak) via metabolomics: A proof of concept

Jumhawan, Udi; Putri, Sastia Prama; Yusianto,; Bamba, Takeshi; Fukusaki, Eiichiro

doi:10.1016/j.jbiosc.2015.12.008

Cited by 60 publications

(34 citation statements)

References 26 publications

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“…Using metabolomics approach and orthogonal projection to latent structures (OPLS) prediction technique, Jumhawan et al [24] developed two prediction OPL models to quantify the degree of coffee adulteration for certified and commercial luwak coffee with R 2 = 0.975 and R 2 = 0.987, respectively. The scatter plot between actual and predicted luwak content in the best PLS calibration model using SG smoothing spectra is presented in Figure 3.…”

Section: Resultsmentioning

confidence: 99%

The Use of Partial Least Square Regression and Spectral Data in UV-Visible Region for Quantification of Adulteration in Indonesian Palm Civet Coffee

Suhandy

Yulia

2017

International Journal of Food Science

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Asian palm civet coffee or kopi luwak (Indonesian words for coffee and palm civet) is well known as the world's priciest and rarest coffee. To protect the authenticity of luwak coffee and protect consumer from luwak coffee adulteration, it is very important to develop a robust and simple method for determining the adulteration of luwak coffee. In this research, the use of UV-Visible spectra combined with PLSR was evaluated to establish rapid and simple methods for quantification of adulteration in luwak-arabica coffee blend. Several preprocessing methods were tested and the results show that most of the preprocessing spectra were effective in improving the quality of calibration models with the best PLS calibration model selected for Savitzky-Golay smoothing spectra which had the lowest RMSECV (0.039) and highest RPDcal value (4.64). Using this PLS model, a prediction for quantification of luwak content was calculated and resulted in satisfactory prediction performance with high both RPDp and RER values.

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Section: Resultsmentioning

confidence: 99%

The Use of Partial Least Square Regression and Spectral Data in UV-Visible Region for Quantification of Adulteration in Indonesian Palm Civet Coffee

Suhandy

Yulia

2017

International Journal of Food Science

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“…In addition to the normal coffee beans produced by the conventional approach [ 2 ], there are special types obtained from the digestive system of animals, including civet coffee (Kopi Luwak) and elephant dung coffee (Black Ivory Coffee). A few scientific studies on civet coffee have been reported [ 3 , 4 , 5 ], while there are no previous reports on elephant dung coffee. Black Ivory Coffee, or elephant dung coffee, is a brand of coffee exclusively provided by the Black Ivory Coffee Company in Thailand.…”

Section: Introductionmentioning

confidence: 99%

Identification of Volatile Compounds and Selection of Discriminant Markers for Elephant Dung Coffee Using Static Headspace Gas Chromatography—Mass Spectrometry and Chemometrics

et al. 2018

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Elephant dung coffee (Black Ivory Coffee) is a unique Thai coffee produced from Arabica coffee cherries consumed by Asian elephants and collected from their feces. In this work, elephant dung coffee and controls were analyzed using static headspace gas chromatography hyphenated with mass spectrometry (SHS GC-MS), and chemometric approaches were applied for multivariate analysis and the selection of marker compounds that are characteristic of the coffee. Seventy-eight volatile compounds belonging to 13 chemical classes were tentatively identified, including six alcohols, five aldehydes, one carboxylic acid, three esters, 17 furans, one furanone, 13 ketones, two oxazoles, four phenolic compounds, 14 pyrazines, one pyridine, eight pyrroles and three sulfur-containing compounds. Moreover, four potential discriminant markers of elephant dung coffee, including 3-methyl-1-butanol, 2-methyl-1-butanol, 2-furfurylfuran and 3-penten-2-one were established. The proposed method may be useful for elephant dung coffee authentication and quality control.

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“…In contrast to targeted analyses of specific components, non-targeted or wide-targeted analyses by GC/MS are used to investigate many kinds of components and to understand sample characteristics based on component profiles [11]. Metabolomics approaches have been applied not only to soy sauce but also to cheese [12], coffee [13], and other food products [14,15]. In soy sauce research, correlations between hydrophilic low-molecular-weight compounds and dipeptides and sensory profiles have been investigated [16,17].…”

Section: Ofmentioning

confidence: 99%

Component Profiling of Soy-Sauce-Like Seasoning Produced from Different Raw Materials

et al. 2020

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Soy sauce is a traditional Japanese umami seasoning commonly made from soybeans, wheat, and salt water. Soy-sauce-like seasoning, made from other raw materials, such as rice and peas, has recently been developed. However, differences in the taste of soy-sauce-like seasoning, depending on the raw materials, have not been evaluated. Component profiling based on GC/MS combined with a paired comparison test were used to investigate the effect of raw materials on seasoning components and umami taste in five grain-based and four bean-based soy-sauce-like seasonings. In a principal component (PC) analysis, grain-based samples and bean-based samples were separated along the PC1 axis (explaining 48.1% of the total variance). Grain-based samples had a higher saccharide content, and bean-based samples had a higher amino acid content. Furthermore, differences in the umami intensity were also observed among sample types. This is the first detailed metabolomics study of the characteristic compounds and umami of a variety of soy-sauce-like seasonings made from different raw materials.

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Quantification of coffee blends for authentication of Asian palm civet coffee (Kopi Luwak) via metabolomics: A proof of concept

Cited by 60 publications

References 26 publications

The Use of Partial Least Square Regression and Spectral Data in UV-Visible Region for Quantification of Adulteration in Indonesian Palm Civet Coffee

The Use of Partial Least Square Regression and Spectral Data in UV-Visible Region for Quantification of Adulteration in Indonesian Palm Civet Coffee

Identification of Volatile Compounds and Selection of Discriminant Markers for Elephant Dung Coffee Using Static Headspace Gas Chromatography—Mass Spectrometry and Chemometrics

Component Profiling of Soy-Sauce-Like Seasoning Produced from Different Raw Materials

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