Metabolomics fingerprint of Philippine coffee by SPME-GC-MS for geographical and varietal classification

Volatile metabolites of Philippine Arabica and Robusta coffee beans in the both forms standard (not-eaten by the Asian palm civet) and civet coffee grown in different Philippine regions were identified using the hyphenated technique headspace-solid phase microextraction-gas chromatography-mass spectrometry. A great number of volatile metabolites with a wide variety of functional groups were extracted and forty-seven prominent compounds were identified. The volatile metabolomics (volatilomics) fingerprint of Arabica coffees considerably differed with Robusta coffee and geographical origin slightly altered the fingerprint profile of coffee samples. Chemometric analysis such as principal component analysis (PCA) displayed a good classification between Arabica and Robusta coffee samples. Although, Arabica coffee samples from different geographical origins were clustered separately from each other, the proximity of clusters between Arabica coffee samples which can be classified into one large group, indicated their close similarity of headspace metabolites. PCA also identified several key volatile metabolites for the distinction of this group from Robusta coffees which is attributed to the higher amount of acetic acid, furfural, 5-methylfurfural, 2-formylpyrrole, and maltol, and lower concentration of 4-ethylguaiacol and phenol in all Arabica samples. These discriminating metabolites could be useful quality markers to differentiate Arabica with Robusta coffee. Results revealed that the headspace metabolites in coffee provide significant information on its inherent aroma quality. Also, the findings suggested that the overall quality of Philippine coffee is variety and region specific

Geographic origin differentiation of Philippine civet coffee using an Electronic nose

An increasing interest in geographical indication of origin has emerged to achieve legal protection of specialty coffee in international market. Civet coffee which is considered as the most expensive and best specialty coffee in the world, is one of the important indigenous export products of the Philippines. Thus, geographical origin differentiation of Philippine civet coffee and their control coffee beans (not eaten by civet) using electronic nose (E-nose) was performed. The E-nose instrument was based on six semiconductor metal oxide (SMO) sensor array. Results showed that the sensors exhibited different responses towards civet coffees and non-civet (control) coffees of different provenance. Principal component analysis (PCA) and Heirarchical cluster analysis (HCA) demonstrated a clearly separated civet coffees from their control beans. The cluster separation among civet coffee samples indicated that geographic origins dictate the aroma and flavor variations in coffee. This remarkable performance of E-nose provides proof that it is an excellent tool for authentication of the provenance of civet coffee and non-civet coffee samples

Metabolomics Fingerprint of Philippine Coffee by SPME-GCMS for Geographical and Varietal Classification

Headspace metabolites of Philippine Arabica and Robusta coffees grown from different geographical origins were identified using solid-phase microextraction gas chromatography mass spectrometry (SPME-GCMS). A great number of metabolites with a wide variety of functional groups were extracted from two different coffee varieties. About forty prominent metabolites were identified in reference to the NIST spectral database (MS library) and twenty seven of which were confirmed using reference standards. The metabolomics fingerprint of Arabica coffee considerably differs with Robusta coffee and geographical origin slightly alters the fingerprint profile of coffee samples. Chemometric analysis such as principal component analysis (PCA) displays a good classification between Arabica and Robusta coffee samples. Although, Arabica coffee samples from different geographical origins were clustered separately from each other, the proximity of clusters between Arabica coffee samples which can be classified into one large group, indicated their close similarity of headspace metabolites. PCA also identified several key metabolites for the distinction of this group from Robusta coffees which is attributed to the higher amount of maltol, acetic acid, 2-furancarboxaldehyde, 1-H-pyrrole-2-carboxaldehyde and lower concentration of phenol and 4-ethyl-2-methoxyphenol in all Arabica samples. These discriminating compounds could be useful quality markers to differentiate Arabica with Robusta coffee. Results revealed that the headspace metabolites in coffee provides significant information on its inherent aroma quality. Also, the findings suggested that the overall quality of Philippine coffee is variety and region specific

Electronic nose and gas chromatography-mass spectrometry for the Philippine civet coffee discrimination

Civet coffee is recognized as the world's most expensive "gourmet" coffee due to its unique taste and aroma. In this work a concrete and promising approach to the headspace profile aroma attributes of Philippine civet coffee using electronic nose (EN) and gas chromatography-mass spectrometry (GC-MS) with SPME techniques was investigated. Chemometric pattern technique was applied to improve the discrimination of civet coffee against its control coffee beans (not eaten by civet animal). EN analysis has shown that aroma characteristic is one of the most important quality indicators of civet coffee. The result was supported by classical chemical techniques like GC-MS analysis with SPME. The chromatographic fingerprints indicated that civet coffees varied with their control beans in terms of composition and concentration of individual volatile constituents (qualitative and quantitative differences). Chemometric discrimination of EN and GC-MS data demonstrated a clearly separated civet from their control coffees, indicating that cultivar and geographic origins decree the aroma and volatile variations in coffee

Chemometric discrimination of Philippine Civet Coffee using Electronic Nose and Gas Chromatography Mass Spectrometry

This study presents a practical and promising approach to profile the headspace aroma attributes of Philippine civet coffee using electronic nose (E-nose) and gas chromatography mass spectrometry (GCMS). Chemometric pattern method was applied to enhance the discrimination of civet coffee against its control coffee beans (not eaten by civet animal). E-nose analysis revealed that aroma characteristic is one of the most important quality indicators of civet coffee. The result was supported by GCMS analysis. The chromatographic fingerprints indicated that civet coffee differed with their control beans in terms of composition and concentration of individual volatile constituents. Chemometric discrimination of E-nose and GCMS data demonstrated a clearly separated civet from their control coffees indicating that cultivar and geographic origins dictate the aroma and volatiles variations in coffee.Chemometric discrimination of Philippine Civet Coffee using Electronic Nose and Gas Chromatography Mass Spectrometr