Unknown

Dataset Information

0

16-O-methylcafestol is present in ground roast Arabica coffees: Implications for authenticity testing.


ABSTRACT: High-field and low-field proton NMR spectroscopy were used to analyse lipophilic extracts from ground roast coffees. Using a sample preparation method that produced concentrated extracts, a small marker peak at 3.16?ppm was observed in 30 Arabica coffees of assured origin. This signal has previously been believed absent from Arabicas, and has been used as a marker for detecting adulteration with robusta. Via 2D 600?MHz NMR and LC-MS, 16-O-methylcafestol and 16-O-methylkahweol were detected for the first time in Arabica roast coffee and shown to be responsible for the marker peak. Using low-field NMR, robusta in Arabica could be detected at levels of the order of 1-2%?w/w. A surveillance study of retail purchased "100% Arabica" coffees found that 6 out of 60 samples displayed the 3.16?ppm marker signal to a degree commensurate with adulteration at levels of 3-30%?w/w.

SUBMITTER: Gunning Y 

PROVIDER: S-EPMC5774150 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

altmetric image

Publications

16-O-methylcafestol is present in ground roast Arabica coffees: Implications for authenticity testing.

Gunning Yvonne Y   Defernez Marianne M   Watson Andrew D AD   Beadman Niles N   Colquhoun Ian J IJ   Le Gall Gwénaëlle G   Philo Mark M   Garwood Hollie H   Williamson David D   Davis Aaron P AP   Kemsley E Kate EK  

Food chemistry 20171211


High-field and low-field proton NMR spectroscopy were used to analyse lipophilic extracts from ground roast coffees. Using a sample preparation method that produced concentrated extracts, a small marker peak at 3.16 ppm was observed in 30 Arabica coffees of assured origin. This signal has previously been believed absent from Arabicas, and has been used as a marker for detecting adulteration with robusta. Via 2D 600 MHz NMR and LC-MS, 16-O-methylcafestol and 16-O-methylkahweol were detected for t  ...[more]

Similar Datasets

| S-EPMC7309026 | biostudies-literature
| S-EPMC5960070 | biostudies-literature
| S-EPMC7492344 | biostudies-literature
| S-EPMC8415594 | biostudies-literature
| S-EPMC8750839 | biostudies-literature
| S-EPMC4664423 | biostudies-literature
2023-12-31 | GSE221086 | GEO
| S-EPMC8343811 | biostudies-literature
| S-EPMC6115996 | biostudies-literature
| S-EPMC9149555 | biostudies-literature