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Investigating sensory-classified roasted arabica coffee with GC x GC-TOFMS and chemometrics to understand potato taste defect
被引:3
|作者:
Cain, Caitlin N.
[1
]
Gaida, Meriem
[2
]
Stefanuto, Pierre-Hugues
[2
]
Focant, Jean-Francois
[2
]
Synovec, Robert E.
[1
]
Jackels, Susan C.
[3
]
Skogerboe, Kristen J.
[3
]
机构:
[1] Univ Washington, Dept Chem, POB 351700, Seattle, WA 98195 USA
[2] Univ Liege, MolSys Res Unit, Organ & Biol Analyt Chem Grp, Allee Six Aout 11, B6C, B-4000 Liege, Belgium
[3] Seattle Univ, Dept Chem, 901 12th Ave, Seattle, WA 98122 USA
基金:
美国国家科学基金会;
关键词:
Coffee;
Potato taste defect;
Comprehensive two-dimensional gas;
chromatography -mass spectrometry;
Chemometrics;
Fisher ratio analysis;
Principal components analysis;
Partial least squares regression;
2-DIMENSIONAL GAS-CHROMATOGRAPHY;
FLIGHT MASS-SPECTROMETRY;
VOLATILE COMPOUNDS;
FEATURE-SELECTION;
QUALITY;
IDENTIFICATION;
OPTIMIZATION;
RECOGNITION;
FINGERPRINT;
SOFTWARE;
D O I:
10.1016/j.microc.2023.109578
中图分类号:
O65 [分析化学];
学科分类号:
070302 ;
081704 ;
摘要:
The presence of flavor defects in coffee beans can negatively impact quality, the consumer experience, and commercial trade. Potato taste defect (PTD), a flavor defect specific to East African coffee, is often characterized by a musty, vegetable-like aroma. While previous work has correlated PTD with the presence of 2-isopropyl-3methoxypyrazine (IPMP), additional changes in the volatile profile of these beans can further amplify the distinct odor of this defect. The aim of this work was to develop a volatile fingerprint of PTD in roasted arabica coffee using headspace solid-phase microextraction coupled to comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (HS-SPME-GC x GC-TOFMS) and chemometrics. Examination of the HSSPME-GC x GC-TOFMS data with tile-based Fisher ratio (F-ratio) analysis discovered 359 analytes that differentiated clean coffee samples from those impacted by severe PTD (p-value < 0.01). It was determined that 327 of the identified analytes were more prevalent in the clean coffee samples while 32 analytes, including IPMP, exhibited higher signals in the impacted coffee samples. Principal components analysis (PCA) of the F-ratio results demonstrated that the coffee samples clustered based on the presence of PTD. Partial least squares (PLS) regression modeling further demonstrated that the compounds discovered by F-ratio analysis were correlated with PTD by accurately predicting the concentration of IPMP in the samples. Investigation of the compounds highly weighted in both the PCA and PLS loadings suggest that the presence of microorganisms on coffee beans after antestia bug damage could be a potential pathway for PTD. This damage results in an overall decrease of analytes that are known to have positive sensory contributions to coffee aroma. Collectively, the volatile fingerprint shown herein illustrates that PTD alters the biochemical process in coffee beans.
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页数:12
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