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  • Dynamic headspace solid-phase microextraction combined with one-dimensional gas chromatography-mass spectrometry as a powerful tool to differentiate banana cultivars based on their volatile metabolite profile.

Dynamic headspace solid-phase microextraction combined with one-dimensional gas chromatography-mass spectrometry as a powerful tool to differentiate banana cultivars based on their volatile metabolite profile.

Food chemistry (2013-02-28)
Marisela Pontes, Jorge Pereira, José S Câmara
ABSTRACT

In this study the effect of the cultivar on the volatile profile of five different banana varieties was evaluated and determined by dynamic headspace solid-phase microextraction (dHS-SPME) combined with one-dimensional gas chromatography-mass spectrometry (1D-GC-qMS). This approach allowed the definition of a volatile metabolite profile to each banana variety and can be used as pertinent criteria of differentiation. The investigated banana varieties (Dwarf Cavendish, Prata, Maçã, Ouro and Platano) have certified botanical origin and belong to the Musaceae family, the most common genomic group cultivated in Madeira Island (Portugal). The influence of dHS-SPME experimental factors, namely, fibre coating, extraction time and extraction temperature, on the equilibrium headspace analysis was investigated and optimised using univariate optimisation design. A total of 68 volatile organic metabolites (VOMs) were tentatively identified and used to profile the volatile composition in different banana cultivars, thus emphasising the sensitivity and applicability of SPME for establishment of the volatile metabolomic pattern of plant secondary metabolites. Ethyl esters were found to comprise the largest chemical class accounting 80.9%, 86.5%, 51.2%, 90.1% and 6.1% of total peak area for Dwarf Cavendish, Prata, Ouro, Maçã and Platano volatile fraction, respectively. Gas chromatographic peak areas were submitted to multivariate statistical analysis (principal component and stepwise linear discriminant analysis) in order to visualise clusters within samples and to detect the volatile metabolites able to differentiate banana cultivars. The application of the multivariate analysis on the VOMs data set resulted in predictive abilities of 90% as evaluated by the cross-validation procedure.

MATERIALS
Product Number
Brand
Product Description

Supelco
SPME Fiber Assembly Polydimethylsiloxane/Divinylbenzene (PDMS/DVB), df 65 μm(PDMS/DVB, for use with autosampler, needle size 23 ga
Supelco
SPME Fiber Assembly Polydimethylsiloxane/Divinylbenzene (PDMS/DVB), df 65 μm(PDMS/DVB, needle size 24 ga, StableFlex, for use with manual holder
Supelco
SPME Fiber Assembly Polydimethylsiloxane/Divinylbenzene (PDMS/DVB), df 65 μm(PDMS/DVB, needle size 23 ga, PDMS/DVB StableFlex, for use with autosampler
Supelco
SPME Fiber Assembly Polydimethylsiloxane/Divinylbenzene (PDMS/DVB), df 65 μm(PDMS/DVB, needle size 24 ga, for use with manual holder
Supelco
SPME Portable Field Sampler, coating PDMS/DVB
Supelco
SPME Fiber Assembly Polydimethylsiloxane/Divinylbenzene (PDMS/DVB), fused silica fiber, df 65 μm(PDMS/DVB, for use with manual holder, needle size 23 ga
Supelco
SPME Fiber Assembly Polydimethylsiloxane/Divinylbenzene (PDMS/DVB), df 65 μm(PDMS/DVB, needle size 24 ga, StableFlex, for use with autosampler
Supelco
SPME Fiber Assembly Polydimethylsiloxane/Divinylbenzene (PDMS/DVB), df 65 μm(PDMS/DVB, needle size 24 ga, for use with autosampler
Supelco
SPME Fiber Assembly Polydimethylsiloxane/Divinylbenzene (PDMS/DVB), df 65 μm(PDMS/DVB, for use with autosampler, needle size 23 ga, metal alloy fiber