Determination of Volatilome Profile in Carbonated Beverages Using n-Hexane as an Extractant by GC-MS

Author:

Mu Li1ORCID,Meng Xianglong1,Luo Huihong1,Liu Qianqian1,Zhang Li2,Li Xin2,Xu Ying2,Li Gang2

Affiliation:

1. College of Food Science and Engineering, Changchun University, Jilin 130022, China

2. Jilin Province Product Quality Supervision and Inspection Institute, Jilin 130023, China

Abstract

A liquid–liquid extraction pretreatment method using n-hexane as the extractant was developed for the analysis of volatile aroma substances in three flavors (six cola samples, six lemon samples, and six orange samples) of carbonated beverages by gas chromatography–mass spectrometry (GC-MS). Quantitative analysis was conducted using the external standard method. The spiked recovery rate of α-terpineol was used as the evaluation criterion. Single-factor and response surface experiments were conducted to investigate the effects of extraction temperature, extraction time, and solvent-to-sample ratio. The results indicated that the maximum spiked recovery rate of α-terpineol, 81.00%, was achieved at an extraction temperature of 45 °C, extraction time of 30 min, and a solvent-to-sample ratio of 1 mL:15 mL. Thirty-four components were identified by GC-MS on the pretreated samples via the internal standard method. 1,4-Cineole, fenchyl alcohol, borneol, and α-terpineol are covered aroma substances in cola beverages. Two aromatic substances, D-limonene and α-terpineol, were detected in orange juices. α-Terpineol was detected in each lemon-flavor carbonated beverage sample. Going a step further, α-terpineol was detected in all 18 carbonated beverage samples and had high response values. The principal component analysis by functional group classification led to the conclusion that acids, phenols, hydrocarbons, alcohols, and ethers played a major contribution to the aroma of these 18 beverages. Increased separation of target compounds was found using the new pre-treatment methods, resulting in improved analytical resolution and selectivity.

Funder

Jilin Province Science and Technology Department

Jilin Province Education Department Fund

Publisher

MDPI AG

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