Optimization of Headspace Solid-Phase Micro-Extraction and Its Application in Analysis of Volatile Compounds in Cherry Tomato by Gas Chromatography

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• 作者：Zuobing Xiao ; Quyang Wu ; Yunwei Niu ; Qiang Liu ; Feng Chen…
• 关键词：Cherry tomato juice ; Optimization ; HS ; SPME ; GC ; MS ; PCA ; PLSR
• 刊名：Food Analytical Methods
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：10
• 期：3
• 页码：596-609
• 全文大小：
• 刊物类别：Chemistry and Materials Science
• 刊物主题：Food Science; Chemistry/Food Science, general; Microbiology; Analytical Chemistry;
• 出版者：Springer US
• ISSN：1936-976X
• 卷排序：10

文摘

In this study, four main experimental parameters were optimized, such as coating material of fiber, extraction temperature, extraction time, and salt addition of headspace solid-phase micro-extraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS) for analysis of cherry tomatoes. As a result, the best extraction conditions were 50/30 μm divinybenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS) fiber and 50 °C and 50 min of SPME; the amount of sodium chloride addition was 1.5 g in 8 g tomato sample. Under the optimized conditions, the limits of detection (LOD) and limits of quantification (LOQ) of SPME were ranged from 0.06 to 1.83 μg/kg and 0.21 to 6.10 μg/kg. The linear regression value (R2) of the standard curve was higher than 0.9879. The repeatability was between 2.50 % and 12.30 %, while the reproducibility was ranged from 4.74 % to 14.63 %. Afterward, the method was applied successfully to analysis the volatile compounds in four different varieties of fresh cherry tomatoes, and a total of 50 volatile compounds were identified. Meanwhile, the principle component analysis (PCA) results indicated the distribution of cherry tomato samples based on their sensory evaluation data. And partial least squares regression (PLSR) analysis elucidated the relationship between sensory descriptors and volatile compounds in cherry tomato juices.