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. 2022 Oct;59(10):4108-4121.
doi: 10.1007/s13197-022-05463-8. Epub 2022 May 6.

Characterization of aroma-active compounds in Dongli by quantitative descriptive analysis, gas chromatography-triple quadrupole tandem mass spectrometry, and gas chromatography-olfactometry

Jia-Nan Chen  1   2 , Hao-Ting Han  1 , Chun-Ju Liu  3 , Qi Gao  4 , Xiao-Wen Wang  1 , Jun-Wei Zhang  1 , Masaru Tanokura  5 , You-Lin Xue  1
Affiliations

Characterization of aroma-active compounds in Dongli by quantitative descriptive analysis, gas chromatography-triple quadrupole tandem mass spectrometry, and gas chromatography-olfactometry

Jia-Nan Chen et al. J Food Sci Technol. 2022 Oct.

Abstract

Dongli, or frozen pear, is a traditional Chinese snack with a unique flavor. This study identified the aroma-active volatile compounds (VOCs) in Dongli using quantitative descriptive analysis (QDA), gas chromatography-triple quadrupole tandem mass spectrometry (GC-MS/MS), and gas chromatography-olfactometry (GC-O). QDA indicated that Dongli of all cultivars presented increased sweet and wine aromas. A total of 21 VOCs were identified by GC-MS/MS. Bidirectional orthogonal partial least square (O2PLS) analysis, GC-O analysis, detection frequency analysis (DFA), and relative odor activity values (ROAV) showed that: estragole and anethole contributing "anise, green" aromas were the key aromatic VOCs of fresh pears, while ethyl butanoate, butyl acetate, heptyl acetate, benzaldehyde, and geranyl acetone contributing "sweet, fruity, green" aromas were the key aromatic VOCs of Dongli. The results revealed that the repeated freezing treatment promoted a unique aroma in pears. This study would contribute to developing new pear products.

Supplementary information: The online version contains supplementary material available at 10.1007/s13197-022-05463-8.

Keywords: Aroma; Dongli; GC-MS/MS; GC-O; O2PLS.

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Conflict of interest statement

Conflict of interestThe authors have no conflict of interest to disclose.

Figures

Fig. 1
Fig. 1
A–D Radar charts of the aroma characteristics of AP versus FAP, BP versus FBP, JP versus FJP and NP versus FNP by QDA. E Score scatter plot and F biplot chart of PC1 versus PC2 scores based on QDA data by PCA
Fig. 2
Fig. 2
Clustering heatmap of VOCs from the pear samples
Fig. 3
Fig. 3
A Correlation heatmap between the samples based on their VOCs by CA. B Score scatter plot and C biplot chart of PC1 versus PC2 scores based on the relative contents of VOCs by PCA D Differences in the relative contents of VOC categories in fresh pears and Dongli
Fig. 4
Fig. 4
A PLS-DA of the VOCs (compound numbers refer to the compounds listed in Table 1). B Circle plot combining the results of the above PLS-DA models. The key VOCs (VIP > 1) were screened by PLS-DA. Each line represented an important VOC of the sample, and different colors represented different samples. The VOCs with more lines contained only in fresh pears or Dongli could be the key VOCs
Fig. 5
Fig. 5
A Changes in VIP(pred) values of O2PLS model by relative contents of VOCs and QDA data. The VOCs in which VIP(pred) > 1 were considered as the potential key VOCs of the pear samples. B Network model of the correlation between the VOCs and samples by O2PLS modeling. C Network model of the correlation between the VOCs and aroma characteristics by O2PLS modeling
See this image and copyright information in PMC

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