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Disentangling the Tissue-Specific Variations of Volatile Flavor Profiles of the Lentinula edodes Fruiting Body

文献类型： 外文期刊

作者： Guo, Yuan 1 ; Zhao, Jing 2 ; Wei, Huixian 3 ; Gao, Qi 1 ; Song, Shuang 1 ; Fan, Yangyang 1 ; Yan, Dong 1 ; Liu, Yu 1 ; Wang, Shouxian 1 ;

作者机构： 1.Beijing Acad Agr & Forestry Sci, Beijing Engn Res Ctr Edible Mushroom, Inst Plant Protect, Beijing 100097, Peoples R China

2.Inner Mongolia Agr Univ, Coll Hort & Plant Protect, Hohhot 010018, Peoples R China

3.Baise Univ, Coll Agr & Food Engn, Baise 533000, Peoples R China

关键词： Lentinula edodes; volatile flavor; metabolomics; GC-MS; tissue specificity; multivariate analysis

期刊名称：FOODS （ 影响因子：5.2； 五年影响因子：5.5 ）

ISSN：

年卷期： 2024 年 13 卷 1 期

页码：

收录情况： SCI

摘要： For Lentinula edodes, its characteristic flavor is the key determinant for consumer preferences. However, the tissue-specific volatile flavor variations of the fruiting body have been overlooked. Here, we comprehensively investigated the volatile flavor profiles of different tissues, including the pileus skin, context, gill, and stipe of the fruiting body, of two widely cultivated L. edodes strains (T2 and 0912) using the gas chromatography-mass spectrometry (GC-MS) technique combined with a multivariate analysis. We show that the eight-carbon and sulfur compounds, which represented 43.2-78.0% and 1.4-42.9% of the total volatile emissions for strains 0912 and T2, respectively, dominated their volatile profiles. Compared with strain T2, strain 0912 had a higher total content of eight-carbon compounds but a lower total content of sulfur compounds in the fruiting body. The sulfur compounds represented 32.2% and 42.9% of the total volatile emissions for strains 0912 and T2, respectively. In contrast, they constituted only 1.4% in the stipes of strain 0912 and 9.0% in the skin of strain T2. The proportions of the predominant C8 compounds (1-octen-3-one, 1-octen-3-ol, and 3-octanone) and sulfur compounds (lenthionine, 1,2,4-trithiolane, dimethyl disulfide, and dimethyl trisulfide) changed depending on the tissues and strains. Using machine learning, we show that the prediction accuracy for different strains and tissues using their volatile profiles could reach 100% based on the highly diverse strain- and tissue-derived volatile variations. Our results reveal and highlight for the first time the comprehensive tissue-specific volatile flavor variations of the L. edodes fruiting body. These findings underscore the significance of considering strain and tissue differences as pivotal variables when aiming to develop products with volatile flavor characteristics.

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