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Starter-specific flavor markers in Suansun revealed by cross-platform GC-MS/GC-IMS volatilomics

葡萄酒的香气 芳香 风味 色谱法 化学 三硫化二甲酯 气相色谱-质谱法 质谱法 食品科学 萃取(化学) 葡萄酒 醋酸 偏最小二乘回归 模式识别(心理学) 挥发性有机化合物 发酵 气相色谱法 代谢组学 优先次序
作者
Jianwen Wu,Guiqing Li,Jihua Guan,Suhua Yang,Xingyue Tang,Mi Mi Qiu
出处
期刊:Lebensmittel-Wissenschaft & Technologie [Elsevier BV]
卷期号:244: 119205-119205 被引量:1
标识
DOI:10.1016/j.lwt.2026.119205
摘要

(fermented bamboo shoots) exhibits complex aroma profiles that are difficult to capture using a single analytical platform. Here, we compared three inoculation approaches (dairy-derived consortium, Lactiplantibacillus plantarum monoculture, and plant-origin consortium; biological replicates, n = 3) using cross-platform volatilomics integrating gas chromatography-ion mobility spectrometry (GC-IMS) fingerprinting with GC-MS profiling. For GC-MS, we evaluated four sorptive sample-preparation workflows: headspace solid-phase microextraction (SPME), thin-film SPME (TF), stir bar sorptive extraction (SBSE), and a combined TF+SBSE. GC-IMS resolved inoculation-dependent volatile fingerprints and annotated 95 signals corresponding to 77 compounds, enabling clear separation of fermentation groups. Across GC-MS workflows, TF+SBSE broadened the detectable volatile range and generated the highest cumulative responses for many aroma-active compounds. Multivariate analyses combined with machine-learning prioritization identified six discriminant volatiles: cresol isomers, benzyl alcohol, acetic acid, ethyl acetate, hexanal, and dimethyl sulfide. These compounds were consistently prioritized for differentiating inoculation approaches in this dataset and indicated complementary detection preferences between GC-MS and GC-IMS. The integrated GC-IMS/GC-MS method gives a shortlist of candidate marker volatiles for differentiating inoculation-dependent aroma signatures in Suansun and provides a practical guide for targeted monitoring and starter benchmarking in plant-based fermentations. Broader applications will require sensory confirmation and independent batch validation. • Cross-platform volatilomics expands coverage. An integrated cross-platform volatilomics framework combining GC-MS (SPME, TF, SBSE, TF+SBSE) with GC-IMS expands detectable volatile coverage beyond single workflows. • Candidate marker panel prioritized across inoculation strategies. Six candidate marker volatiles ( o / m / p -cresols, benzyl alcohol, hexanal, acetic acid, ethyl acetate, and dimethyl sulfide) were consistently prioritized to discriminate inoculation approaches in the dataset, supporting the interpretation of Suansun’ s characteristic aroma. • Inoculation-dependent signatures with practical relevance. The plant-origin inoculum was associated with higher abundances of acids, esters, and sulfur-containing compounds compared with the dairy-derived consortium, providing a practical basis for starter benchmarking and targeted monitoring in Suansun fermentation.
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