车丽娜,赵良忠,周晓洁.基于高通量测序分析湘派卤牛肉冷藏过程中真菌多样性[J].食品安全质量检测学报,2023,14(4):127-136 |
基于高通量测序分析湘派卤牛肉冷藏过程中真菌多样性 |
High-throughput sequencing analysis of fungal diversity in Xiangpai dried beef during cold storage |
投稿时间:2022-10-19 修订日期:2023-01-05 |
DOI: |
中文关键词: 湘派卤牛肉 冷藏 高通量测序技术 真菌多样性 |
英文关键词:Xiangpai dried beef cold storage high-throughput sequencing technology diversity of fungi |
基金项目:湖南省研究生科研创新项目(CX20201182)、湖南省自然科学青年基金项目(2021JJ40514)、湖南省教育厅科学研究优秀青年项目(20B530)、湖南省科技创新计划资助项目(2019TP1028、2019SK2122、2019NK4229、2022NK2039) |
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中文摘要: |
目的 探究湘派卤牛肉冷藏过程中真菌菌群变化规律及其多样性。方法 将湘派卤牛肉于4℃下贮藏16 d, 每间隔4 d采样, 利用高通量测序技术对样品中的真菌进行检测。结果 湘派卤牛肉在冷藏过程中真菌多样性呈先下降后上升的趋势。在门水平上, 被孢霉门(Mortierellomycota)为优势菌门, 相对丰度为22.3%~51.9%。其次为子囊菌门(Ascomycota), 相对丰度为22.6%~42.0%。最后为担子菌门(Basidiomycota), 相对丰度为6%~40.3%。在属水平上, 优势菌属主要为: f_Mortierellaceae;g_unidentified、散尾鬼笔属(Lysurus)和伊萨酵母属(Issatchenkia)。主坐标分析显示4与12 d之间微生物结构差异较小, 0、8、16 d之间微生物结构差异较大, 两个主坐标叠加解释度达79.35%; 经UPGMA聚类算法构建的真菌聚类堆叠树状图显示, 5种样品可分为4个大类, 其中LNR4 d、LNR12 d菌群差异不大为一类, LNR0 d、LNR8 d、LNR16 d菌群差异较大各聚为一类。结论 本研究通过对比不同冷藏时间下湘派卤牛肉的真菌菌群结构及多样性的变化, 揭示湘派卤牛肉冷藏过程中的真菌菌群群落结构特征, 探索引起其腐败变质的主要菌群, 为湘派卤牛肉的今后冷藏过程中靶向抑菌保鲜及延长货架期提供理论依据。 |
英文摘要: |
Objective To explore the changes and diversity of fungal flora of Xiangpai dried beef during cold storage. Methods The Xiangpai dried beef was stored at 4℃ for 16 d, sampled every 4 days, and high-throughput sequencing technology was used to detect the fungi in the samples. Results The fungi diversity of Xiangpai dried beef showed decreased firstly and then increased trend during the cold storage. At the phylum level, Mortierellomycota was dominant, with the relative abundance of 22.3%?51.9%. Ascomycota was next, with relative abundance of 22.6%?42.0%. Finally, Basidiomycota, with the relative abundance of 6%?40.3%. On the genus level, the dominant genera were: f_Mortierellaceae;g_unidentified, Lysurus, and Issatchenkia. The principal coordinate analysis showed that the difference in microbial structure was small on days 4 and 12, and significant on days 0, 8 and 16, with the explanation degree of superposition of the two principal coordinates reaching 79.35%. The fungal cluster stack tree constructed by UPGMA clustering algorithm showed that the 5 kinds of samples could be divided into 4 major classes, in which, the flora of LNR4 d and LNR12 d were not significantly different in one class, while those of LNR0 d, LNR8 d and LNR16 d were significantly different in each class. Conclusion In this study, by comparing the changes of fungi flora structure and diversity of Xiangpai dried beef during cold storage, reveal the characteristics of fungi flora community structure in the process of Xiangpai brined beef refrigeration, explore its fungal diversity during cold storage, and explore the main bacteria that cause the spoilage, which provides a theoretical basis for the targeted bacteriostatic preservation and shelf life extension of Xiangpai brined beef in the future refrigeration process. |
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