通过对冷吃兔生产所用冷鲜兔、辣椒、花椒、八角、芝麻、孜然、山奈、香料、桂皮、生产用水中的微生物数量进行测定并采用传统培养法结合16S rDNA测序技术鉴定，确定了原料和各种辅料中细菌的主要种属，最后通过构建系统发育树进行溯源分析。结果表明，原辅料中共分离76株菌，分布于20个属；不同原辅料菌落总数从大到小为：兔肉>孜然>辣椒>香料>生产用水>山奈>八角>桂皮>花椒>芝麻；不同原辅料含细菌属水平数量排序为：原料肉>辣椒、孜然>香料、生产用水>花椒、八角、芝麻、桂皮>山奈；不同原辅料含细菌种水平数量排序为：香料>原料肉>桂皮>辣椒>八角>山奈>孜然、花椒>芝麻、生产用水。在冷吃兔原辅料中细菌多样性高，芽孢杆菌属在原辅料中普遍存在，原料肉所含的细菌量最多。本研究深入了解了冷吃兔原辅料中的污染情况并能为从源头控制细菌种类与数量提供理论依据，更好的控制管理生产过程，使其安全性提升。

The number of microorganisms in chilled rabbit meat, chili pepper, Chinese prickly ash, star anise, sesame, cumin, aromatic ginger, spices, cinnamon, and process water used in the production of Leng-chi rabbit was determined, and the main species of bacteria in these raw materials and various auxiliary materials were identified using a traditional culture method combined with 16S rDNA sequencing. Subsequently, traceability analysis was performed by constructing a phylogenetic tree. The results showed that a total of 76 bacterial strains from 20 genera were isolated from the raw and auxiliary materials. The materials were ranked according to the total number of colonies as follows: rabbit meat > cumin > chili pepper > spices > process water > aromatic ginger > star anise > cinnamon > Chinese prickly ash > sesame. The materials were ranked for the number of bacterial genera present, as follows: raw meat > chili pepper, cumin > spices, process water > Chinese prickly ash, star anise, sesame, cinnamon > aromatic ginger. Additionally, the ranking for number of bacterial species present was: spices > raw meat > cinnamon > chili pepper > star anise > aromatic ginger > cumin, Chinese prickly ash > sesame, process water. The bacterial diversity was high in the raw and auxiliary materials for Leng-chi rabbit. Bacillus was common in all materials; however, raw meat contained the most bacteria. This study provides an in-depth understanding of the contamination of raw and auxiliary materials used in the production of Leng-chi rabbit. Thus, it provides a theoretical basis for controlling the species and quantity of bacteria from each source and improving production process management and safety.

四川省科技计划项目（2020YFN0151）