本研究在A、B、C、D四个市的包装饮用水产工艺中的微生物进行调查，获得微生物污染的基础数据，评价企业生产工艺中微生物污染控制系统的有效性。全面对四个工厂生产工艺过程中原水、过程水及成品水进行微生物检测，利用传统和分子方法对优势菌进行菌种鉴定。结果显示，33份样品霉菌和酵母计数、大肠菌群检出值均<1 CFU/mL，砂滤水和碳滤水的菌落总数均有检出，且检出值较高。过程水中的产气荚膜梭菌均未检出，其中碳滤水有检出粪链球菌，反渗透（Reverses Osmosis，RO）水有检出铜绿假单胞菌。共分离到34株细菌，优势菌包括食酸菌属、假单胞菌属、分枝杆菌属和芽胞杆菌属。包装饮用水企业生产工艺对微生物的控制较为有效，微生物危害风险较低。议包装饮用水企业建立生产现场微生物识别系统，加强微生物监控，掌握生产过程中的微生物风险，为合理有效地控制生产工艺中微生物风险提供科学依据。

Microorganisms from the production process of bottled drinking water plants distributed in A, B, C, D four cities were investigated, to obtain basic microbial contamination data, and evaluate the effectiveness of the microbial contamination control system for the production process of the plants. Microbial analyses of raw water, process water and finished water from the production process of four factories were carried out, and the dominant strains were identified by traditional and molecular identification techniques. The obtained results revealed that the number of molds and yeasts or coliforms of 33 samples was less than 1 CFU/mL. The number of total bacterial colonies in sand-filtering water and carbon-filtering water was detected and the detection values were high. Fecal streptococcus was detected in the process water through a carbon filter, and Pseudomonas aeruginosa was detected in the Reverses Osmosis (RO) water, although Clostridium perfringens was not detected in either water. A total of 34 strains of bacteria were isolated, and dominant bacteria included Acidovorax sp., Pseudomonas sp., Mycobacterium sp., and Bacillus sp.. Microbial monitoring in the production process of bottled drinking water is reasonably effective and the microbial risk is low. It is suggested that the bottled drinking water plants should establish the in-process microbial identification system in the production, strengthen microbial supervision, monitor the microbial risk in the production process, and provide scientific basis for the rational and effective control of microbial risk in the production process.

国家重点研发计划项目(2016YFD0401204）；广东省科技计划项目(2016A010105012）；广州市科技计划项目(201707020036）；科学院2017年实施创新驱动发展能力建设专项资金项目(2017GDASCX-0201）