A New Alginate-Based Rapid Method for Determining Coliforms in Milk

Author:

CHANG SU-SEN1,GRAY PETER M.1,WOO GUN-JO2,KANG DONG-HYUN1

Affiliation:

1. 1Department of Food Science and Human Nutrition, Washington State University, Pullman, Washington 99164-6376, USA

2. 2Food Microbiology Division, Korea Food and Drug Administration, Seoul, 122-704, Korea

Abstract

A new rapid method for monitoring coliforms was developed on the basis of the instant gelling effects of alginate and calcium. The effectiveness of this new method in the detection of coliforms was evaluated. Tests involving Escherichia coli, Enterobacter cloacae, Klebsiella pneumoniae, total coliforms in milk, cold-injured coliforms, and total coliforms in raw milk were carried out. The bacterial samples were diluted in 0.2% peptone water containing 90 mM CaCl2 and added into test tubes containing modified purple broth base medium. Coliform concentrations were determined on the basis of the time of color change and gas production in the alginate tubes. All results obtained by the alginate method correlated strongly with those obtained by the conventional violet red bile agar (VRBA) plating method. The alginate method reduced detection time by 12 to 14 h compared with the conventional VRBA plating method. The alginate method can be applied in field studies more easily than melted-agar systems can. The results of this study indicate that the alginate method is an accurate, rapid, simple, and economical way to monitor and estimate concentrations of total coliforms in food.

Publisher

International Association for Food Protection

Subject

Microbiology,Food Science

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3