title: Design and Elementary Evaluation of a Highly-Automated Fluorescence-Based Instrument System for On-Site Detection of Food-Borne Pathogens.
abstract: A simple, highly-automated instrument system used for on-site detection of foodborne pathogens based on fluorescence was designed, fabricated, and preliminarily tested in this paper. A corresponding method has been proved effective in our previous studies. This system utilizes a light-emitting diode (LED) to excite fluorescent labels and a spectrometer to record the fluorescence signal from samples. A rotation stage for positioning and switching samples was innovatively designed for high-throughput detection, ten at most in one single run. We also developed software based on LabVIEW for data receiving, processing, and the control of the whole system. In the test of using a pure quantum dot (QD) solution as a standard sample, detection results from this home-made system were highly-relevant with that from a well-commercialized product and even slightly better reproducibility was found. And in the test of three typical kinds of food-borne pathogens, fluorescence signals recorded by this system are highly proportional to the variation of the sample concentration, with a satisfied limit of detection (LOD) (nearly 10²-10³ CFU·mL-1in food samples). Additionally, this instrument system is low-cost and easy-to-use, showing a promising potential for on-site rapid detection of food-borne pathogens.
authors.affiliation: College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China. 11413014@zju.edu.cn.
authors.forename: Zhan
authors.initials: Z
authors.lastname: Lu
authors.affiliation: College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China. zhangjianyilong2@126.com.
authors.forename: Jianyi
authors.initials: J
authors.lastname: Zhang
authors.affiliation: College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China. xu.lizhou@163.com.
authors.forename: Lizhou
authors.initials: L
authors.lastname: Xu
authors.affiliation: Department of Biological and Agricultural Engineering, University of Arkansas, Fayetteville, AR 72701, USA. yanbinli@zju.edu.cn.
authors.forename: Yanbin
authors.initials: Y
authors.lastname: Li
authors.affiliation: College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China. sychen412@gmail.com.
authors.forename: Siyu
authors.initials: S
authors.lastname: Chen
authors.affiliation: College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China. zzye@zju.edu.cn.
authors.forename: Zunzhong
authors.initials: Z
authors.lastname: Ye
authors.affiliation: College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China. jpwang@zju.edu.cn.
authors.forename: Jianping
authors.initials: J
authors.lastname: Wang
mesh_terms: D005516:Food Microbiology; D057230:Limit of Detection; D045663:Quantum Dots; D015203:Reproducibility of Results
keywords: LabVIEW; automated instrument system; fluorescence; food-borne pathogens; on-site detection; quantum dots