A microfluidic biosensor for microbial quantitative monitoring of air and nutrient solution in the plant factory

IF 8.9 Q1 AGRICULTURE, MULTIDISCIPLINARY
Information Processing in Agriculture Pub Date : 2025-12-01 Epub Date: 2025-03-24 DOI:10.1016/j.inpa.2025.03.002
Weizhong Yu , Yizheng Huang , Fang Ji , Yude Yu , Dongxian He , Zhao Li
{"title":"A microfluidic biosensor for microbial quantitative monitoring of air and nutrient solution in the plant factory","authors":"Weizhong Yu ,&nbsp;Yizheng Huang ,&nbsp;Fang Ji ,&nbsp;Yude Yu ,&nbsp;Dongxian He ,&nbsp;Zhao Li","doi":"10.1016/j.inpa.2025.03.002","DOIUrl":null,"url":null,"abstract":"<div><div>Microbial contamination is an inevitable challenge in plant factory, posing substantial risks of economic loss and potential threats to human health if not addressed promptly. However, existing detection methods are characterized by prolonged processing times, high costs, and dependence on skilled technicians, limiting their practicality for routine monitoring. Therefore, there is a critical need for the development of rapid, cost-effective, and reliable device for the quantitative monitoring of microorganisms in both the air and nutrient solutions of the plant factory. We have developed an integrated microfluidic biosensor that can be used to quantitatively monitor microbial levels in air and nutrient solutions by combining ATP bioluminescence. The biosensor was verified and calibrated through a standard ATP solution with <em>Bacillus subtilis</em> bacterial solution, followed by testing of the real air and nutrient solution samples from plant factories. The detection process on the microfluidic chip was automatically controlled to complete within 3 min. The consumption of ATP reaction solution and lysate for one assay was about 10 μL and 16 μL, respectively. The sensitivity of bacterial quantification was up to 6.4 × 10<sup>3</sup> CFU mL<sup>−1</sup> with a detection range covering 4 orders of magnitude. This biosensor has been demonstrated to have similar detection accuracy with the culture counting method and enable quantitative monitoring of microorganisms in plant factory, while greatly reducing the detection cycles.</div></div>","PeriodicalId":53443,"journal":{"name":"Information Processing in Agriculture","volume":"12 4","pages":"Pages 478-486"},"PeriodicalIF":8.9000,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Processing in Agriculture","FirstCategoryId":"1091","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2214317325000186","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/3/24 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

Abstract

Microbial contamination is an inevitable challenge in plant factory, posing substantial risks of economic loss and potential threats to human health if not addressed promptly. However, existing detection methods are characterized by prolonged processing times, high costs, and dependence on skilled technicians, limiting their practicality for routine monitoring. Therefore, there is a critical need for the development of rapid, cost-effective, and reliable device for the quantitative monitoring of microorganisms in both the air and nutrient solutions of the plant factory. We have developed an integrated microfluidic biosensor that can be used to quantitatively monitor microbial levels in air and nutrient solutions by combining ATP bioluminescence. The biosensor was verified and calibrated through a standard ATP solution with Bacillus subtilis bacterial solution, followed by testing of the real air and nutrient solution samples from plant factories. The detection process on the microfluidic chip was automatically controlled to complete within 3 min. The consumption of ATP reaction solution and lysate for one assay was about 10 μL and 16 μL, respectively. The sensitivity of bacterial quantification was up to 6.4 × 103 CFU mL−1 with a detection range covering 4 orders of magnitude. This biosensor has been demonstrated to have similar detection accuracy with the culture counting method and enable quantitative monitoring of microorganisms in plant factory, while greatly reducing the detection cycles.
一种用于植物工厂空气和营养液微生物定量监测的微流控生物传感器
微生物污染是植物工厂不可避免的挑战,如果不及时处理,将带来巨大的经济损失风险和对人类健康的潜在威胁。然而,现有检测方法的特点是处理时间长,成本高,依赖熟练的技术人员,限制了其在日常监测中的实用性。因此,迫切需要开发一种快速、经济、可靠的设备来定量监测植物工厂空气和营养液中的微生物。我们开发了一种集成的微流控生物传感器,可以通过结合ATP生物发光来定量监测空气和营养液中的微生物水平。通过标准ATP溶液和枯草芽孢杆菌细菌溶液对生物传感器进行验证和校准,然后对植物工厂的真实空气和营养液样品进行测试。微流控芯片上的检测过程自动控制在3 min内完成。ATP反应液和裂解液的耗量分别约为10 μL和16 μL。细菌定量的灵敏度可达6.4 × 103 CFU mL−1,检测范围覆盖4个数量级。该生物传感器已被证明具有与培养计数方法相似的检测精度,可以对植物工厂中的微生物进行定量监测,同时大大缩短了检测周期。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Information Processing in Agriculture
Information Processing in Agriculture Agricultural and Biological Sciences-Animal Science and Zoology
CiteScore
21.10
自引率
0.00%
发文量
80
期刊介绍: Information Processing in Agriculture (IPA) was established in 2013 and it encourages the development towards a science and technology of information processing in agriculture, through the following aims: • Promote the use of knowledge and methods from the information processing technologies in the agriculture; • Illustrate the experiences and publications of the institutes, universities and government, and also the profitable technologies on agriculture; • Provide opportunities and platform for exchanging knowledge, strategies and experiences among the researchers in information processing worldwide; • Promote and encourage interactions among agriculture Scientists, Meteorologists, Biologists (Pathologists/Entomologists) with IT Professionals and other stakeholders to develop and implement methods, techniques, tools, and issues related to information processing technology in agriculture; • Create and promote expert groups for development of agro-meteorological databases, crop and livestock modelling and applications for development of crop performance based decision support system. Topics of interest include, but are not limited to: • Smart Sensor and Wireless Sensor Network • Remote Sensing • Simulation, Optimization, Modeling and Automatic Control • Decision Support Systems, Intelligent Systems and Artificial Intelligence • Computer Vision and Image Processing • Inspection and Traceability for Food Quality • Precision Agriculture and Intelligent Instrument • The Internet of Things and Cloud Computing • Big Data and Data Mining
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信
小红书