MicroVi: A Cost-Effective Microscopy Solution for Yeast Cell Detection and Count in Wine Value Chain.

IF 4.9 3区 工程技术 Q1 CHEMISTRY, ANALYTICAL Biosensors-Basel Pub Date : 2025-01-12 DOI:10.3390/bios15010040
Ismael Benito-Altamirano, Sergio Moreno, David M Vaz-Romero, Anna Puig-Pujol, Gemma Roca-Domènech, Joan Canals, Anna Vilà, Joan Daniel Prades, Ángel Diéguez
{"title":"MicroVi: A Cost-Effective Microscopy Solution for Yeast Cell Detection and Count in Wine Value Chain.","authors":"Ismael Benito-Altamirano, Sergio Moreno, David M Vaz-Romero, Anna Puig-Pujol, Gemma Roca-Domènech, Joan Canals, Anna Vilà, Joan Daniel Prades, Ángel Diéguez","doi":"10.3390/bios15010040","DOIUrl":null,"url":null,"abstract":"<p><p>In recent years, the wine industry has been researching how to improve wine quality along the production value chain. In this scenario, we present here a new tool, MicroVi, a cost-effective chip-sized microscopy solution to detect and count yeast cells in wine samples. We demonstrate that this novel microscopy setup is able to measure the same type of samples as an optical microscopy system, but with smaller size equipment and with automated cell count configuration. The technology relies on the top of state-of-the-art computer vision pipelines to post-process the images and count the cells. A typical pipeline consists of normalization, feature extraction (i.e., SIFT), image composition (to increase both resolution and scanning area), holographic reconstruction and particle count (i.e., Hough transform). MicroVi achieved a 2.19 µm resolution by properly resolving the G7.6 features from the USAF Resolving Power Test Target 1951. Additionally, we aimed for a successful calibration of cell counts for <i>Saccharomyces cerevisiae</i>. We compared our direct results with our current optical setup, achieving a linear calibration for measurements ranging from 0.5 to 50 million cells per milliliter. Furthermore, other yeast cells were qualitatively resolved with our MicroVi microscope, such as, <i>Brettanomyces bruxellensis</i>, or bacteria, like, <i>Lactobacillus plantarum</i>, thus confirming the system's reliability for consistent microbial assessment.</p>","PeriodicalId":48608,"journal":{"name":"Biosensors-Basel","volume":"15 1","pages":""},"PeriodicalIF":4.9000,"publicationDate":"2025-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11763666/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biosensors-Basel","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.3390/bios15010040","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
引用次数: 0

Abstract

In recent years, the wine industry has been researching how to improve wine quality along the production value chain. In this scenario, we present here a new tool, MicroVi, a cost-effective chip-sized microscopy solution to detect and count yeast cells in wine samples. We demonstrate that this novel microscopy setup is able to measure the same type of samples as an optical microscopy system, but with smaller size equipment and with automated cell count configuration. The technology relies on the top of state-of-the-art computer vision pipelines to post-process the images and count the cells. A typical pipeline consists of normalization, feature extraction (i.e., SIFT), image composition (to increase both resolution and scanning area), holographic reconstruction and particle count (i.e., Hough transform). MicroVi achieved a 2.19 µm resolution by properly resolving the G7.6 features from the USAF Resolving Power Test Target 1951. Additionally, we aimed for a successful calibration of cell counts for Saccharomyces cerevisiae. We compared our direct results with our current optical setup, achieving a linear calibration for measurements ranging from 0.5 to 50 million cells per milliliter. Furthermore, other yeast cells were qualitatively resolved with our MicroVi microscope, such as, Brettanomyces bruxellensis, or bacteria, like, Lactobacillus plantarum, thus confirming the system's reliability for consistent microbial assessment.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
求助全文
约1分钟内获得全文 去求助
来源期刊
Biosensors-Basel
Biosensors-Basel Biochemistry, Genetics and Molecular Biology-Clinical Biochemistry
CiteScore
6.60
自引率
14.80%
发文量
983
审稿时长
11 weeks
期刊介绍: Biosensors (ISSN 2079-6374) provides an advanced forum for studies related to the science and technology of biosensors and biosensing. It publishes original research papers, comprehensive reviews and communications. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced. Electronic files and software regarding the full details of the calculation or experimental procedure, if unable to be published in a normal way, can be deposited as supplementary electronic material.
期刊最新文献
A Novel Aggregation-Induced Emission-Based Electrochemiluminescence Aptamer Sensor Utilizing Red-Emissive Sulfur Quantum Dots for Rapid and Sensitive Malathion Detection. Is Breath Best? A Systematic Review on the Accuracy and Utility of Nanotechnology Based Breath Analysis of Ketones in Type 1 Diabetes. Sensitive Detection of Biomarker in Gingival Crevicular Fluid Based on Enhanced Electrochemiluminescence by Nanochannel-Confined Co3O4 Nanocatalyst. Potential of Zinc Oxide Nanostructures in Biosensor Application. Application of PS2M Aptamer as Receptor Layer for Electrochemical Detection of Lead Ions.
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1