Rapid and concise quantification of mycelial growth by microscopic image intensity model and application to mass cultivation of fungi
- Authors
- Lee, Soo Kweon; Lee, Ju Hun; Kim, Hyeong Ryeol; Chun, Youngsang; Lee, Ja Hyun; Park, Chulhwan; Yoo, Hah Young; Kim, Seung Wook
- Issue Date
- 17-12월-2021
- Publisher
- NATURE PORTFOLIO
- Citation
- SCIENTIFIC REPORTS, v.11, no.1
- Indexed
- SCIE
SCOPUS
- Journal Title
- SCIENTIFIC REPORTS
- Volume
- 11
- Number
- 1
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/135403
- DOI
- 10.1038/s41598-021-03512-4
- ISSN
- 2045-2322
- Abstract
- The microbial food fermentation industry requires real-time monitoring and accurate quantification of cells. However, filamentous fungi are difficult to quantify as they have complex cell types such as pellet, spores, and dispersed hyphae. In this study, numerous data of microscopic image intensity (MII) were used to develop a simple and accurate quantification method of Cordyceps mycelium. The dry cell weight (DCW) of the sample collected during the fermentation was measured. In addition, the intensity values were obtained through the ImageJ program after converting the microscopic images. The prediction model obtained by analyzing the correlation between MII and DCW was evaluated through a simple linear regression method and found to be statistically significant (R-2 = 0.941, p < 0.001). In addition, validation with randomly selected samples showed significant accuracy, thus, this model is expected to be used as a valuable tool for predicting and quantifying fungal growth in various industries.
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Collections - College of Engineering > Department of Chemical and Biological Engineering > 1. Journal Articles
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