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 (R2 = 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.

Details

Title
Rapid and concise quantification of mycelial growth by microscopic image intensity model and application to mass cultivation of fungi
Author
Kweon, Lee Soo 1 ; Lee, Ju Hun 1 ; Kim, Hyeong Ryeol 1 ; Chun Youngsang 2 ; Lee Ja Hyun 3 ; Park Chulhwan 4 ; Yoo Hah Young 5 ; Kim, Seung Wook 1 

 Korea University, Department of Chemical and Biological Engineering, Seoul, Republic of Korea (GRID:grid.222754.4) (ISNI:0000 0001 0840 2678) 
 Korea University, Department of Interdisciplinary Bio-Micro System Technology, College of Engineering, Seoul, Republic of Korea (GRID:grid.222754.4) (ISNI:0000 0001 0840 2678) 
 Dongyang Mirae University, Department of Food Science and Engineering, Seoul, Republic of Korea (GRID:grid.449106.e) (ISNI:0000 0004 0532 5576) 
 Kwangwoon University, Department of Chemical Engineering, Seoul, Republic of Korea (GRID:grid.411202.4) (ISNI:0000 0004 0533 0009) 
 Sangmyung University, Department of Biotechnology, Seoul, Republic of Korea (GRID:grid.263136.3) (ISNI:0000 0004 0533 2389) 
Publication year
2021
Publication date
2021
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2611009354
Copyright
© The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.