ORIGINAL PAPER
Visual detection of microbial community during three bacteria mixed fermentation through hyperspectral imaging technology
1
School of Agricultural Equipment Engineering, Jiangsu University, China
2
School of Food and Biological Engineering, Jiangsu University, China
3
International Research Center for Food Nutrition and Safety, Jiangsu University, China
4
Department of Analytical Chemistry and Food Science, University of Vigo - Ourense Campus, Spain
Submission date: 2021-10-15
Final revision date: 2021-11-09
Acceptance date: 2021-11-09
Online publication date: 2021-11-13
Publication date: 2022-02-01
Corresponding author
eFood 2021;2(5):271-278
KEYWORDS
Microbial community structureVinegar fermentationHyperspectral imaging technologyStrain colony identificationStrain colony counting
TOPICS
ABSTRACT
Hyperspectral imaging technology with chemometrics was used for identifying and counting each species in microbial community during mixed fermentation. Hyperspectral images of microbial community of Enterobacter sp, Acetobacter pasteurianus, and Lactobacillus paracasei colonies were obtained and the spectra of strain colonies were extracted. Identification models were developed using linear discriminant analysis (LDA) and least-squares support vector machine (LS-SVM) by using 23 variables selected by genetic algorithm. The optimal LS-SVM model with identification rate of 96.67 % was used to identify colonies and prepare colony distribution maps in color for strains counting. The counting results by hyperspectral imaging technology agree with that of the manual counting method with average relative error of 3.70 %. The developed counting method has been successfully used to identify and count the specific strain from the mixed strains simultaneously. The hyperspectral imaging technology has a great potential to monitor changes in the microbial community structure.
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