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Image analysis for monitoring the barley tempeh fermentation process
Author(s) -
Feng X.M.,
Olsson J.,
Swanberg M.,
Schnürer J.,
Rönnow D.
Publication year - 2007
Publication title -
journal of applied microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.889
H-Index - 156
eISSN - 1365-2672
pISSN - 1364-5072
DOI - 10.1111/j.1365-2672.2007.03341.x
Subject(s) - rhizopus oligosporus , fermentation , image processing , food science , artificial intelligence , computer science , mathematics , biology , image (mathematics)
Aims: To develop a fast, accurate, objective and nondestructive method for monitoring barley tempeh fermentation. Methods and Results: Barley tempeh is a food made from pearled barley grains fermented with Rhizopus oligosporus . Rhizopus oligosporus growth is important for tempeh quality, but quantifying its growth is difficult and laborious. A system was developed for analysing digital images of fermentation stages using two image processing methods. The first employed statistical measures sensitive to image colour and surface structure, and these statistical measures were highly correlated ( r = 0·92, n = 75, P < 0·001) with ergosterol content of tempeh fermented with R. oligosporus and lactic acid bacteria (LAB). In the second method, an image‐processing algorithm optimized to changes in images of final tempeh products was developed to measure number of visible barley grains. A threshold of 5 visible grains per Petri dish indicated complete tempeh fermentation. When images of tempeh cakes fermented with different inoculation levels of R. oligosporus were analysed the results from the two image processing methods were in good agreement. Conclusion: Image processing proved suitable for monitoring barley tempeh fermentation. The method avoids sampling, is nonintrusive, and only requires a digital camera with good resolution and image analysis software. Significance and Impact of the Study: The system provides a rapid visualization of tempeh product maturation and qualities during fermentation. Automated online monitoring of tempeh fermentation by coupling automated image acquisition with image processing software could be further developed for process control.