Feng X M, Olsson J, Swanberg M, Schnürer J, Rönnow D
Department of Microbiology, Swedish University of Agricultural Sciences (SLU), Uppsala, Sweden.
J Appl Microbiol. 2007 Oct;103(4):1113-21. doi: 10.1111/j.1365-2672.2007.03341.x.
To develop a fast, accurate, objective and nondestructive method for monitoring barley tempeh fermentation.
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.
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.
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.
开发一种快速、准确、客观且无损的方法来监测大麦豆豉发酵过程。
大麦豆豉是由珍珠大麦粒经少孢根霉发酵制成的食品。少孢根霉的生长对豆豉品质很重要,但量化其生长既困难又费力。开发了一个系统,使用两种图像处理方法来分析发酵阶段的数字图像。第一种方法采用对图像颜色和表面结构敏感的统计测量方法,这些统计测量值与经少孢根霉和乳酸菌(LAB)发酵的豆豉中的麦角固醇含量高度相关(r = 0.92,n = 75,P < 0.001)。在第二种方法中,开发了一种针对最终豆豉产品图像变化进行优化的图像处理算法,以测量可见大麦粒的数量。每个培养皿中有5个可见颗粒的阈值表明豆豉发酵完成。当分析用不同接种水平的少孢根霉发酵的豆豉饼图像时,两种图像处理方法的结果吻合良好。
图像处理被证明适用于监测大麦豆豉发酵。该方法无需取样,是非侵入性的,并且只需要一台具有高分辨率的数码相机和图像分析软件。
该系统能够快速直观地呈现豆豉产品在发酵过程中的成熟度和品质。通过将自动图像采集与图像处理软件相结合,进一步开发用于过程控制的豆豉发酵自动化在线监测系统是可行的。