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- Feng, X. M., et al.
(författare)
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Image analysis for monitoring the barley tempeh fermentation process
- 2007
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Ingår i: Journal of Applied Microbiology. - Oxon, United Kingdom : Oxford University Press (OUP). - 1364-5072 .- 1365-2672. ; 103:4, s. 1113-1121
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 2. |
- Reza, Salim, 1985-, et al.
(författare)
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Smart dosimetry by pattern recognition using a single photon counting detector system in time over threshold mode
- 2012
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Ingår i: Journal of Instrumentation. - 1748-0221. ; 7:1
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Tidskriftsartikel (refereegranskat)abstract
- The function of a dosimeter is to determine the absorbed dose of radiation, for those cases in which, generally, the particular type of radiation is already known. Lately, a number of applications have emerged in which all kinds of radiation are absorbed and are sorted by pattern recognition, such as the Medipix2 application in [1]. This form of smart dosimetry enables measurements where not only the total dosage is measured, but also the contributions of different types of radiation impacting upon the detector surface. Furthermore, the use of a photon counting system, where the energy deposition can be measured in each individual pixel, ensures measurements with a high degree of accuracy in relation to the pattern recognition. In this article a Timepix [2] detector system has been used in the creation of a smart dosimeter for Alpha, Beta and Gamma radiation. When a radioactive particle hits the detector surface it generates charge clusters and those impacting upon the detector surface are read out and image processing algorithms are then used to classify each charge cluster. The individual clusters are calculated and as a result, the dosage for each type of radiation is given. In some cases, several particles can impact in roughly the same place, forming overlapping clusters. In order to handle this problem, a cluster separation method has been added to the pattern recognition algorithm. When the clusters have been separated, they are classified by shape and sorted into the correct type of radiation. The algorithms and methods used in this dosimeter have been developed so as to be simple and computationally effective, in order to enable implementation on a portable device. © 2012 IOP Publishing Ltd and SISSA.
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