共 31 条
YEAST FERMENTATION OF SUGARCANE FOR ETHANOL PRODUCTION: CAN IT BE MONITORED BY USING IN SITU MICROSCOPY?
被引:6
作者:
Belini, V. L.
[1
]
Caurin, G. A. P.
[2
]
Wiedemann, P.
[3
]
Suhr, H.
[4
]
机构:
[1] Univ Fed Sao Carlos, Dept Elect Engn, Rodovia Washington Luis,Km 235, BR-13565905 Sao Carlos, SP, Brazil
[2] Univ Sao Paulo, Dept Mech Engn, Av Trabalhador Sao Carlense 400, BR-13566590 Sao Carlos, SP, Brazil
[3] Hsch Mannheim, Fak Biotechnol, Paul Wittsack Str 10, D-68163 Mannheim, Germany
[4] Hsch Mannheim, Fak Informat Tech, Paul Wittsack Str 10, D-68163 Mannheim, Germany
基金:
巴西圣保罗研究基金会;
关键词:
yeast;
in situ microscopy;
image analysis;
sugarcane;
molasses;
ethanol;
SACCHAROMYCES-CEREVISIAE;
IMAGE-ANALYSIS;
BIOETHANOL PRODUCTION;
CELL-CONCENTRATION;
BACTERIAL-CONTAMINATION;
ALCOHOLIC FERMENTATION;
ONLINE;
POPULATIONS;
BIOREACTORS;
VIABILITY;
D O I:
10.1590/0104-6632.2017034420160162
中图分类号:
TQ [化学工业];
学科分类号:
0817 ;
摘要:
This paper addresses some key issues related to the automation of fermentation process analysis in the context of industrial-scale ethanol production from sugarcane substrates. As the current methods for the determination of cell density and viability are time consuming and laborious, high resolution in situ microscopy (0.5 mu m) is proposed as a promising alternative. Laboratory-scale experiments presented here show that this imaging technique allows automatic, on-line, and real-time monitoring of yeast cells suspended in sugarcane molasses used in the ethanol industry. In particular, the feasibility of cell concentration measurements of Saccharomyces cerevisiae SA-1 in industrial sugarcane molasses is demonstrated. Automated concentration measurements exhibit a linear correlation with manual reference values using a Neubauer chamber from 3x10(6) cells/mL up to a saturation level at approximately 2x10(8) cells/mL. Furthermore, it was demonstrated that the microscopic resolution of this technique, combined with its large statistics, allows a morphological assessment of the size, shape and some internal structures of the yeast cells. On average, the accuracy of the algorithm 's yeast cells classification was 0.80. The results obtained suggest that the ISM is a suitable tool to perform in-line sugarcane fermentation monitoring.
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页码:949 / 959
页数:11
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