Energy efficient inactivation of Saccharomyces cerevisiae via controlled hydrodynamic cavitation
被引:34
作者:
Albanese, Lorenzo
论文数: 0引用数: 0
h-index: 0
机构:
CNR, Ist Biometeorol, Via Caproni 8, I-50145 Florence, FI, ItalyCNR, Ist Biometeorol, Via Caproni 8, I-50145 Florence, FI, Italy
Albanese, Lorenzo
[1
]
Ciriminna, Rosaria
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h-index: 0
机构:
CNR, Ist Studio Mat Nanostrutturati, I-90146 Palermo, ItalyCNR, Ist Biometeorol, Via Caproni 8, I-50145 Florence, FI, Italy
Ciriminna, Rosaria
[2
]
Meneguzzo, Francesco
论文数: 0引用数: 0
h-index: 0
机构:
CNR, Ist Biometeorol, Via Caproni 8, I-50145 Florence, FI, ItalyCNR, Ist Biometeorol, Via Caproni 8, I-50145 Florence, FI, Italy
Meneguzzo, Francesco
[1
]
Pagliaro, Mario
论文数: 0引用数: 0
h-index: 0
机构:
CNR, Ist Studio Mat Nanostrutturati, I-90146 Palermo, ItalyCNR, Ist Biometeorol, Via Caproni 8, I-50145 Florence, FI, Italy
Pagliaro, Mario
[2
]
机构:
[1] CNR, Ist Biometeorol, Via Caproni 8, I-50145 Florence, FI, Italy
[2] CNR, Ist Studio Mat Nanostrutturati, I-90146 Palermo, Italy
来源:
ENERGY SCIENCE & ENGINEERING
|
2015年
/
3卷
/
03期
关键词:
Energy efficiency;
hydrodynamic cavitation;
pasteurization;
Saccharomyces cerevisiae;
yeast;
RESOURCE-POPULATION SYSTEM;
MICROORGANISM DISRUPTION;
WATER DISINFECTION;
GENERALIZED MODEL;
REACTORS;
OPTIMIZATION;
DEGRADATION;
FOOD;
D O I:
10.1002/ese3.62
中图分类号:
TE [石油、天然气工业];
TK [能源与动力工程];
学科分类号:
0807 ;
0820 ;
摘要:
We investigate hydrodynamic cavitation to inactivate commonly employed Saccharomyces cerevisiae yeast strains in an aqueous solution using different reactors and hydraulic circuit selected to demonstrate the process feasibility on the industrial scale. The target to achieve an useful lethality of the yeast at lower temperature when compared with standard thermal and even with other cavitation processes was achieved, with 90% yeast strains lethality at lower temperature (6.3-9.5 degrees C), and about 20% lower energy input. A separate model simulating the combined thermal and cavitational effects on yeast lethality allows to accommodate the data into a comprehensive framework providing a tool to design further targeted experiments and to predict results when changing the process parameters.