Investigating the growth kinetics in sourdough microbial associations

被引:11
作者
Altilia, Samuele [1 ]
Foschino, Roberto [2 ]
Grassi, Silvia [2 ]
Antoniani, Davide [2 ]
Dal Bello, Fabio [3 ]
Vigentini, Ileana [2 ]
机构
[1] Univ Milan, Dept Phys, Milan, Italy
[2] Univ Milan, Dept Food Environm & Nutr Sci, Via G Celoria,2, I-20133 Milan, Italy
[3] Sacco Syst, Cadorago, Como, Italy
关键词
Fructilactobacillus sanfranciscensis; Kazachstania humilis; Sourdough; Growth kinetics; Microbial association; Predictive microbiology; Growth modelling; LACTIC-ACID BACTERIA; LACTOBACILLUS-SANFRANCISCENSIS; CANDIDA-MILLERI; POPULATION-DYNAMICS; PROCESS PARAMETERS; FERMENTATIONS; MANUFACTURE; MICROFLORA; DIVERSITY;
D O I
10.1016/j.fm.2021.103837
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
In this study we investigated the effect of the single strain in stabilization of type I sourdough microbial associations by crossing six different Fructilactobacillus sanfranciscensis with five Kazachstania humilis strains. Furthermore, we compared three predictive models, Zwitwering based on Gompertz's equation, Baranyi and Roberts' function and Schiraldi's function to evaluate which one best fitted the experimental data in determining the behaviour of co-cultivated microorganisms. Specific growth rates (mu m) and lag time (lambda) values for each mixed population were assessed. Results showed that the different F. sanfranciscensis strains significantly steer the growth kinetics within the pair and affect the ratio bacterial/yeast cells, as data analysis confirmed, whereas K. humilis accommodates to the bacterial strain. To compare the growth models, Root Mean Square (RMS) values were calculated for each predicted curve by implementing an algorithm based on an iterative process to minimize the deviation among observed and calculated data. Schiraldi's function performed better than the others, revealing, on average, the smallest RMS values and providing the best fitting for over 70% of co-cultivation experiments. Models prove to be consistent in predicting growth kinetics of microbial consortia too.
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页数:10
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