کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
2768 130 2016 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Validation of a predictive model for fed-batch and continuous lipids production processes from acetic acid using the oleaginous yeast Cryptococcus curvatus
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی بیو مهندسی (مهندسی زیستی)
پیش نمایش صفحه اول مقاله
Validation of a predictive model for fed-batch and continuous lipids production processes from acetic acid using the oleaginous yeast Cryptococcus curvatus
چکیده انگلیسی


• A growth and lipid production model was built from fed-batch culture.
• The model predicted the optimal parameters for lipid production in chemostat.
• Experimental data validated the growth and lipid production model.
• High lipid content (above 50%) was obtained during experimental continuous culture.
• The specific lipid productivity was the highest reported in literature on acetate.

This study focuses on the use of acetic acid as carbon source for cell mass and lipid production using an oleaginous yeast, Cryptococcus curvatus. To improve this cell mass and lipid production on acetic acid, a numerical model was built to predict the yeast behavior. The model was first calibrated and validated on a fed-batch culture of the oleaginous yeast grown on acetic acid. After the validation step, this model was used as a predictive tool to search for optimal dilution rate and C/N ratios for continuous culture. A continuous culture was then launched using these culture parameters, revealing that the experimental data fitted the model predictions. At steady-state, cell mass concentration was stabilized at 26.7 g/L containing 48–53% of lipid content. A maximal lipid productivity of 0.54 g L−1 h−1 was obtained, which was superior to those reported in literature. This model could be qualified as a mechanistic one since it allows understanding reactions underlying the lipid production process. The experimental data fitted the model predictions, which confirmed that the use of a model is a powerful and predictive tool which could help the operator to process parameters to improve the culture.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Biochemical Engineering Journal - Volume 111, 15 July 2016, Pages 117–128
نویسندگان
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