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008 120306t2010 my a f m 000 0 eng d
020 _aTHE0004128(Local)
039 9 _a201905132115
_bfarhana
_y201203061549
_zFida
040 _aUMP
090 _aTP156.F4 M37 2010 rs Bc.
100 0 _aMaryam Ismail
245 1 0 _aModelling of batch biopolymer fermentation /
_cMaryam Ismail
260 _aKuantan, Pahang :
_bUMP,
_c2010
300 _axiii, 79 p. :
_bill. (some col.) ;
_c30 cm. +
_e1 CD-ROM
502 _aProject paper (Bachelor of Chemical Engineering (Biotechnology)) -- Universiti Malaysia Pahang - 2010
504 _aBibliography: p. 25-26
520 3 _aThis research is about modelling of Cupriavidus necator (C. necator) growth and polyhydroxyalkanoates (PHA) production in batch fermentation and fitting the models to the data using Runge-Kutta 4th Order Method by minimizing the error between experimental data and predicted data using the Simplex Method in MATLAB R2009b software. The models and the fitting methods were first tried on data of yeast biomass growth and intracellular enzyme cytochrome p-450 production in batch fermentation while the data of C. necator growth and PHA production is being generated. Hence, data were obtained from three sources which are Jailani et. al., (1995), Ali (2009) and Firdaus (2010). The biomass growth model developed was based on Logistic Model while the model for PHA production was developed based on the assumptions that each cell contain the same amount of PHA and that PHA degrades with the same rate. Predicted data was obtained using function ode45 in MATLAB R2009b software which implements Runge-Kutta 4th Order Method while minimum error was obtained through function fminsearch in the same software which implements Simplex Method. After completing the works, it was found that the models fit very well on data Salihon et. al., (1995) and Ali (2009). However, the models were not well fitted on data Firdaus (2010) as the values of parameters were not converged.
650 0 _aFermentation
650 0 _aBiopolymers
999 _aVIRTUA40
_c1662
_d1668
999 _aVTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*6501*9992