EXPLORING THE OPTIMUM CONDITIONS FOR MAXIMIZING THE MICROBIAL GROWTH OFCandida intermediaBY RESPONSE SURFACE METHODOLOGY

Abstract

Exploring optimum and cost-efficient medium composition for microbial growth of Candida intermedia Y-1981 yeast culture growing on whey was studied by applying a multistep response surface methodology. In the first step, Plackett-Burman (PB) design was utilized to determine the most significant fermentation medium factors on microbial growth. The medium temperature, sodium chloride and lactose concentrations were determined as the most important factors. Subsequently, the optimum combinations of the selected factors were explored by steepest ascent (SA) and central composite design (CCD). The optimum values for lactose and sodium chloride concentrations and medium temperature were found to be 18.4 g/L, 0.161 g/L, and 32.4°C, respectively. Experiments carried out at the optimum conditions revealed a maximum specific growth rate of 0.090 1/hr; 42% of total lactose removal was achieved in 24 h of fermentation time. The obtained results were finally verified with batch reactor experiments carried out under the optimum conditions evaluated.

Optimization of lipase production on agro-industrial residue medium byPseudomonas fluorescens(NRLL B-2641) using response surface methodology

“…The significant effect of the carbon source was reported to be in the range of 5–30 g L −1 for different kinds of cultures. [ 35 , 39–41 ] The evaluated values for both peptone and carbon sources are in agreement with the reported data. [ 39 , 41 ] In this work, peptone and AS source were supplied to the medium to respectively provide the organic and inorganic sources of nitrogen required by the microorganism.…”

“…The experiments were carried out in random order as suggested in many design programs. [ 22 , 31 , 35 ]…”

“…In the optimization process, the response can be related to selected factors in quadratic models. A quadratic model is supposed to be as follows [ 34 , 35 ]: where Y is the response, β 0 is the constant coefficient, X i ( i = 1–3) are variables, β i , β ii and β ij ( i and j = 1–3) are the linear, quadratic and second-order interaction coefficients, respectively. Data were processed using the Design-Expert 6.0 program (trial version) and an analysis of variance (ANOVA) test was conducted to obtain the interaction between the process variables and the response.…”

“…A general mathematical expression ( Equation (2) ) was used to locate the stationary points. [ 21 , 34 , 35 ] Writing the second-order model in matrix notation, we have where where b is a vector of the first-order regression coefficient and B is a symmetric matrix whose main diagonal elements are the pure quadratic coefficients ( β ii ) and whose off-diagonal elements are one-half of the mixed quadratic coefficients ( β ij , i ≠ 1). The stationary points ( x s ) are the solution of Equation (3) .…”

Nuclear and mitochondrial ribosomal ratio as an index of animal growth rate

“…Different animal species have different growth rates as part of their life histories and survival strategies (Pianka 1970). Under optimum environmental conditions, organisms are capable of maximizing their growth rate and productivity (Karakiri et al 1991;Yönten and Aktaş 2014). However, changes in environmental conditions, such as temperature (Logan et al 1976;McCarthy et al 1998), nutrition (Urabe et al 1997), salinity (Boeuf and Payan 2001), and daylight cycle (Martínez-Jerónimo 2012), could reduce the animal's growth rate.…”