THE CHARACTERISTICS OF SOYBEAN PHYTASE

Soybean phytase was extracted with 2% CaCl₂ and partially purified by ammonium sulphate fractionation followed by dialysis in 0.01 M tris-maleate buffer, pH 6.5. The enzyme showed an optimum pH of 4.8 and optimum temperature of 60°C. The phytase was partially inhibited at high substrate concentration, with an optimum substrate concentration at 20 mM and a K_m value of 2.4 × 10^-3 M. V_max was 0.22 μmole P_i liberated/min/mL enzyme. The inactivation and activation energies for the hydrolysis of phytic acid were approximately 47,000 cal/mole and 11,100 cal/mole, respectively. Enzyme activity was inhibited by about 25%, 23% and 22% in the presence of 10^-3 M Zn⁺⁺, Cu⁺⁺ and Hg⁺⁺, respectively, and was also decreased by about 85% in the presence of 10^-1 M N-ethylmaleimide and sodium fluoride. Reducing and chelating agents at concentrations up to 10^-1 M inhibited activity by about 50% and by more than 90%, respectively.     

Multiobjective water resources investment planning under budgetaryand socio-technical uncertainties

An integration of stochastic dynamic programming (SDP) and integer goal programming (IGP) modeling framework is proposed to handle problems of multiobjective-multicriteria sequential decision making under budgetary and socio-technical uncertainties inherent in water resources investment planning. In the proposed SDP model, probabilities of the funding levels in any time period that are generated using a subjective model are employed to handle budgetary fluctuations. This subjective model consists of historical data as a basic rate, functional relationships among inter-related parameters of the SDP model, scenarios of future budget availability, and subjective inputs elicited from a group of decision makers through a collective opinion technique. Application of the SDP model primarily yields an optimal investment planning policy that recognizes the possibility that actual funding received maybe less than that anticipated, and therefore the projects being implemented under the anticipated budget would be interrupted. In this integrated model, economic return of each level of investment decision together with its associated project portfolio is determined by the IGP model based on goals and criteria preferences with explicit consideration to socio-technical uncertainty