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Showing 1 results for Langmuir Equation.

A. Samadi, E. Sepehr,
Volume 17, Issue 65 (12-2013)
Abstract

In order to determine optimum equilibrium solution phosphorus (P) concentration using P adsorption isotherm and obtain model(s) by integrating soil solution P concentration, physicochemical properties, and soil P test (available P) which predict standard P requirements to achieve maximum yield, laboratory and glasshouse experiments were conducted on 36 soil samples belonging to 15 soil series and 14 soil samples, respectively. Using wheat as a test crop, the glasshouse experiment was laid out with five P levels in a completely randomized design with three replications. Concentrations of P in solution established by adding P in the pots estimated from the sorption curve ranged from 0.2 to 1.2 mg P/L including check treatment (no P). The results showed that equilibrium solution P concentration (EPC) was almost low in comparison with the requirement for most crops (<0.2 mg/L). The amount of P adsorbed by the soils at 0.2 mg/L EPC ranged from 5 to 114 mg/kg soil. The phosphate adsorption was well described by Freundlich (R2 = 0.96) and Langmuir (R2 = 0.88) isotherms. Langmuir maximum adsorption (Xm) and Freundlich coefficient (aF) estimated from Langmuir and Freundlich equations ranged from 127 to 238 mg P /kg soil and from 43 to 211 mg P/kg, respectively. Yield of wheat in all soils approached maximum as adjusted P levels were increased to 0.4 mg P/L. The results showed that some soils studied were adequate in available P by the NaHCO3 test, but required an amount of P fertilizer by the isotherm P requirement test to obtain maximum biomass production. Soil clay content was significantly related to the soil P sorption indices, P0.4 (P sorbed at 0.4 mg P/L EPC) (R = 0.40, P<0.01), PBC (P buffering capacity) (R = 0.54, P<0.001), aF (R = 0.48, P<0.01), and Xm (R = 0.40, P<0.01). Total CaCO3 and Active CaCO3 were found to be less important factors affecting P adsorption. Using stepwise regression analysis resulted in a useful regression model including the combination of Olsen P and clay content for the prediction of standard P requirement (P0.4).

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