BEBERAPA SIFAT FISIKA KIMIA TANAH YANG BERPENGARUH TERHADAP MODEL KECEPATAN INFILTRASI PADA TEGAKAN MAHONI, JABON, DAN TREMBESI DI KEBUN RAYA PURWODADI
BEBERAPA SIFAT FISIKA KIMIA TANAH YANG BERPENGARUH TERHADAP MODEL KECEPATAN INFILTRASI PADA TEGAKAN MAHONI, JABON, DAN TREMBESI DI KEBUN RAYA PURWODADI
Abstract
The research was conducted at the Purwodadi Botanical Gardens in three areas covered by the dominant vegetation Mahoni (Swietenia macrophylla), Jabon (Anthocephalus cadamba) and trembesi (Samanea saman) in January to May 2012. The purpose of this study was to obtain a model infiltration rate (cm/h) that was influed by physical and chemical properties of the soil that exist under the vegetation. Physical and chemicalparameters of soil chemical properties is observed macropore (%), organic matter (%), percentage of the fraction silt (%), sand(%), and clay(%), and bulk density (BD) (g/cm3). The six factors are thought to differ indirectly because of the specification and morphology of the dominant plant species shelter. Data infiltration was collected by using the ring infiltrometer, while macroporosity tested with metylen blue method, the properties of the other physical chemical factortested by laboratory of Department of Soil, Brawijaya University. The model derived from the analysis of the regression equation using SPSS software version 17.0. The study produced three different models of infiltration rate on each plot different, they were Y = - 15,8 + 17,3 X1 - 1,09 X2 + 1,53 X3 + 0,001 X4 - 21,3 X6 (Mahoni's plot);Y = - 108 + 53,0 X1 - 0,68 X2 + 5,27 X3 - 0,470 X4 + 59,7 X6 (Jabon's plot); Y = - 20,1 + 17,4 X1 - 1,06 X2 + 1,57 X3 + 0,082 X4 - 21,6 X6 (Trembesi's plot). Y= Infiltration rate (cm/h), X1= macropore (%), X2= organic matter (%), percentage of the fraction silt (%) (X3), sand (%) (X4), and X6= bulk density (g/cm3). In the equation not found factor X5 (clay fraction) helped form a model because of multicollinearity analysis obtained by assuming that the clay fraction still contains a linear relationship (correlated) with other variables.