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Modeling of soil penetration resistance using multiple linear regression (MLR)
Authors:Anis Elaoud  Hanen Ben Hassen  Nahla Ben Salah  Afif Masmoudi  Sayed Chehaibi
Institution:1.Laboratory of Natural Treatment Water, Water Research and Technologies Center,Borj Cedria,Tunisia;2.Higher Institute of Agronomic Sciences of Chott Mariem,University of Sousse,Sousse,Tunisia;3.Laboratory of Probabilities and Statistic, Faculty of Sciences of Sfax,University of Sfax,Sfax,Tunisia
Abstract:In agricultural areas, the use of machinery leads to improved yields. Nevertheless, its inadequate implementation and excessive utilization can seriously affect the soil efficiency. In fact, latter can be generated by increasing the penetration resistance and subsequently, it results in the compaction phenomenon. This problem becomes considerable with the increasing report wheel/soil. The aim of this work was to evaluate the efficiency through the prediction of soil penetration resistance (Rp) using a statistical model based on moisture content, density, tractor weight, number of passes, and the wheel inflation pressure. Experimental works (211 measurements) were analyzed and the penetration resistance was modeled using multiple linear regressions (MLR). Besides, the developed model elucidates the variables affecting the accentuation of soil Rp and allows the investigation of equations for novel sampled soils. Our results showed that the parameters related to soil and tractors were significant to explain Rp. The adopted model in the MLR analysis emphasizes that the mechanical parameters of ground measurements are statistically significant in estimating and evaluating Rp. The statistical calculation of the R 2 expresses 83% of the variance in Rp generated by the various parameters related to soil and tractor. In view of the importance of estimating the penetration resistance (Rp), the regression equation shows that the weight of the tractor and the number of passages contributed the most to the proposed model for the soil.
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