Abstract
Research was conducted to develop a knowledge-based decision support system to assess the degree of compaction in agricultural soils. The experiments were conducted in a laboratory soil bin at the Asian Institute of Technology in three soils, namely, clay, silty clay loam, and silty loam. The research was likewise aimed to quantify the effect of tire variables (section width, diameter, inflation pressure); soil variables (soil moisture content, initial cone index, initial bulk density); and external variables (travel speed, axle load, number of tire passes) on soil compaction and to develop compaction models for soil compaction assessment. Dimensional analysis technique was used in the development of the compaction models. The soil compaction models were found to provide good predictions of the bulk density and cone index. Using the compaction models and other secondary data, the decision support system was developed to assess the compaction status of the soil in relation to crop yield. The predictions by the decision support system were validated with actual field data from earlier studies and high correlation was observed. Thus, the output of the decision support system may be able to provide useful recommendations for appropriate soil management practices and solutions to site-specific soil compaction problems.
Published Version
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