CRITICAL MOISTURE CONTENT OF COMPACTED AGRICULTURAL SOILS WITH VARYING ORGANIC MATTER CONTENT

2013 
Abstract. The quantitative effect of organic matter incorporation in alleviating compaction of three different Agricultural soils in Borno State was determined in the laboratory using the standard proctor compaction test. Cow dung, groundnut haulms and chicken dung were incorporated into the soil textures before compaction at two different levels (2% and 4%) by weight. Each of the soil organic matter mixtures was subjected to three levels of compaction (5, 15 and 25 blows) at seven different moisture contents. The moisture level of compaction were selected according to the consistency limits of the soils. Measurements were made of dry bulk density and moisture content of the soils. Results obtained indicated that, addition of organic materials has no effect on the values of the critical moisture content (CMC) of the soils while decreasing those of the maximum dry bulk densities (MDBD). Results also indicated that, dry bulk density increases with increase in compactive effort until the optimum moisture content and the maximum dry bulk density (MDBD) were reached. Further increases in compactive effort and moisture content resulted in decreased dry bulk density values. Generally, it was observed that, compactive efforts on the soils increases the values of the dry bulk density while the values of the critical moisture content remains constant. For the three organic materials used in this study, cow dung was the most effective in reducing MDBD followed by groundnut haulms and then chicken dung. It has been observed from the results that, the values of the dry bulk densities depend on the density of the organic material incorporated. It was also observed that, the University Research sandy loam soil had the highest values of MDBD and lowest values of CMC and this characteristic of the sandy loam soil was followed by the Biu town sandy clay, Nguma village sandy clay and then Ngala town clay. Equations were derived for predicting MDBD and CMC.
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