Aggragates Stability Evaluation Indices and The Most Effective Soil Characteristics: Case Study in Sugarcane Agro-Industry of Khozestan

Document Type : Research

Authors

1 Master's student in soil science, Ramin University of Agriculture and Natural Resources, Khuzestan

2 Assistant Professor of the Department of Soil Science, University of Agriculture and Natural Resources, Khuzestan, Ramin

3 Assistant Professor of Soil Science, Shahrekord University

Abstract

The description and quantification of soil structure is very important because of the many agronomic and environmental processes related to the arrangement of secondary soil units (aggregates) and their stability. The purpose of this study is to evaluate indices used to characterize soil structural stability based on Khozestan sugarcane Agro-Industries data. According to this, 155 soil samples from 0-40 cm were collected to establish regression equations predicting mean weight diameter (MWD), De Leenheer and Deboodt (DDI), Middleton’s dispersion ratio (DR) and water dispersed clay (WDC) indices and to introduce most important factors influence these indices. Further, the possibility of using the geometric mean (dg) and geometric standard deviation (σg) of soil particle diameters instead of soil particle size distribution to derive regression equations was investigated. These results indicate that sodium adsorption ratio and organic carbon were the most important factors that influence the MWDand DDI indices,respectively, with a grade of 81.8 and 27.8 for MWD and 61.3 and 15.2 for DDI. Also, among the features that influence the DR, greatest role was related to sodium adsorption ratio, whereas, clay content, organic carbon and calcium carbonateprovided later ranking of evaluation. Electerical conductivity, calcium carbonate, sodium adsorption ratio, organic carbon and sand content, almost, have the same portion in predicted WDC. Maximum correlation(R=0.97) found between MWD and DDI. Also, results showed that the descriptors of the particle size distribution (dg and σg) did not improve the accuracy of indices prediction.

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History

  • Receive Date: 15 February 2013
  • Revise Date: 20 July 2013
  • Accept Date: 22 August 2013

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