Prediction Soil Enzyme Activity by the Use of Soil and Topographic Characteristics in Hilly Region of Semiroum District, Isfahan Province

آب و خاک

Article 22, Volume 26, Issue 3, July 2012   

Document Type: Research Article

DOI: 10.22067/jsw.v0i0.14944

Authors

S. Tajik; Sh. Ayoubi^* ; F. Nourbakhash

Department of Soil Science, College of Agriculture, Isfahan University of Technology, Isfahan, Iran

Abstract

Enzymes are so crucial in the mineralization process of organic material. Information of the soil enzymes activity is used in determining of the soil microbial properties and they are also important in soil health and quality. Topographic attributes, soil properties and soil enzymes are associated together. Hence, it is essential to know how these parameters affect on the soil enzymes activity. This study has been implemented in hilly region of Semiroum district located at southern Isfahan province, to develop a regression model between soil enzymes activity and soil and topographic characteristics. Mean annual temperature and precipitation in the studied area is 10.6°C and 350 mm, respectively. Soil sampling was done in a systematic randomly manner from the 0-10 cm surface layer. Topographic attributes were calculated by the digital elevation model with 10×10 m spatial resolution. Soil properties were determined by laboratory analysis. Multiple regression models between these parameters and soil enzymes activity were established and then the predictive models were validated using 20% of data. Results indicated soil parameters explained 33-63% of total variability of soil enzymes activity in the studied site. Topographic attributes explained 14- 15 %, and a combination of soil and topographic characteristics could explain 33-67% of total variability of soil enzymes activity. Therefore, the use of a combined data set of soil properties and topographic attributes could provide the powerful models for predicting of soil enzymes activity. These results confirmed that soil enzyme activity in the studied area is influenced by soil and topographic attributes synchronously. The results of validation ascertained that the predictors were unbiased and sufficiently accurate.

Keywords

Urease; L-glutaminase; L-asparaginase; Modeling