Research Article Open Access

Relationship between Rice Yield and Apparent Electrical Conductivity of Paddy Soils

M.H. Ezrin, M.S.M. Amin, A.R. Anuar and W. Aimrun


Problem statement: Understanding the relationships between rice yield and soil properties such as bulk electrical conductivity is of critical importance in precision farming. The apparent Electrical Conductivity of soil (ECa) is influenced by a combination of physico-chemical properties including soluble salts, clay content and mineralogy, soil water content, bulk density, organic matter and soil temperature. Accordingly, ECa is considered as the most reliable and frequently used tools in precision farming research for the spatio-temporal characterization of edaphic and anthropogenic properties that influence crop yield. Many researchers have found positive correlation of ECa to crop yield such as corn and soy bean but not rice paddies. This study discussed on the relationship between ECa and rice yield for best practice management on paddy field. Approach: The analyses had used two reliable methods in six selected paddy lots at Sawah Sempadan, Selangor, Malaysia. Stepwise Linear Regression (SLR) and Boundary Line Analysis (BLA) techniques were used. External factors such as weather conditions, disease outbreaks, labor shortage and other factors were not considered in the data analysis and interpretation. Results: The results indicate that deep ECa (ECad) is significantly related to rice yield with R2 = 0.1246 and R2 = 0.4156 from SLR and BLA analyses, respectively. Conclusion: Results of this study can benefit farmers and researchers to understand the influence of ECa to the crop productivity.

American Journal of Applied Sciences
Volume 7 No. 1, 2010, 63-70


Submitted On: 20 November 2009 Published On: 31 January 2010

How to Cite: Ezrin, M., Amin, M., Anuar, A. & Aimrun, W. (2010). Relationship between Rice Yield and Apparent Electrical Conductivity of Paddy Soils. American Journal of Applied Sciences, 7(1), 63-70.

  • 13 Citations



  • Apparent electrical conductivity
  • precision farming
  • regression analysis
  • boundary line analysis