Modeling plant response to salinity and soil nitrogen deficiency

Subject Areas : Farm water management with the aim of improving irrigation management indicators

Arezoo Akhtari ¹ , Mehdi Homaee ² , Yaghoob Hoseini ³

1 - دانشجوی دکتری؛ دانشگاه آزاد اسلامی؛ واحد علوم و تحقیقات؛ گروه خاکشناسی؛ تهران؛ ایران
2 - Professor, Department of Soil Science, Faculty of Agriculture, Tarbiat Modares University, 14116-336, Tehran, Iran
3 - Assistant Professor, Hormozgan Agricultural and Natural Resources Research Center, Bandar Abbas, Iran

Received: 2013-11-18 Accepted : 2014-09-22 Published : 2014-09-22

Keywords: Modeling, Nitrogen, Salinity,

Abstract :

Assessment of interactive effects of salinity and nitrogen deficiency is of great importance for optimal management of soil and water resources in arid and semi-­arid regions. The objective of this study was to model canola (Brassica napus L.) response to salinity under nitrogen deficiency conditions. For this reason, the soil fertility models including Liebig- Sprengel (LS) and Mitscherlich- Baule (MB) that are originally proposed for nutrient deficiency were derived such to account for simultaneous salinity and nitrogen deficiency. To obtain the required data and to assess the proposed models, an extensive experiment was conducted by different levels of salinity and nitrogen. The experimental treatments were consisted of five levels of none saline water, 3, 6, 9 and 12 dSm-1 and four nitrogen levels of 0, 75, 150 and 300 mgKg-1. Some statistics including maximum errors, root mean square error, modelling efficiency, coefficient of determination and coefficient of residual mass were used to evaluate the three proposed models. Results of these statistical analyses indicated that the proposed LS-based model can provide better estimates for relative grain yield in different nitrogen levels. The proposed MB-based model, in the salinity levels of irrigation water and interaction of salinity and nitrogen levels provided better results. It can be concluded that the proposed models can predict the interactive effect of salinity and nitrogen deficiency reasonably well.