Modeling Response of Tomato (Solanum lycopersicum) under Simultaneous Water Salinity and Nitrogen Deficiency Stresses

Abstract:
Salinity is considered as one of the main problems affecting the growth and yield of many plants. Salinity tolerance varies with the amount of nitrogen uptake. The aim of the study was modeling the response of tomato (Solanum lycopersicum) under simultaneous salinity and nitrogen deficiency stresses. The indoor pot experiment was conducted in Damavand region, Iran, in 2015. The experiment was carried out on tomato plant in a factorial randomized complete block design with 3 replications. The treatments consisted of six levels of salinity (1, 2, 4, 6, 8 and 10 dS/m) and three levels of nitrogen including zero, 50 and 100 percent of the N-fertilizer needs. The maximum dry matter yield (25.8 gr) was obtained in the treatment with salinity of 1 dS/m and fertilizer consumption of 100%, while the minimum dry matter yield (5.8 gr) belonged to the treatment with salinity of 10 dS/m and no fertilizer application. Modified Liebig-Sprengel (LS) and Mitscherlich-Baule (MB) models were used to evaluate tomato response to nutrients. Comparison of statistics showed that for modeling tomato plants response to simultaneous salinity and nitrogen stresses, modified MB model (d=0.95) fitted better to the measured data compared to modified LS model (d=0.88). Therefore, modified MB model was recommended to estimate relative yield of tomato. Also, results showed that, at a fixed salinity level, by increasing amount of nitrogen application, the yield of dry matter was increased, while yield of dry matter decreased with increasing salinity. Threshold of yield decline in saline conditions is not fixed and depends on the amount of nitrogen in the soil. Decline of relative yield with increase in salinity wasn’t significant in zero-nitrogen treatment, which showed the influence of nitrogen deficiency relative to salinity. Therefore, threshold of tomato yield decline could be increased by nitrogen fertilizer management.
Language:
Persian
Published:
Journal of Water Research in Agriculture, Volume:31 Issue: 1, 2017
Pages:
87 to 104
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