Effect of Different Planting Densities and Irrigation Managements on Rice (Tarom Hashemi Variety) Yield and Yield Components in Kooshal Lahijan Region, Guilan Province

Document Type : Research Paper


1 Water Sci. and Eng. Dept., College of Agriculture and Natural Resources, Science and Research Branch, Islamic Azad University, Tehran, Iran

2 Water Engineering Department, Islamic Azad University - Lahijan Branch, Lahijan, Iran


. In order to study the effect of different irrigation managements and planting densities on Tarom Hashemi cultivar, an experiment was conducted in a randomized complete block design (RCBD) with three replications at Koshal-Lahijan in north of Iran during cropping seasons of 2014 and 2015. There were 5 levels of irrigation treatments in this research including: I1 = Full irrigation, I2 = Saturation, I3 = Irrigation with 8 days alternative before anthesis, I4 = Irrigation with 8 days alternative after anthesis, I5= Irrigation with 8 days alternative whole growth season) and there were 3 levels of density including, D1=15×15, D2=20×20, D3=25×25cm. Evaluation of calculated and measured yield was done with adjusted coefficient of correlation; T test of means; and by absolute and normalized root mean square errors (RMSE). Combined variance analysis showed that the effect of irrigation treatment and plant density on measured traits were significantly different (p<0.01). Irrigation with 8 days alternative before anthesis with only 4.88 percent yield reduction could be accounted as a treatment with maximum water use efficiency in all treatments while it saved 13.6 percent of water consumption. There was positive correlation between Grain yield and Total number of panicles, Number of tillers but there was negatively correlated with the Number of filled grains per panicle. According to results it is possible to predict rice production function under conditions of water deficit in different densities using 1000-grain weight, Total number of panicles, Number of filled grains per panicle. Quadratic equation on the one hand with the lowest root mean square error and the lowest normalized root mean square error and on the other hand with the highest correlation indicated best simulation in calibration process. In addition the amount of error in the validation process reduced so the quadratic production function would be recommended.


Main Subjects

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