Abasalt Rostami Ajirloo; Ebrahim Amiri
Abstract
In order to investigate the effect of potassium nano fertilizer on soybean growth under cutting irrigation condition, an experiment was carried out as split plots arrangement based on completely randomized block design with three replications in Moghan plain at 2015 and 2016 cropping seasons. The main ...
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In order to investigate the effect of potassium nano fertilizer on soybean growth under cutting irrigation condition, an experiment was carried out as split plots arrangement based on completely randomized block design with three replications in Moghan plain at 2015 and 2016 cropping seasons. The main factor included four levels of irrigation normal irrigation, cutting irrigation during vegetative phase, cutting irrigation during flowering phase and cutting irrigation during grain filling phase and a sub factor included three levels of potassium nano fertilizer five, 10 and 15 kg per hectare. The results showed that at all stages of irrigation, the use of potassium nano fertilizer reduced the effect of drought stress. So that the greatest seed yield and yield components under normal irrigation and off-irrigation conditions were obtained with use of 15 kg / ha of potassium nano fertilizer. Also, the highest plant height (66 cm), the distance between the first pod of ground (20 cm), number of leaves per plant (345) and the number of lateral branches (19.66) in normal irrigation treatment with consumption 15 kg of potassium nano fertilizer was obtained and the least of them was obtained in irrigation cut during vegetative phase with use of 5 kg/ha of potassium nano fertilizer. According to the results, it can be concluded that using 15 kg / ha of potassium nano fertilizer can reduce the effects of drought stress on yield, especially in seed filling stage in soybean plant, by 15%.
Javad Taie; Ebrahim Amiri; Ahmad Aien; Naser Boroumand; Mehrangiz Jokar
Abstract
Crop Simulation Models are advanced tools to estimate crop yield and optimizing of crop management practices. This study was conducted in order to evaluate DSSAT model under autumn cropping system condition in Jiroft, Iran, 2012-2014. The field experiment which repeated in two sequential years and three ...
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Crop Simulation Models are advanced tools to estimate crop yield and optimizing of crop management practices. This study was conducted in order to evaluate DSSAT model under autumn cropping system condition in Jiroft, Iran, 2012-2014. The field experiment which repeated in two sequential years and three replications were performed as randomized complete block design in split plots. The main factor was planting date (17th, 23th, 29th September and 5th October) and its subfactor was potato cultivars (Sante, Satina and Boren). Data of first and second years of field experiment was applied respectively for calibration and evaluation of model. Data-base requirement for model was created from 1. climatic data includes: temperature, radiation, relative humidity, wind and precipitation; 2. crop data attained from field experiment, 3. soil data. Results of statistical evaluation of model showed the good fitness of simulated and actual yield performance. Simulated tuber yields were similar to their observed value with RMSE of 19% (1210 kg/ha) and high correlation between observed and simulated tuber yield (R2>0.9). Simulated biomass had 2673.5 kg/ha difference to its observed value that showed low estimation precision (RMSE>30%). This model couldn’t predict tuber initiation stage correctly (RMSE>30%). Therefore, it was concluded that DSSAT model predicted potato yield correctly but due to weak precision in estimation of phenological stage, had low assurance for use in autumn cropping system of potato under autumn cropping system in Jiroft region.