Fatemeh salmani; afshin soltani; Ebrahim Zeinali; Hossein Shahkoomahali
Abstract
In order to simulate transplantation, the parameters related to cotton seedling growth are firstly measured in a factorial experiment in a randomized complete block design at Gorgan University of agricultural sciences and natural resources within 2018. The parameters are then utilized in SSM-iCrop2 Model. ...
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In order to simulate transplantation, the parameters related to cotton seedling growth are firstly measured in a factorial experiment in a randomized complete block design at Gorgan University of agricultural sciences and natural resources within 2018. The parameters are then utilized in SSM-iCrop2 Model. In the simulation section, four seedling size based on the leaf area (namely 17, 22, 27, and 37 cm-2 per plant) are evaluated in 4 planting dates (15 June, 1 July, 15 July, and 30 July). Results show that in early planting date, seedling transplantation rushes the process of crop maturation for 43 to 49 days. However, this has had no significant effect on yield values (from 453 to 461 g/m2) and net water requirement (312 to 316 mm). The usual sowing date causes the crop to mature between 27 and 38 days (earlier vacant land), whereas seed sowing at this planting date impairs the subsequent crop cultivation. At this planting date, as in early planting, transplanting has no strong effect on the yield (from 444 to 452 g/m2) and water requirement (299 to 308 mm). In a late planting date, seedling transplanting with four seedling sizes between 1 and 5 days results in premature seed germination, even though seed cultivation impairs subsequent planting. At this planting date, transplanting has a noticeable effect on the yield (361 to 441 g/m2), but the amount of pure irrigation (271 to 300 mm) remains unaffected by transplanting.
Mostafa Keshavarz Mehr; Hosein Moghaddam; Mostafa Oveisi; Javad Bazrafshan
Abstract
The present research has been conducted to parameterize and evaluate the APSIM-Wheat model for winter wheat and to use the model for evaluation of climate change effects on grain yield. The model is used to simulate leaf area index, dry matter, and grain yield of Roshan cultivar winter wheat in Karaj ...
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The present research has been conducted to parameterize and evaluate the APSIM-Wheat model for winter wheat and to use the model for evaluation of climate change effects on grain yield. The model is used to simulate leaf area index, dry matter, and grain yield of Roshan cultivar winter wheat in Karaj and Khomein regions between 2014 and 2015, under four irrigation regimes and three levels of nitrogen fertilizers. The experiments have been conducted in both regions as split-plot in a randomized complete block design. Irrigation is considered as main plot and nitrogen as a sub-plot. Model parameterization is based on observational data from full irrigation and 200 kg/ha nitrogen treatment in both regions. Results from the model evaluation show that the simulated values closely predict the observed values so that the RMSE in both regions is less than 670 and 450 kg/ha for biomass and yield, respectively, being below 0.56 for leaf area index as well. Normalized RMSE in all treatments has been below 17.8%, with Wilmot's index being above 0.82. The evaluation of model shows high performance and its possible use in other studies. Results from climate change analysis show that increasing the temperature from 0 to 5 °C leads to a maximum reduction of 75% in grain yield and an increase in carbon dioxide concentration, resulting in a maximum increase of 24% and, if the temperature increase exceeds three degrees Celsius, the grain yield will decrease in all possible concentrations of carbon dioxide.
Benjamin Torabi; Najebullah Ebrahimi; Afshin Soltani; Ebrahim Zeinali
Abstract
The present study was conducted to parameterize the SSM_iCrop model and evaluate the prediction of growth and development of faba bean in Gorgan climate condition. This study was carried out on faba bean cv."Barkat" as split-plot in randomized complete block design with four replications at Gorgan University ...
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The present study was conducted to parameterize the SSM_iCrop model and evaluate the prediction of growth and development of faba bean in Gorgan climate condition. This study was carried out on faba bean cv."Barkat" as split-plot in randomized complete block design with four replications at Gorgan University of Agricultural Sciences and Natural Resources in 2015-2016. The experimental factors consisted of planting date (27 November, 25 December and 31 January) and plant density (5, 15, 25 and 35 plants/m2). The parameters of phonological stages, leaf expansion and senescence, production and distribution of dry matter and water balance were estimated using the present data experiment and other data. The results of model evaluation showed that, it can well predict, days to flowering (RMSE = 3.8 and CV =4.1), days to maturity (RMSE = 11.9 and CV= 8.1), node number on main stem (RMSE = 1.7 and CV = 10.0), leaf area index (RMSE =0.8 CV =28.8), biological yield (RMSE = 158.5 and CV =21.6) and seed yield (RMSE = 118.6 and CV = 24.7). Therefore, the SSM_iCrop model can be used to evaluate the agronomic management and analyze the growth and yield of faba bean in Gorgan conditions.
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.