Simulation of Soybean Growth under Sowing Date Management by CROPGRO Model
Farzad Paknejad, Pouria Farahani Pad, Mohammad Nabi Ilkaee and Faezeh Fazeli
DOI : 10.3844/ajabssp.2012.143.149
American Journal of Agricultural and Biological Sciences
Volume 7, Issue 2
Problem statement: Always because of weather change, determine of optimum sowing date in each zone is difficult. Dynamic models can help us for solving this problem. In order to evaluation of soybean simulation by using of CROPGRO-Soybean model at four sowing date in field research of Azad university of Karaj branch a field experiment conducted in form of split plot in based on randomize complete block design with four replication in 2009s. Approach: At this experiment simulation of some traits such Leaf Area Index (LAI), Leaf Dry Weight (LDW), Stem Dry Weight (SDW) and Biomass (B) evaluated for cv. Williams using of CROPGRO-Soybean. According to results, model was successful in the traits simulation, because of high Wilmot coefficient produced (0.6), 20 days after planting to the end of the growth duration. Results: Model explained well stem dry weight, as correlation coefficient in each sowing date was significant (p<0.01). Simulation precision for biomass was suitable, as coefficient differentiation was significant (p<0.01) for first to fourth sowing date (S1-S4) 0.889, 0.986, 0.909 and 0. 796, respectively. These statistic parameters designated high ability of model for simulation of some traits measured in soybean for four sowing date management. Conclusion: We can use by model for sowing date management of soybean in Karaj climate condition, of course after repetitions of experiment and doing of model calibration. We proposed that soil and weather data measured in each place of experience and also plant morphology parameter measured precisely because this help to us for obtaining of objects.
© 2012 Farzad Paknejad, Pouria Farahani Pad, Mohammad Nabi Ilkaee and Faezeh Fazeli. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.