شبیه‌سازی اثرات تاریخ کاشت بر رشد و عملکرد نخود دیم (cicer arientinum l.) توسط مدل cropgro-chickpea

به‌منظور شبیه‌سازی اثرات تاریخ کاشت بر رشد و عملکرد نخود دیم منطقه کرمانشاه توسط مدل cropgrochickpea، آزمایشی به صورت کرت‌های خرد شده در قالب طرح پایه بلوک‌های کامل تصادفی با 3 تکرار در مزرعه تحقیقاتی پردیس کشاورزی و منابع طبیعی دانشگاه رازی در سال زراعی 961395 اجرا شد. تیمارها شامل سه تاریخ کاشت (10 اسفند، 20 اسفند و 17 فروردین) به‌عنوان عامل اصلی و چهار رقم نخود (بیونیج، عادل، آرمان و ilc482) به‌عنوان عامل فرعی بود. ضرایب ژنتیکی ارقام توسط بخش محاسبه ضرایب ژنتیکی برای تاریخ کاشت 10 اسفند محاسبه شد. نتایج واسنجی نشان داد مدل قادر است با حداقل اختلاف، ویژگی‌های رشد و نمو را برای ارقام نخود شبیه‌سازی کند که بیانگر دقت بالای ضرایب ژنتیکی محاسبه شده بود. نتایج ارزیابی‌های مدل نشان داد که میانگین nrmse وزن خشک کل برای ارقام مورد بررسی 5/16 درصد میانگین مشاهده‌ها بود. میانگین nrmse عملکرد دانه نیز برای ارقام ذکر شده 5/13 درصد میانگین مشاهده‌ها بود. هم در شرایط مزرعه و هم در شبیه‌سازی تاخیر در کاشت منجر به کاهش عملکرد نخود شد. بیشترین عملکرد دانه مشاهده شده و شبیه‌سازی شده برای سال زراعی 961395 به‌ترتیب، 6/1326 و 6/1279 کیلوگرم در هکتار در تاریخ کاشت 20 اسفند حاصل شد. به‌طور کلی نتایج نشان داد که مدل cropgrochickpea قادر است واکنش ارقام نخود در تاریخ کاشت‌های مختلف را تحت شرایط اقلیمی منطقه مورد مطالعه با دقت قابل قبولی پیش‌بینی کند که این نشان‌دهنده دقت بالای ضرایب ژنتیک محاسبه شده در بخش واسنجی مدل است.

Simulation Effects of Sowing Date on Growth and Yield of Rainfed Chickpea (Cicer arientinum L.) by CROPGRO-CHICKPEA Model

IntroductionSimulation crop models allow to represent growth, phenological development and yield of crops and to evaluate new technologies or conditions not yet explored. The DSSAT (Decision Support System for Agrotechnology Transfer) is one of the most widely used modeling systems across the world. The DSSAT was developed with a modular structure to facilitate its maintenance and to include additional components to simulate cropping systems, considering different soils, climates, and management conditions. The DSSAT has also proven to be a useful tool for selecting improved agricultural practices. Currently, the DSSAT is able to incorporate models of 27 different crops, including several cereal grains, grain legumes, and root crops. The CROPGROChickpea model is part of the DSSAT model. This model allows simulating the development and yield of the grain legumes, to represent and to evaluate the influence of multiple environmental and agronomic factors. Among all management practices, selecting optimum sowing date helps in minimizing the effect of high temperatures during the grain filling period responsible for reduction of grain yield. Therefore, the objectives of the present study were: (1) to estimate the genetic coefficients and calibrate the CROPGROChickpea model (2) to evaluate the performances of the CROPGROChickpea model in simulating chickpea cultivars growth, development and grain yield in different sowing dates under Kermanshah climatic conditions.Materials and MethodsThis experiment was carried out in a splitplot design with three sowing dates (28 February, 10 March and 6 April) as main plots and 4 current chickpea cultivars (Bivanij, Adel, Arman and ILC482) as sub plots with three replications at 2017. The required model inputs consisted field management, daily weather conditions, soil profile characteristics, and cultivar characteristics. The cultivar coefficients were obtained under optimum conditions (i.e., minimum stress in weather and nutrients). The genetic coefficients of the chickpea cultivars i.e. Bivanij, Adel, Arman and ILC482 were determined using the GenCal software of DSSAT v 4.6 for sowing date of 28 February treatment. Model performance was evaluated by comparing simulated and measured values of chickpea cultivars phonological development stages (DVS), leaf area index (LAI), total dry weight (TDW) and grain yield (GY) for another sowing date treatments (10 March and 6 April) by root mean square error (RMSE), normalized RMSE (nRMSE) and index of agreement (d).Results and DiscussionThe results of model calibration showed that there were very good agreements between the DVS, LAI, TDW and GY of observed and simulated values. The results of the model validation also indicated that the CROPGROChickpea model was able to accurately simulate DVS and yield for chickpea cultivars. The nRMSE values for Bivanij, Adel, Arman and ILC482 of LAI were 26.1, 27.9, 28.3 and 20.1%, respectively. The index of agreement (d) for LAI ranged from 0.8 to 0.9. The nRMSE average for evaluated cultivars of TDW was 16.5%. The index of agreement (d) for TDW was 0.99. The nRMSE average for evaluated cultivars of GY was 13.5%. The index of agreement (d) for GY ranged from 0.96 to 0.98. For both simulated and measured conditions the late sowing date led to reduce in the grain yield. The greatest grain yield of simulated and measured were 1279.7 and 1326.6 kg ha1 that related to sowing date of 10 March 2017 treatment.ConclusionsBased on the results of model calibration, it can be concluded that the estimated of genetic coefficients by the GenCalc software were very robust in simulating the phenological development stages and growth of chickpea. The results of model validation showed that the CROPGROChickpea model was able to give an accurate simulation of all studied traits of chickpea cultivars except leaf area index in different sowing date under Kermanshah climate conditions.