پژوهشهای زراعی ایران (Jun 2020)
Simulation Effects of Sowing Date on Growth and Yield of Rainfed Chickpea (Cicer arientinum L.) by CROPGRO-CHICKPEA Model
Abstract
Introduction Simulation 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 CROPGRO-Chickpea 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 CROPGRO-Chickpea model (2) to evaluate the performances of the CROPGRO-Chickpea model in simulating chickpea cultivars growth, development and grain yield in different sowing dates under Kermanshah climatic conditions. Materials and Methods This experiment was carried out in a split-plot 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 Discussion The 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 CROPGRO-Chickpea 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 ha-1 that related to sowing date of 10 March 2017 treatment. Conclusions Based 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 CROPGRO-Chickpea 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.
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