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Growth, phenology and yield modeling for wheat-fallow cropping system in Gujarat

机译:古吉拉特邦麦耕作系统的生长,候选和产量建模

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CropSyst is a daily time step crop growth simulation model that can be used to study the effect of cropping systems management on crop productivity and environment. A total five years experimental field observations (2009-10 to 2013-14) comprising four sowing dates, viz. November 1, 15, 30 and Dec 15 for wheat-fallow crop rotations were used to simulate the growth, phenology and yield for wheat cultivar GW 322 at Anand (Gujarat). Among the five years observations, initial two years observations (2009-10 and 2010-11) were used for model parameterization and remaining year's observations (2011-12 to 2013-14) were used for model performance evaluation. The results indicated that the model was able to predict the wheat phenology precisely in terms of mean bias error (MBE) and root mean square error (RMSE) which was less than 6 days for all the phenological stages except maturity date on Dec 15 sowing. Nov 15 sowing has resulted in maximum grain and biological yield and found to be optimum date for sowing followed by Nov 30 for this region while Dec 15 resulted in highest yield reduction. It was also observed that CropSystmodel was efficient in simulation of yield and biomass of wheat crop during various years of observations. The model has efficiently predicted grain and biological yield with +/- 10% of model error for wheat crop. However, it failed to predict the leaf area index (LAI) precisely. It may also be concluded that the model error were less for early and normal sown crops but increased with the delay in sowing.
机译:经纪人是一种日常时间步骤作物生长模拟模型,可用于研究种植系统管理对作物生产力和环境的影响。共有五年的实验场观察(2009-10至2013-14),包括四个播种日期,viz。用于小麦休耕作物旋转的11月1日,15日,30日和12月15日用于模拟Anand(Gujarat)的小麦品种GW 322的生长,候选和产量。在五年的意见中,最初的两年意见(2009-10和2010-11)用于模型参数化,并且剩下的年度观察(2011-12至2013-14)用于模型绩效评估。结果表明,该模型能够精确地在平均偏置误差(MBE)和均方根误差(RMSE)方面精确地预测小麦吩苯(RMSE),除了在12月15日播种的成熟日期以外的所有毒性阶段的6天。 11月15日播种导致最大谷物和生物产量,发现是播种的最佳日期,然后是该地区的11月30日,而DEC 15导致收益率最高。还观察到,在不同观测结果期间,综合症患者在模拟小麦作物的产量和生物量的模拟中有效。该模型有效地预测了麦片和生物产量,+/- 10%的小麦作物的模型误差。但是,它未能准确地预测叶面积指数(LAI)。还可以得出结论,模型错误对早期和正常的播种作物较少,但随着播种的延迟而增加。

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