使用CERES-Maize (DSSAT) 模拟玉米生长和动态,在基于保护农业的玉米-小麦系统中的各种管理选项下
Kamlesh Kumar1,2, C M Parihar3, H S Nayak1,4
1ICAR-Indian Agricultural Research Institute (IARI), New Delhi, India.
Scientific reports
|May 22, 2024
概括
这项研究对DSSAT-CERES-Maize模型进行了校准,以准确模拟保护农业下的玉米生长和产量. 该模型有效评估了耕作和管理对作物表现和土壤动态的影响.
科学领域:
- 农业科学 农业科学
- 作物建模作物建模
- 土壤科学 土壤科学
背景情况:
- 农业实地实验是资源密集型的,并且与时空变异性作斗争.
- 机械作物生长模型为农场管理提供了一种方法来理解复杂的作物-土壤-天气相互作用.
- 保护农业 (CA) 系统需要精确的管理策略来实现最佳性能.
研究的目的:
- 在长期CA系统中校准和验证DSSAT-CERES-Maize模型来模拟玉米生长,产量和动态.
- 研究土壤温度,含量和作物吸收之间的关系.
- 探索不同耕作方式和管理对玉米产量的影响.
主要方法:
- 校准了DSSAT-CERES-Maize (v 4.8) 模型,使用2019-2020年的现场数据对关键增长阶段,LAI,生物质和产量进行校准.
- 使用2021年的数据验证了模型性能.
- 在零耕作 (ZT) 和传统耕作 (CT) 系统下比较了四种管理选项 (N0,N150尿素,绿色寻找者,尿素超颗粒).
主要成果:
- 该模型准确地模拟了玉米的成熟度 (5%的误差范围内) 和叶面积指数 (RMSE0.57,nRMSE10.33%).
- 模拟的谷物产量与测量值 (0-3%的误差) 密切匹配,在缺乏的地块中略有高估 (9-16%).
- 模型准确地捕获了土壤中酸盐-N水平 (RMSE 12.63 公斤/公,nRMSE 12.84%).
结论:
- 在不同的耕作和管理下,DSSAT-CERES-Maize模型可靠地模拟了玉米的生长,产量和土壤动态.
- 这种建模方法有助于在CA系统中更好地规划和资源管理玉米生产.
- 进一步的研究应该提高模型的能力和更广泛的应用的预测准确性.
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