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优化 (Medicago sativa L.) 肥的管理,基于关键度稀释曲线模型

Yaya Duan¹, Yi Ling¹, Haiyan Li¹

¹College of Water Conservancy and Hydrpower Engineering, Gansu Agricultural University, Lanzhou 730070, China.

Plants (Basel, Switzerland)

|June 27, 2025

概括

这项研究适应了的临界稀释曲线 (CNDC) 模型,开发了营养指数 (NNI) 和累积缺乏 (Nand) 模型. 与标准尿素相比,控制释放尿素 (CRU) 显著减少了的输入,同时保持了高产量.

科学领域:

农学和土壤科学农学和土壤科学
植物营养植物营养
料作物的管理

背景情况:

关键稀释曲线 (CNDC) 模型对于作物中精确的管理至关重要,优化生产率和使用效率.
它对多年作物的应用,如 (Medicago sativa L.),一个重要的料豆类,尚未被彻底研究.
准确的状况诊断和应用率对于可持续的种植至关重要.

研究的目的:

适应和验证CNDC模型用于多年料作物草.
开发营养指数 (NNI) 和累积不足 (Nand) 模型,用于诊断的状况.
确定使用尿素和控制释放尿素 (CRU) 对的最佳施加率,并比较它们的效率.

主要方法:

在两年的实地实验中,在不同的肥 (尿素和CRU) 方案下,对进行了实地实验.
对地面生物质的临界缩曲线 (CNDC) 模型是为每个肥料类型和切割构建的.
开发和验证了营养指数 (NNI),累积不足 (Nand) 和产量反应模型;通过回归分析确定了最佳率.

主要成果:

在尿素和CRU处理下,临界度和地表生物质都表现出功率函数关系.
开发的CNDC模型显示出高可靠性,正常化根平均平方误差 (n-RMSE) 在3.1%至13%之间.
控制释放尿素 (CRU) 需要比尿素少18.4120.47%的输入,才能达到同等或更高的理论产量 (16.7620.66 t·ha−1 对于CRU和14.7617.40 t·ha−1 对于尿素).

结论:

CNDC模型适用于,使得精确的状况诊断和管理.
该研究建立了可靠的NNI和Nand模型,用于评估的状况.
控制释放尿素 (CRU) 为提供了更有效的管理策略,减少了肥料投入,提高了产量潜力.

关键词:

阿尔法萨法 (Alfalfa) 是一种植物.关键的度是关键的度.的应用率的应用率营养诊断营养诊断

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