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一种通过将WOFOST模型与Sentinel-2卫星数据同化来估计玉米杂交线的产量方法

Junyi Liu¹, Xianpeng Hou¹, Shuaiming Chen¹

¹College of Land Science and Technology, China Agricultural University, Beijing, China.

Frontiers in plant science

|September 25, 2023

概括

这项研究开发了一种新方法,利用作物模型和卫星数据来估计玉米的杂交生产线产量. 这种方法提高了玉米杂交品种的产量估计准确度,这对中国至关重要.

科学领域:

农业科学农业科学
遥感技术遥感技术遥感技术
作物建模作物建模

背景情况:

玉米杂交系对中国的种子和粮食安全至关重要.
现有的遥感方法很难区分玉米的杂交品种和杂交品种,并准确地估计它们的产量.

研究的目的:

开发和验证一种使用作物模型数据同化估计玉米近亲系产量的方法.
为了提高基于遥感的玉米同系品种的产量估计的准确性.

主要方法:

用马尔科夫链蒙特卡洛 (MCMC) 校准的世界粮食研究 (WOFOST) 模型参数用于使用马尔科夫链蒙特卡洛 (MCMC) 的玉米杂交线.
开发了在关键生长阶段将植被指数与叶面积指数 (LAI) 联系起来的实证模型.
使用集成卡尔曼波器 (EnKF) 数据同化用于像素对像素的产量估计和映射.

主要成果:

优化的WOFOST模型与EnKF同化实现了产量估计的R2为0.56和RMSE为684.90 Kg/Ha.
使用单个生长参数的简化同化方法产生了0.18的R2和949.95 Kg/Ha的RMSE.
采用作物模型和数据同化方法,在监测玉米近亲系生长和估计产量方面取得了初步成功.

结论:

综合作物模型和数据同化方法对玉米近亲系产量估计是有效的.
对作物模型的准确参数化对于区分同血统和杂交品种至关重要.
这种方法为提高中国玉米种子安全和食品安全提供了一个有希望的工具.

关键词:

在EnKF中使用.哨兵-2 卫星 - 卫星-2 哨兵-2 卫星这就是WOFOST的WOFOST.数据同化数据同化玉米杂交线条杂交线条

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