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预测甜菜叶面积指数:在不同的灌和植物密度场景下评估双形函数的性能

Saba Hashempour Motlagh Shirazi¹, Fatemeh Razzaghi², Ali Shabani³

¹Water Engineering Department and Drought Research Center, School of Agriculture, Shiraz University, Shiraz, Iran.

Scientific reports

|December 29, 2025

概括

后勤理查德斯 (LR) 和希尔-希尔 (HH) 函数准确地模拟了甜菜叶面积指数 (LAI) 动态. 这些模型对于预测不同种植条件和种植方法的LAI变化是有价值的.

科学领域:

农业科学农业科学
植物生理学作物生理学
数学建模的数学建模

背景情况:

甜菜 (Beta vulgaris L.) 叶面积指数 (LAI) 对于产量预测至关重要.
简单地说,LAI动态通常表现出双西格曲线,需要适当的数学函数来准确建模.
了解不同农业实践下的LAI变化对于优化作物管理至关重要.

研究的目的:

为了评估15个sigmoid函数在糖LAI动态建模中的表现.
为了比较基于生长度日 (GDD) 和种植后日 (DAP) 的模型的准确性.
评估模型在不同灌处理,作物密度和种植方法 (直接播种与移植) 下的适用性.

主要方法:

利用 15 种不同的 sigmoid 函数来建模甜菜 LAI 数据.
使用GDD和DAP作为时间依赖变量进行校准和验证的模型.
对直接和移植种植系统的不同灌制度和种植密度的模型性能进行了分析.

主要成果:

后勤-理查德斯 (LR) 和Hill-Hill (HH) 函数在模拟甜菜LAI方面表现出卓越的性能.
在基于GDD的直接播种校准中,LR和HH函数显示出高精度 (NRMSE ≤0.05,d ≥0.99).
其他函数,如Von Bertalanffy,Weibull和Hill被认为不适合描述甜菜LAI动态.

结论:

在不同的环境条件和管理实践下,LR函数是模拟甜菜LAI变化的有价值工具.
使用LR函数准确的LAI建模可以帮助优化灌和种植密度策略.
这项研究强调了特定的Sigmoid功能的有效性,用于预测甜菜中的作物生长动态.

关键词:

戈珀茨-戈珀茨函数是一个函数.越来越多的度数数天.丘陵 - 丘陵函数后勤 - 理查德斯的功能功能.种植方法种植方法水的压力是水的压力.

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