将植物形态特征与遥感多谱图像相结合,可以准确地预测玉米谷物产量
Chunhwa Jang1, Nictor Namoi1, Eric Wolske1
1Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.
PloS one
|April 2, 2024
概括
使用植被指数的遥感有效预测玉米产量,特别是使用季末数据. 结合NDVI和GNDVI等指数,可以准确预测可持续的管理.
科学领域:
- 农业学是一种农业学.
- 遥感 遥感 遥感 遥感
- 精准农业 精准农业 精准农业
背景情况:
- 可持续的作物生产需要有效的 (N) 管理,以减轻环境影响.
- 遥感为监测农业系统提供了一种具有成本效益和时间效率的方法.
研究的目的:
- 评估植被指数 (VIs) 和玉米产量的形态特征的预测能力.
- 评估不同肥率和应用方法对玉米产量的有效性.
- 确定最佳时间和VI的组合,以准确预测收益率.
主要方法:
- 在V6,R3和成熟阶段使用无人机 (UAV) 衍生的VI和形态数据 (植物高度,SPAD).
- 对不同N率 (0-208公斤N ha-1) 和应用方法 (液体UAN,尿素侧装,缓释) 的玉米产量反应进行比较.
- 采用单变量和多变量回归模型 (多线性,多指数) 进行收益预测,使用像NDVI,GNDVI和NDRE这样的VI.
主要成果:
- 慢释放肥料和尿素侧装剂的特定高N率之间没有观察到显著的谷物产量差异.
- 季初的VI和V6的形态数据显示玉米产量的预测能力有限.
- 季末的VI,特别是NDVI与GNDVI或NDRE的组合,在通过回归模型预测玉米产量方面表现出高准确度.
结论:
- 季末的遥感数据,特别是组合的VI,可提供可靠的玉米产量预测.
- 多变量分析和季后测量提高了产量预测的准确性,而不是季前或单变量方法.
- 优化的N受精策略可以通过准确的产量预测模型获得信息.
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