无人驾驶飞行器 (UAV) 传感器在不同修剪策略下的葡萄园中用于估计水状态的应用
Juan C Nowack1,2, Luz K Atencia-Payares1,2,3, Ana M Tarquis1,4
1CEIGRAM, ETSIAAB, Universidad Politécnica de Madrid (UPM), 28040 Madrid, Spain.
Plants (Basel, Switzerland)
|May 25, 2024
概括
高分辨率的多光谱图像有效地估计了葡萄酒水的状态,这对于灌管理至关重要. 红色和红边带与植被指数相结合,提供了最准确的预测,无论剪裁策略如何.
科学领域:
- 农业科学 农业科学
- 遥感 遥感 遥感 遥感
- 植物生理学 植物生理学
背景情况:
- 植物水的状态受到修剪的显著影响,影响叶面积和灌需求.
- 精确监测葡萄酒水的状态对于优化干旱地区葡萄园管理至关重要.
研究的目的:
- 评估高分辨率的多光谱图像,以估计葡萄酒水的状态.
- 为了确定最佳的光谱波段和植被指数,以评估水的状态.
- 评估这些方法在不同修剪策略下的适用性.
主要方法:
- 在西班牙中部的Merlot葡萄园进行的实地研究 (2021-2022).
- 机械修剪与没有修剪策略的比较.
- 在9h和12h使用压力室测量茎水潜力 (Ψstem).
- 通过无人机 (UAV) 获取多光谱图像.
- 计算和分析各种植被指数 (VIs).
主要成果:
- 修剪管理显著影响了 Ψstem,束重,果重量和产量.
- 规范差异植被指数 (NDVI) 显示了12h与 Ψstem 的最强相关性 (R2 = 0.58).
- 一个包含红色和红边带的通用化多变量线性回归模型在预测 Ψstem 中取得了更高的准确性 (R2 = 0.74).
结论:
- 高分辨率的多光谱图像是预测葡萄酒水状况的宝贵工具.
- 红色和红边带的组合提供了一个可靠的方法来估计水的状态.
- 这种遥感方法是有效的,不管采用的修剪管理策略.
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