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Mapping stressed wheat plants by soil aluminum effect using C-band SAR images: implications for plant growth and grain quality
Precision Agriculture ( IF 5.4 ) Pub Date : 2022-03-14 , DOI: 10.1007/s11119-022-09875-6
Mercedes Hernández 1, 2 , Andrés A. Borges 1 , Desiderio Francisco-Bethencourt 3
Affiliation  

Under toxic aluminum (Al) levels in the soil, wheat (Triticum aestivum L.) suffers stress and plant growth is affected. A method for diagnosis of plants is proposed that includes the following as a strategy: to analyze total Al in the soil, employ satellite radar imagery and calculate a vegetation index. The objective of this research, conducted at the field scale, was to explore how radar backscattering coefficients from a winter wheat canopy, combined with the normalized difference vegetation index (NDVI) and geographic information system (GIS) technology, can be used as a mapping tool for the variability of Al-stressed canopies. As a result, an analysis of covariance showed significant differences, and the lowest plant height was obtained at a high level of soil Al, as well as the minimum grain weight and magnesium content. It was found that a simple model could be used to estimate plant height from the backscattering coefficient of vertical transmit-vertical receive polarization (σ°VV), with a strong correlation (r − 0.84). In turn, a third-order polynomial regression model (R2 0.70) was proposed to estimate the NDVI from σ°VV. This model provided a good estimate of the NDVI at the stem elongation stage of growth (50 days after sowing). Detected NDVI patterns were associated with variation in canopy stress depending on polarimetric information, which, in turn, was related to soil Al levels. Thus, the maps derived from the model can monitor spatial variability, where NDVI values < 0.68 indicate stressed areas. This study provides guidance for in-season stress spatial variability caused by Al.



中文翻译:

使用 C 波段 SAR 图像通过土壤铝效应映射受胁迫的小麦植物:对植物生长和谷物质量的影响

在土壤中的有毒铝 (Al) 水平下,小麦 ( Triticum aestivumL.) 遭受压力,植物生长受到影响。提出了一种植物诊断方法,包括以下策略:分析土壤中的总铝,采用卫星雷达图像并计算植被指数。本研究的目的是在田间尺度上进行,旨在探索冬小麦冠层的雷达后向散射系数如何结合归一化差异植被指数 (NDVI) 和地理信息系统 (GIS) 技术用作制图铝应力檐篷可变性的工具。结果,协方差分析显示出显着差异,在高水平的土壤铝中获得了最低的株高,以及最小的粒重和镁含量。VV ),具有很强的相关性 (r - 0.84)。反过来,提出了一个三阶多项式回归模型(R 2 0.70)来从σ° VV估计NDVI 。该模型很好地估计了茎伸长生长阶段(播种后 50 天)的 NDVI。检测到的 NDVI 模式与取决于极化信息的冠层应力变化有关,而极化信息又与土壤铝水平有关。因此,从模型导出的地图可以监测空间变异性,其中 NDVI 值 < 0.68 表示压力区域。本研究为铝引起的季节性应力空间变异提供了指导。

更新日期:2022-03-14
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