期刊
PRECISION AGRICULTURE
卷 22, 期 4, 页码 1353-1376出版社
SPRINGER
DOI: 10.1007/s11119-021-09788-w
关键词
Geophysics; Precision viticulture; Electrical conductivity; Electromagnetic Induction (EMI); NDVI; Hyperspectral; Bordeaux; Vineyard soil; Grapevine vigor
资金
- Lawrence Berkeley National Laboratory-Directed Research and Development (LDRD) grant
This study in Bordeaux vineyards explores the relationship between soil classes and grapevine vigor using simple statistical methods and high-resolution datasets. Results indicate a strong correlation between soil classes and grapevine vigor, providing valuable insights for vineyard management and replanting.
Working within a vineyard in the Pessac Leognan Appellation of Bordeaux, France, this study documents the potential of using simple statistical methods with spatially-resolved and increasingly available electromagnetic induction (EMI) geophysical and normalized difference vegetation index (NDVI) datasets to accurately estimate Bordeaux vineyard soil classes and to quantitatively explore the relationship between vineyard soil types and grapevine vigor. First, co-located electrical tomographic tomography (ERT) and EMI datasets were compared to gain confidence about how the EMI method averaged soil properties over the grapevine rooting depth. Then, EMI data were used with core soil texture and soil-pit based interpretations of Bordeaux soil types (Brunisol, Redoxisol, Colluviosol and Calcosol) to estimate the spatial distribution of geophysically-identified Bordeaux soil classes. A strong relationship (r = 0.75, p < 0.01) was revealed between the geophysically-identified Bordeaux soil classes and NDVI (both 2 m resolution), showing that the highest grapevine vigor was associated with the Bordeaux soil classes having the largest clay fraction. The results suggest that within-block variability of grapevine vigor was largely controlled by variability in soil classes, and that carefully collected EMI and NDVI datasets can be exceedingly helpful for providing quantitative estimates of vineyard soil and vigor variability, as well as their covariation. The method is expected to be transferable to other viticultural regions, providing an approach to use easy-to-acquire, high resolution datasets to guide viticultural practices, including routine management and replanting.
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