Proximal sensing of vineyard soil and canopy vegetation for determining vineyard spatial variability in plant physiology and berry chemistry

摘要

Proximal sensing is used in vineyards to precisely monitor and manage spatial and temporal variability while reducing laborious and repetitive measurements. Soil electrical conductivity (EC) and canopy vegetation indexes are two frequently assessed variables with off-the-shelf sensors. In this study, the ecophysiological variability of a commercial vineyard comprising three varieties in three blocks, Cabernet-Sauvignon (CS), Cabernet franc (CF), and Petit Verdot (PV), was investigated. Random sampling was used to continuously assess spatial variability in plant physiology and berry composition. Soil EC and NDVI were also continuously monitored throughout the season. There was a noticeable spatial pattern in the normalised differential vegetation index (NDVI) in the vineyard and soil EC. The spatial pattern of NDVI can be partially elucidated by the season-long stem water potential (Ψ_(stem)), which was lowest in the CS block. However, leaf photosynthesis did not match this spatial pattern. The spatial distribution of NDVI and soil EC did not satisfactorily explain the spatial variations in yield components and berry chemistry. Principal component analyses (PCA) were performed resulting in a clear discrimination of each of the three cultivars. Soil EC showed a significant relationship with Ψ_(stem) integrals, total skin anthocyanins and tri- to di-hydroxylated flavonoids. In each cultivar block, soil EC showed some capability to be related to plant water status, and NDVI showed a relationship with yield. Overall, this study provided evidence of the spatial variability of grapevine physiology in a commercial vineyard with three cultivars. Also, it showed that the cultivar effect and uniform crop level management can diminish the efficiency of proximal sensing, thus weakening the relationship of soil and canopy indexes with plant physiology and berry chemistry. Nonetheless, our study showed that it is possible to apply temporal proximal sensing methods when assessing plant water status, primary metabolism, yield and berry secondary metabolism, which give an indication of the possibility of managing the spatial variability of both plant physiology and berry chemistry.