PT  - JOURNAL ARTICLE
AU  - Elena Kotsaki
AU  - Andrew G. Reynolds
AU  - Ralph Brown
AU  - Hyun-Suk Lee
AU  - Emily Aubie
TI  - Proximal Sensing and Relationships to Soil and Vine Water Status, Yield, and Berry Composition in Ontario Vineyards
AID  - 10.5344/ajev.2019.19018
DP  - 2019 Dec 16
TA  - American Journal of Enology and Viticulture
PG  - ajev.2019.19018
4099  - http://www.ajevonline.org/content/early/2019/12/10/ajev.2019.19018.short
4100  - http://www.ajevonline.org/content/early/2019/12/10/ajev.2019.19018.full
AB  - Proximal sensing technology was developed to overcome many of the restrictions related to satellite -or aircraft- based remote sensing systems. Ground-based proximal sensing systems collect multispectral images in the visible and near infrared wavebands and they calculate vegetation indices, such as the Normalized Difference Vegetation Index (NDVI). The objective of this study was to assess the usefulness of NDVI measurements acquired by the GreenSeeker™ optical sensor technology in viticulture and relate those measurements with grapevine physiological indicators. It was hypothesized that variability in vegetative expression, yield and plant water status would relate to NDVIs, and that differences in grape composition, including phenols and color would be identified. It was also hypothesized that spatial variability in the study plots would exhibit temporally stable patterns. Results suggested that NDVI successfully established relationships with most variables; positive relationships were exhibited with vine size, and yield components, while inverse correlations were demonstrated with phenols in red cultivars and monoterpenes in Riesling. Clustering patterns in NDVI were confirmed by k-means clustering analysis and Moran's I spatial autocorrelation index. The usefulness of GreenSeeker™ proximal sensing tool was confirmed, and was indicative of future applicability of this technology to divide vineyards into sub-blocks of different productivity.