article · Irrigation Science
This study investigated water status variability within a 2.42-hectare commercial Cabernet Sauvignon vineyard block, aiming to find more efficient methods than laborious standard measurements like midday stem water potential (Ψ SWP). Researchers used remote sensing tools, specifically canopy fraction-based vegetation indices (VIs) derived from multispectral unmanned aerial vehicle (UAV) imagery, alongside standard soil and plant water status evaluations. They monitored 31 vines for Ψ SWP throughout the growing season, finding the highest variability at véraison, which correlated with soil water content patterns. While canopy fraction-based VIs did not significantly improve correlation with Ψ SWP compared to mean VIs, fractional cover showed a similar trend to plant water stress. The integration of NDVI canopy and NDRE mean with additional parameters like temperature, humidity, vapour pressure deficit, soil water content, and fractional cover could serve as an indicator for mapping water stress variability.
Grapevine water stress significantly impacts yield and quality, making efficient monitoring crucial for vineyard management. This research explores how remote sensing, combined with other data, could provide a less labour-intensive way to identify and map water stress variability, helping growers optimise irrigation and improve crop outcomes.
This research is early-stage, investigating the utility of remote sensing and integrated data for mapping water stress variability in vineyards. It could inform the development of decision-support tools for viticulturists and vineyard managers, enabling more precise irrigation strategies. The findings suggest a pathway towards more efficient water management in commercial viticulture, potentially reducing costs and improving grape quality.
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Abstract Water stress is a major factor affecting grapevine yield and quality. Standard methods for measuring water stress, such as midday stem water potential (Ψ SWP ), are laborious and time-consuming for intra-block variability mapping. In this study, we investigate water status variability within a 2.42-ha commercial Cabernet Sauvignon block with a standard vertical trellis system, using remote sensing (RS) tools, specifically canopy fraction-based vegetation indices (VIs) derived from multispectral unmanned aerial vehicle (UAV) imagery, as well as standard reference methods to evaluate soil and plant water status. A total of 31 target vines were monitored for Ψ SWP during the whole growing season. The highest variability was at véraison when the highest atmospheric demand occurred. The Ψ SWP variability present in the block was contrasted with soil water content (SWC) measurements, showing similar patterns. With spatial and temporal water stress variability confirmed for the block, the relationship between the Ψ SWP measured in the field and fraction-based VIs obtained from multispectral UAV data was analysed. Four UAV flights were obtained, and five different VIs were evaluated per target vine across the vineyard. The VI correlation to Ψ SWP was further evaluated by comparing VI obtained from canopy fraction (VI canopy ) versus the mean (VI mean ). It was found that using canopy fraction-based VIs did not significantly improve the correlation with Ψ SWP (NDVI canopy r = 0.57 and NDVI mean r = 0.53), however fractional cover ( f cover ) did seem to show a similar trend to plant water stress with decreasing canopy size corresponding with water stress classes. A subset of 14 target vines were further evaluated to evaluate if additional parameters (maximum temperature, relative humidity (RH), vapour pressure deficit, SWC and fractional cover) could serve as potential water stress indicators for future mapping. Results showed that the integration of NDVI canopy and NDRE mean with additional information could be used as an indicator for mapping water stress variability within a block.
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DOI: 10.1007/s00271-023-00907-1
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