Articles
Use of remote sensing to estimate plant water status caused by different pruning strategies in ‘Merlot’ vineyards in central Spain
Article number
1409_31
Pages
231 – 240
Language
English
Abstract
Spain counts roughly 941,000 ha of vineyards, of which 41% are grown under irrigation systems.
Water status is a relevant parameter in grapevines as it affects yield, fruit composition and wine quality.
Water stress reduces photosynthetic activity and vegetative growth and limits berry ripening.
In addition to irrigation management, pruning determines plant water status due to its effects on leaf area.
This study aims to assess the use of high-resolution multispectral imagery (0.12 m pixel‑1) to estimate plant water status through different vegetation indexes (VI) and evaluate which is most suitable for determining it.
Another objective is determining if SWP-VI relations can include vines under different pruning management.
This work was carried out in a commercial ‘Merlot’ vineyard in Yepes (Toledo), an arid area in central Spain where rainfall and irrigation water availability are scarce.
The vines were established in 2002 and arranged on a trellis with a plantation spacing of 2.6×1.1 m.
Two different pruning strategies are carried out: mechanical pruning and no pruning.
The SWP measurements were taken at two different solar times (9:00 and 12:00) using a pressure chamber.
Images were obtained using a multispectral camera mounted on a UAV at the same times as the field SWP measurements were taken, and different VIs were calculated (NDVI, RDVI, TCARI, OSAVI and TCARI/OSAVI). Results have shown that the no-pruning system presents lower values of SWP, therefore, higher levels of water stress throughout the different days and measurements.
These differences were also found in the values of the VIs.
Non-pruned vines presented lower values of NDVI, RDVI and OSAVI than pruned and higher values for TCARI. Linear regressions between SWP and NDVI, TCARI and RDVI presented the tightest correlations at noon solar time (R2: 0.82 and 0.81), although OSAVI and TCARI/OSAVI showed significant correlations too.
Solar noon flights achieved higher R2 values on all evaluated VIs.
Water status is a relevant parameter in grapevines as it affects yield, fruit composition and wine quality.
Water stress reduces photosynthetic activity and vegetative growth and limits berry ripening.
In addition to irrigation management, pruning determines plant water status due to its effects on leaf area.
This study aims to assess the use of high-resolution multispectral imagery (0.12 m pixel‑1) to estimate plant water status through different vegetation indexes (VI) and evaluate which is most suitable for determining it.
Another objective is determining if SWP-VI relations can include vines under different pruning management.
This work was carried out in a commercial ‘Merlot’ vineyard in Yepes (Toledo), an arid area in central Spain where rainfall and irrigation water availability are scarce.
The vines were established in 2002 and arranged on a trellis with a plantation spacing of 2.6×1.1 m.
Two different pruning strategies are carried out: mechanical pruning and no pruning.
The SWP measurements were taken at two different solar times (9:00 and 12:00) using a pressure chamber.
Images were obtained using a multispectral camera mounted on a UAV at the same times as the field SWP measurements were taken, and different VIs were calculated (NDVI, RDVI, TCARI, OSAVI and TCARI/OSAVI). Results have shown that the no-pruning system presents lower values of SWP, therefore, higher levels of water stress throughout the different days and measurements.
These differences were also found in the values of the VIs.
Non-pruned vines presented lower values of NDVI, RDVI and OSAVI than pruned and higher values for TCARI. Linear regressions between SWP and NDVI, TCARI and RDVI presented the tightest correlations at noon solar time (R2: 0.82 and 0.81), although OSAVI and TCARI/OSAVI showed significant correlations too.
Solar noon flights achieved higher R2 values on all evaluated VIs.
Authors
J.C. Nowack, A.M. Tarquis, L.K. Atencia, P. Cuello, M. Gómez-del-Campo
Keywords
water stress, stem water potential, vegetation index, UAV
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