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Estimation of Water Stress in Grapevines Using Proximal and Remote Sensing Methods

1
Institute of Biometeorology (IBIMET), National Research Council (CNR), Via Caproni 8, 50145 Florence, Italy
2
Institute of Biometeorology (IBIMET), National Research Council (CNR), Via P.Gobetti, 101, 40129 Bologna, Italy
3
Institute of Clinical Physiology (IFC), National Research Council (CNR), Via Moruzzi 1, 56124 Pisa, Italy
4
Institute of Biometeorology (IBIMET), National Research Council (CNR), Traversa La Crucca, 3, 07100 Sassari, Italy
5
AGRIS Sardegna, Loc. Bonassai S.S. 291 Sassari-Fertilia—Km. 18,600, 07100 Sassari, Italy
*
Author to whom correspondence should be addressed.
This paper is an extended version of our paper published in Acta Horticulturae 2017—International Symposium on Sensing Plant Water Status—Methods and Applications in Horticultural Science.
Remote Sens. 2018, 10(1), 114; https://doi.org/10.3390/rs10010114
Received: 6 December 2017 / Revised: 11 January 2018 / Accepted: 12 January 2018 / Published: 16 January 2018
(This article belongs to the Section Remote Sensing in Agriculture and Vegetation)
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Abstract

In light of climate change and its impacts on plant physiology, optimizing water usage and improving irrigation practices play a crucial role in crop management. In recent years, new optical remote sensing techniques have become widespread since they allow a non-invasive evaluation of plant water stress dynamics in a timely manner. Unmanned aerial vehicles (UAV) currently represent one of the most advanced platforms for remote sensing applications. In this study, remote and proximal sensing measurements were compared with plant physiological variables, with the aim of testing innovative services and support systems to farmers for optimizing irrigation practices and scheduling. The experiment, conducted in two vineyards located in Sardinia, Italy, consisted of two regulated deficit irrigation (RDI) treatments and two reference treatments maintained under stress and well-watered conditions. Indicators of crop water status (Crop Water Stress Index—CWSI—and linear thermal index) were calculated from UAV images and ground infrared thermal images and then related to physiological measurements. The CWSI values for moderate water deficit (RDI-1) were 0.72, 0.28 and 0.43 for ‘Vermentino’, ‘Cabernet’ and ‘Cagnulari’ respectively, while for severe (RDI-2) water deficit the values were 0.90, 0.34 and 0.51. The highest differences for net photosynthetic rate (Pn) and stomatal conductance (Gs) between RDI-1 and RDI-2 were observed in ‘Vermentino’. The highest significant correlations were found between CWSI with Pn (R = −0.80), with ΦPSII (R = −0.49) and with Fv’/Fm’ (R = −0.48) on ‘Cagnulari’, while a unique significant correlation between CWSI and non-photochemical quenching (NPQ) (R = 0.47) was found on ‘Vermentino’. Pn, as well as the efficiency of light use by the photosystem II (PSII), declined under stress conditions and when CWSI values increased. Under the experimental water stress conditions, grapevines were able to recover their efficiency during the night, activating a photosynthetic protection mechanism such as thermal energy dissipation (NPQ) to prevent irreversible damage to the photosystem. The results presented here demonstrate that CWSI values derived from remote and proximal sensors could be valuable indicators for the assessment of the spatial variability of crop water status in Mediterranean vineyards. View Full-Text
Keywords: unmanned aerial vehicle (UAV); grapevine; crop water stress index (CWSI); stem water potential (SWP); photosynthesis; fluorescence unmanned aerial vehicle (UAV); grapevine; crop water stress index (CWSI); stem water potential (SWP); photosynthesis; fluorescence
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Matese, A.; Baraldi, R.; Berton, A.; Cesaraccio, C.; Di Gennaro, S.F.; Duce, P.; Facini, O.; Mameli, M.G.; Piga, A.; Zaldei, A. Estimation of Water Stress in Grapevines Using Proximal and Remote Sensing Methods. Remote Sens. 2018, 10, 114.

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