AUTHOR=Briglia Nunzio , Williams Kevin , Wu Dan , Li Yaochen , Tao Sha , Corke Fiona , Montanaro Giuseppe , Petrozza Angelo , Amato Davide , Cellini Francesco , Doonan John H. , Yang Wanneng , Nuzzo Vitale 

TITLE=Image-Based Assessment of Drought Response in Grapevines

JOURNAL=Frontiers in Plant Science

VOLUME=11

YEAR=2020

URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2020.00595

DOI=10.3389/fpls.2020.00595

ISSN=1664-462X

ABSTRACT=<p>Many plants can modify their leaf profile rapidly in response to environmental stress. Image-based data are increasingly used to retrieve reliable information on plant water status in a non-contact manner that has the potential to be scaled to high-throughput and repeated through time. This paper examined the variation of leaf angle as measured by both 3D images and goniometer in progressively drought stressed grapevine. Grapevines, grown in pots, were subjected to a 21-day period of drought stress receiving 100% (CTRL), 60% (<italic>IRR</italic><sub>60%</sub>) and 30% (<italic>IRR</italic><sub>30%</sub>) of maximum soil available water capacity. Leaf angle was (i) measured manually (goniometer) and (ii) computed by a 3D reconstruction method (multi-view stereo and structure from motion). Stomatal conductance, leaf water potential, fluorescence (<italic>F</italic><sub><italic>v</italic></sub>/<italic>F</italic><sub><italic>m</italic></sub>), leaf area and 2D RGB data were simultaneously collected during drought imposition. Throughout the experiment, values of leaf water potential ranged from −0.4 (CTRL) to −1.1 MPa (<italic>IRR</italic><sub>30%</sub>) and it linearly influenced the leaf angle when measured manually (<italic>R</italic><sup>2</sup> = 0.86) and with 3D image (<italic>R</italic><sup>2</sup> = 0.73). Drought was negatively related to stomatal conductance and leaf area growth particularly in <italic>IRR</italic><sub>30%</sub> while photosynthetic parameters (i.e., <italic>F</italic><sub><italic>v</italic></sub>/<italic>F</italic><sub><italic>m</italic></sub>) were not impaired by water restriction. A model for leaf area estimation based on the number of pixels of 2D RGB images developed at a different phenotyping robotized platform in a closely related experiment was successfully employed (<italic>R</italic><sup>2</sup> = 0.78). At the end of the experiment, top view 2D RGB images showed a ∼50% reduction of greener fraction (GGF) in CTRL and <italic>IRR</italic><sub>60%</sub> vines compared to initial values, while GGF in <italic>IRR</italic><sub>30%</sub> increased by approximately 20%.</p>