Using UAV-based Remote Sensing to Assess Grapevine Canopy Damages Due to Fire Smoke.

BACKGROUND Bushfires are becoming an increasing issue for the wine sector due to grape and vine losses and to smoke taint in wine. Smoke affects vine physiology and the smoke volatile phenols are absorbed by plant and berry, contaminating the wine. Our hypothesis has been that, for the first time, UAV (unmanned aerial vehicle)-based visible images can be used to study the physiology of the smoke-affected vines and to assess the compromised vines. RESULTS Procanico vines were exposed to two smoke treatments, a week apart. Gas exchanges and leaf biochemical traits were measured in the short-term (30 min after smoke-exposure) and in the long-term (24 h after smoke-exposure). Canopy damages were assessed by conventional VIs (Vegetation Indices) and by an innovative index derived by UAV-based visible images, the Canopy Area Health Index (CAHI). Gas exchange showed a reduction after the first smoke exposure, but the vines recovered within 24 h. The second smoke exposure led to an irreversible reduction of functional parameters. VIs exhibited significant differences and CAHI presented a damage gradient related to bushfire nearby. CONCLUSION The vineyard damage assessment by UAV-based visible images may represent a tool to study the physiological activity of smoke-affected vines and to quantify the loss of destroyed or damaged vines. This article is protected by copyright. All rights reserved.

[1]  G. Matteucci,et al.  The hidden land conservation benefits of olive‐based (Olea europaea L.) landscapes: An agroforestry investigation in the southern Mediterranean (Calabria region, Italy) , 2020, Land Degradation & Development.

[2]  Claudia Gonzalez Viejo,et al.  Non-Invasive Tools to Detect Smoke Contamination in Grapevine Canopies, Berries and Wine: A Remote Sensing and Machine Learning Modeling Approach , 2019, Sensors.

[3]  L. Salvati,et al.  Assessing Impacts of Climate Change on Phenology and Quality Traits of Vitis vinifera L.: The Contribution of Local Knowledge , 2019, Plants.

[4]  James Taylor,et al.  What relevant information can be identified by experts on unmanned aerial vehicles’ visible images for precision viticulture? , 2019, Precision Agriculture.

[5]  C. Ford,et al.  Accumulation of volatile phenol glycoconjugates in grapes following grapevine exposure to smoke and potential mitigation of smoke taint by foliar application of kaolin , 2019, Planta.

[6]  John Hogland,et al.  Linking Phenological Indices from Digital Cameras in Idaho and Montana to MODIS NDVI , 2018, Remote. Sens..

[7]  G. Matteucci,et al.  Forest certification map of Europe , 2018, iForest - Biogeosciences and Forestry.

[8]  Matthew Noestheden,et al.  Smoke from simulated forest fire alters secondary metabolites in Vitis vinifera L. berries and wine , 2018, Planta.

[9]  S. Michaletz Xylem dysfunction in fires: towards a hydraulic theory of plant responses to multiple disturbance stressors. , 2018, The New phytologist.

[10]  Nicholas C. Coops,et al.  Monitoring pigment‐driven vegetation changes in a low‐Arctic tundra ecosystem using digital cameras , 2018 .

[11]  G. Gilioli,et al.  Climate warming effects on grape and grapevine moth (Lobesia botrana) in the Palearctic region , 2017 .

[12]  Kevin W. Eliceiri,et al.  ImageJ2: ImageJ for the next generation of scientific image data , 2017, BMC Bioinformatics.

[13]  G. Mugnozza,et al.  Social perception of forest multifunctionality in southern Italy: The case of Calabria Region , 2016 .

[14]  B. Lasserre,et al.  First mapping of the main high conservation value forests (HCVFs) at national scale: The case of Italy , 2016 .

[15]  D. L. Johnson,et al.  Review of smoke taint in wine: Smoke-derived volatile phenols and their glycosidic metabolites in grapes and vines as biomarkers for smoke exposure and their role in the sensory perception of smoke taint , 2015 .

[16]  E. Brunori,et al.  The on-farm conservation of grapevine (Vitis vinifera L.) landraces assures the habitat diversity in the viticultural agro-ecosystem , 2015 .

[17]  R. Biasi,et al.  Sustainable use of genetic resources: the characterization of an Italian local grapevine variety (‚Grechetto rosso') and its own landscape , 2015 .

[18]  Simon Bennertz,et al.  Combining UAV-based plant height from crop surface models, visible, and near infrared vegetation indices for biomass monitoring in barley , 2015, Int. J. Appl. Earth Obs. Geoinformation.

[19]  M. Moritz,et al.  Short-term physiological effects of smoke on grapevine leaves , 2013 .

[20]  K. Nicholas,et al.  Vinecology: pairing wine with nature , 2013 .

[21]  P. Marquet,et al.  Climate change, wine, and conservation , 2013, Proceedings of the National Academy of Sciences.

[22]  Helder Fraga,et al.  An overview of climate change impacts on European viticulture , 2012 .

[23]  Gwendal Latouche,et al.  A new optical leaf-clip meter for simultaneous non-destructive assessment of leaf chlorophyll and epidermal flavonoids , 2012, Physiologia plantarum.

[24]  H. Quénol,et al.  Change in climate and berry composition for grapevine varieties cultivated in the Loire Valley , 2012 .

[25]  R. Ristić,et al.  Amelioration of smoke taint in wine by reverse osmosis and solid phase adsorption , 2011 .

[26]  A. Pollnitz,et al.  Effect of smoke application to field‐grown Merlot grapevines at key phenological growth stages on wine sensory and chemical properties , 2011 .

[27]  Z. Nagy,et al.  Heat acclimation of grapevine leaf photosynthesis: mezo- and macroclimatic aspects. , 2009, Functional plant biology : FPB.

[28]  A. Pollnitz,et al.  Smoke-derived taint in wine: the release of smoke-derived volatile phenols during fermentation of Merlot juice following grapevine exposure to smoke. , 2008, Journal of agricultural and food chemistry.

[29]  M. Schaepman,et al.  Angular sensitivity analysis of vegetation indices derived from CHRIS/PROBA data , 2008 .

[30]  N. D. Tillett,et al.  Automated Crop and Weed Monitoring in Widely Spaced Cereals , 2006, Precision Agriculture.

[31]  John R. Miller,et al.  Assessing vineyard condition with hyperspectral indices: Leaf and canopy reflectance simulation in a row-structured discontinuous canopy , 2005 .

[32]  K. Niyogi,et al.  Photo-oxidative Stress in a Xanthophyll-deficient Mutant of Chlamydomonas* , 2004, Journal of Biological Chemistry.

[33]  T. Kataoka,et al.  Crop growth estimation system using machine vision , 2003, Proceedings 2003 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM 2003).

[34]  B. Ripley,et al.  The effect of smoke on the photosynthetic gas exchange of Chrysanthemoides monilifera , 2002 .

[35]  A. Gitelson,et al.  Novel algorithms for remote estimation of vegetation fraction , 2002 .

[36]  D. Lamb,et al.  Optical remote sensing applications in viticulture - a review , 2002 .

[37]  M. Louhaichi,et al.  Spatially Located Platform and Aerial Photography for Documentation of Grazing Impacts on Wheat , 2001 .

[38]  G. Meyer,et al.  Color indices for weed identification under various soil, residue, and lighting conditions , 1994 .

[39]  J. Guehl,et al.  Photosynthesis Decrease and Stomatal Control of Gas Exchange in Abies alba Mill. in Response to Vapor Pressure Difference. , 1987, Plant physiology.

[40]  M. Moresi,et al.  Novel cold sterilization and stabilization process applied to a pale lager , 2015 .

[41]  M. Gupta,et al.  Effects of coal-smoke pollutants from different sources on the growth, chlorophyll content, stem anatomy and cuticular traits of Euphorbia hirta L. , 1987, Environmental pollution.

[42]  W. Kliewer,et al.  Stomatal Response of Three Grapevine Cultivars (Vitis viniferaL.) to High Temperature , 1986, American Journal of Enology and Viticulture.