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BY 4.0 license Open Access Published by De Gruyter Open Access July 19, 2019

Spectral and thermal data as a proxy for leaf protective energy dissipation under kaolin application in grapevine cultivars

  • Renan Tosin , Isabel Pôças and Mário Cunha EMAIL logo
From the journal Open Agriculture

Abstract

The dynamic effects of kaolin clay particle film application on the temperature and spectral reflectance of leaves of two autochthonous cultivars (Touriga Nacional (TN, n=32) and Touriga Franca (TF, n=24)) were studied in the Douro wine region. The study was implemented in 2017, in conditions prone to multiple environmental stresses that include excessive light and temperature as well as water shortage. Light reflectance from kaolin-sprayed leaves was higher than the control (leaves without kaolin) on all dates. Kaolin’s protective effect over leaves’ temperatures was low on the 20 days after application and ceased about 60 days after its application. Differences between leaves with and without kaolin were explained by the normalized maximum leaf temperature (T_max_f_N), reflectance at 400 nm, 532 nm, and 737 nm, as assessed through TN data. The wavelengths of 532 nm and 737 nm are associated with plant physiological processes, which support the selection of these variables for assessing kaolin’s effects on leaves. The application of principal component analysis to the TF data, based on these four variables (T_max_f_N and reflectances: 400, 532, 737 nm) selected for TN, explained 83.56% of data variability (considering two principal components), obtaining a clear differentiation between leaves with and without kaolin. The T_max_f_N and the reflectance at 532 nm were the variables with a greater contribution for explaining data variability. The results improve the understanding of the vines’ response to kaolin throughout the grapevine cycle and support decisions about the re-application timing.

References

AbdAllah A., Impacts of Kaolin and Pinoline foliar application on growth, yield and water use efficiency of tomato ( Solanum lycopersicum L .) grown under water deficit: A comparative study, Journal of the Saudi Society of Agricultural Sciences, 2017, DOI: 10.1016/j.jssas.2017.08.00110.1016/j.jssas.2017.08.001Search in Google Scholar

AbdAllah A.M., Burkey K.O.,Mashaheet A.M., Reduction of plant water consumption through anti-transpirants foliar application in tomato plants ( Solanum lycopersicum L ), Scientia Horticulturae, 2018, 235373-81, DOI: 10.1016/j.scienta.2018.03.00510.1016/j.scienta.2018.03.005Search in Google Scholar

Behmann J., Steinrücken J.,Plümer L., Detection of early plant stress responses in hyperspectral images, ISPRS Journal of Photogrammetry and Remote Sensing, 2014, 9398-11110.1016/j.isprsjprs.2014.03.016Search in Google Scholar

Brillante L., Belfiore N., Gaiotti F., et al., Comparing Kaolin and Pinolene to Improve Sustainable Grapevine Production during Drought, PLoS One, 2016, 11(6), e0156631, DOI: 10.1371/journal.pone.0156631Search in Google Scholar PubMed

Cantore V., Pace B.,Albrizio R., Kaolin-based particle film technology affects tomato physiology, yield and quality, Environmental and Experimental Botany, 2009, 66(2), 279-88, DOI: 10.1016/j.envexpbot.2009.03.00810.1016/j.envexpbot.2009.03.008Search in Google Scholar

Chaves M.,Rodrigues L., In: Tenhunen JDea (Eds), Plant Response to Stress-functional analises in Mediterranean Ecosystems, Springer Verlag, Berlin, 1987, 279-90Search in Google Scholar

Cunha M.,Richter C., The impact of climate change on the winegrape vineyards of the Portuguese Douro region, Climatic Change, 2016, 138(1), 239-51, DOI: 10.1007/s10584-016-1719-910.1007/s10584-016-1719-9Search in Google Scholar

Dinis L.T., Bernardo S., Conde A., et al., Kaolin exogenous application boosts antioxidant capacity and phenolic content in berries and leaves of grapevine under summer stress, J Plant Physiol, 2016, 19145-53, DOI: 10.1016/j.jplph.2015.12.00510.1016/j.jplph.2015.12.005Search in Google Scholar PubMed

Djurović N., Ćosić M., Stričević R., Savić S.,Domazet M., Effect of irrigation regime and application of kaolin on yield, quality and water use efficiency of tomato, Scientia Horticulturae, 2016, 201271-78, DOI: 10.1016/j.scienta.2016.02.01710.1016/j.scienta.2016.02.017Search in Google Scholar

Falcioni R., Moriwaki T., Bonato C.M., et al., Distinct growth light and gibberellin regimes alter leaf anatomy and reveal their influence on leaf optical properties, Environmental and Experimental Botany, 2017, 14086-95, DOI: 10.1016/j.envexpbot.2017.06.00110.1016/j.envexpbot.2017.06.001Search in Google Scholar

Feng S., Itoh Y., Parente M.,Duarte M.F., Hyperspectral Band Selection From Statistical Wavelet Models, IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(4), 2111-23, DOI: 10.1109/tgrs.2016.263685010.1109/tgrs.2016.2636850Search in Google Scholar

Féret J.B., Gitelson A.A., Noble S.D.,Jacquemoud S., PROSPECT-D: Towards modeling leaf optical properties through a complete lifecycle, Remote Sensing of Environment, 2017, 193204-15, DOI: 10.1016/j.rse.2017.03.00410.1016/j.rse.2017.03.004Search in Google Scholar

Ferrari V., Disegna E., Dellacassa E.,Coniberti A., Influence of timing and intensity of fruit zone leaf removal and kaolin applications on bunch rot control and quality improvement of Sauvignon blanc grapes, and wines, in a temperate humid climate, Scientia Horticulturae, 2017, 22362-71, DOI: 10.1016/j.scienta.2017.05.03410.1016/j.scienta.2017.05.034Search in Google Scholar

Ferreira H.A., Normais climatológicas do continente, Açores e Madeira correspondentes a 1931-1960, Serviço Meteorológico Nacional, Lisboa, 1965.Search in Google Scholar

Filella I.,Penuelas J., The red edge position and shape as indicators of plant chlorophyll content, biomass and hydric status, International Journal of Remote Sensing, 1994, 15(7), 1459-70, DOI: 10.1080/0143116940895417710.1080/01431169408954177Search in Google Scholar

Fox J.,Weisberg S., An (R) Companion to Applied Regression, 2011, Thousand Oaks (CA), URL: http://socserv.socsci.mcmaster.ca/jfox/Books/CompanionSearch in Google Scholar

Gamon J.A., Serrano L.,Surfus J.S., The photochemical reflectance index: an optical indicator of photosynthetic radiation use efficiency across species, functional types, and nutrient levels, Oecologia, 1997, 112(4), 492-501, DOI: 10.1007/s00442005033710.1007/s004420050337Search in Google Scholar PubMed

Gharaghani A., Mohammadi Javarzari A.,Vahdati K., Kaolin particle film alleviates adverse effects of light and heat stresses and improves nut and kernel quality in Persian walnut, Scientia Horticulturae, 2018, 23935-40, DOI: 10.1016/j.scienta.2018.05.02410.1016/j.scienta.2018.05.024Search in Google Scholar

Giorgi F.,Lionello P., Climate change projections for the Mediterranean region, Global and Planetary Change, 2008, 63(2-3), 90-104, DOI: 10.1016/j.gloplacha.2007.09.00510.1016/j.gloplacha.2007.09.005Search in Google Scholar

Gitelson A.A., Gritz Y.,Merzlyak M.N., Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves, J Plant Physiol, 2003, 160(3), 271-82, DOI: 10.1078/0176-1617-0088710.1078/0176-1617-00887Search in Google Scholar PubMed

Glenn D.M., Cooley N., Walker R., Clingeleffer P.,Shellie K., Impact of kaolin particle film and water deficit on wine grape water use efficiency and plant water relations, HortScience, 2010, 45(8), 1178-8710.21273/HORTSCI.45.8.1178Search in Google Scholar

Glenn D.M., Prado E., Erez A., McFerson J.,Puterka G.J., A reflective, processed-kaolin particle film affects fruit temperature, radiation reflection, and solar injury in apple, Journal of the American Society for Horticultural Science, 2002, 127(2), 188-9310.21273/JASHS.127.2.188Search in Google Scholar

Glenn D.M.,Puterka G.J., In: Janick J (Eds), Horticultural Reviews, John Wiley&Sons, Inc., 2005, 1-44Search in Google Scholar

Hall A., Lamb D.W., Holzapfel B., Louis J., Optical remote sensing applications in viticulture - a review, Australian Journal of Grape and Wine Research, 2002, 8(1), 36-47, DOI: 10.1111/j.1755-0238.2002.tb00209.x10.1111/j.1755-0238.2002.tb00209.xSearch in Google Scholar

Huang R.,He M., Band Selection Based on Feature Weighting for Classification of Hyperspectral Data, IEEE Geoscience and Remote Sensing Letters, 2005, 2(2), 156-59, DOI: 10.1109/lgrs.2005.84465810.1109/lgrs.2005.844658Search in Google Scholar

IPCC, Fourth Assessment Report of the Intergovernmental Panel on Climate Change Cambridge University Press2007.Search in Google Scholar

Jifon J.L.,Syvertsen J.P., Kaolin Particle Film Applications Can Increase Photosynthesis and Water Use Efficiency of `Ruby Red’ Grapefruit Leaves, Journal of the American Society for Horticultural Science, 2003, 128(1), 107-1210.21273/JASHS.128.1.0107Search in Google Scholar

Jones H.G.,Vaughan R.A., Remote sensing of vegetation: principles, techniques, and applications, Oxford University Press Inc., New York, USA, 2010.Search in Google Scholar

Kassambara A.,Mundt F., factoextra: Extract and Visualize the Results of Multivariate Data Analyses, 2017, https://CRAN.R-project.org/package=factoextraSearch in Google Scholar

Kuhn M.,Johnson K., Applied predictive modeling, Springer Science+Business Media, New York, 2013.10.1007/978-1-4614-6849-3Search in Google Scholar

Mendiburu F.d., agricolae: Statistical Procedures for Agricultural Research, 2017, https://CRAN.R-project.org/package=agricolaeSearch in Google Scholar

Middleton E.M., Huemmrich K.F., Cheng Y.-B.,Margolis H.A., In: Thenkabail P, Lyon J,Huete A (Eds), Hyperspectral Remote Sensing of Vegetation, Taylor&Francis Group, LLC, Boca Raton, 2012, 265-88Search in Google Scholar

Moriondo M., Ferrise R., Trombi G., et al., Modelling olive trees and grapevines in a changing climate, Environmental Modelling&Software, 2015, 72387-401, DOI: 10.1016/j.envsoft.2014.12.01610.1016/j.envsoft.2014.12.016Search in Google Scholar

Moutinho-Pereira J., Magalhães N., Gonçalves B., et al., Gas exchange and water relations of three Vitis vinifera L. cultivars growing under Mediterranean climate, Photosynthetica, 2007, 45(2), 202-07, DOI: 10.1007/s11099-007-0033-110.1007/s11099-007-0033-1Search in Google Scholar

Moya I., Camenen L., Evain S., et al., A new instrument for passive remote sensing: 1. Measurements of sunlight-induced chlorophyll fluorescence, Remote Sensing of Environment, 2004, 91(2), 186-9710.1016/j.rse.2004.02.012Search in Google Scholar

Müller P., Li X.-P.,Niyogi K.K., Non-photochemical quenching. A response to excess light energy, Plant physiology, 2001, 125(4), 1558-6610.1104/pp.125.4.1558Search in Google Scholar PubMed PubMed Central

Ou C., Du X., Shellie K., Ross C.,Qian M.C., Volatile compounds and sensory attributes of wine from Cv. Merlot (Vitis vinifera L.) grown under differential levels of water deficit with or without a kaolin-based, foliar reflectant particle film, J Agric Food Chem, 2010, 58(24), 12890-8, DOI: 10.1021/jf102587x10.1021/jf102587xSearch in Google Scholar PubMed

Palliotti A., Tombesi S., Frioni T., et al., Physiological parameters and protective energy dissipation mechanisms expressed in the leaves of two Vitis vinifera L. genotypes under multiple summer stresses, J Plant Physiol, 2015, 18584-92, DOI: 10.1016/j.jplph.2015.07.00710.1016/j.jplph.2015.07.007Search in Google Scholar PubMed

R Core Team, R: A Language and Environment for Statistical Computing, 2017, Vienna, Austria, URL: https://www.R-project.org/Search in Google Scholar

Reis R.,Lamelas H., Statistical study of decade series of water balance and its components of potencial evapotranspiration calculated by Penman’s method, Instituto Nacional de Meteorologia e Geofisica, Lisbon, 1988Search in Google Scholar

Russo V.,Diaz-Perez J., Kaolin-based particle film has no effect on physiological measurements, disease incidence or yield in peppers, HortScience, 2005, 40(1), 98-10110.21273/HORTSCI.40.1.98Search in Google Scholar

Sepulcre-Cantó G., Zarco-Tejada P., Jiménez-Muñoz J., et al., Detection of water stress in an olive orchard with thermal remote sensing imagery, Agricultural and Forest Meteorology, 2006, 136(1), 31-4410.1016/j.agrformet.2006.01.008Search in Google Scholar

Shellie K.,Glenn D.M., Wine Grape Response to Foliar Particle Film under Differing Levels of Preveraison Water Stress, HORTSCIENCE, 2008, 43(5), 1392–9710.21273/HORTSCI.43.5.1392Search in Google Scholar

Shellie K.C.,King B.A., Kaolin Particle Film and Water Deficit Influence Malbec Leaf and Berry Temperature, Pigments, and Photosynthesis, American Journal of Enology and Viticulture, 2013, 64(2), 223-30, DOI: 10.5344/ajev.2012.1211510.5344/ajev.2012.12115Search in Google Scholar

Ustin S.L., Gitelson A.A., Jacquemoud S., et al., Retrieval of foliar information about plant pigment systems from high resolution spectroscopy, Remote Sensing of Environment, 2009, 113S67-S77, DOI: https://doi.org/10.1016/j.rse.2008.10.01910.1016/j.rse.2008.10.019Search in Google Scholar

Wang M., Wan Y., Ye Z., Gao X.,Lai X., A band selection method for airborne hyperspectral image based on chaotic binary coded gravitational search algorithm, Neurocomputing, 2017, DOI: 10.1016/j.neucom.2017.07.05910.1016/j.neucom.2017.07.059Search in Google Scholar

Zarco-Tejada P.J., González-Dugo V., Williams L.E., et al., A PRI-based water stress index combining structural and chlorophyll effects: Assessment using diurnal narrow-band airborne imagery and the CWSI thermal index, Remote Sensing of Environment, 2013, 13838-50, DOI: 10.1016/j.rse.2013.07.02410.1016/j.rse.2013.07.024Search in Google Scholar

Received: 2018-10-01
Accepted: 2019-03-20
Published Online: 2019-07-19

© 2019 Renan Tosin et al., published De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 Public License.

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