“Flavescence dorée” (FD) is a grapevine quarantine disease associated with phytoplasmas and transmitted to healthy plants by insect vectors, mainly Scaphoideus titanus. Infected plants usually develop symptoms of stunted growth, unripe cane wood, leaf rolling, leaf yellowing or reddening, and shrivelled berries. Since plants can remain symptomless up to four years, they may act as reservoirs of FD contributing to the spread of the disease. So far, conventional management strategies rely mainly on the insecticide treatments, uprooting of infected plants and use of phytoplasma-free propagation material. However, these strategies are costly and could have undesirable environmental impacts. Thus, the development of sustainable and noninvasive approaches for early detection of FD and its management are of great importance to reduce disease spread and select the best cultural practices and treatments. The present study aimed to evaluate if multispectral/hyperspectral technologies can be used to detect FD before the appearance of the first symptoms and if infected grapevines display a spectral imaging fingerprint. To that end, physiological parameters (leaf area, chlorophyll content and photosynthetic rate) were collected in concomitance to the measurements of plant reflectance (using both a portable apparatus and a remote sensing drone). Measurements were performed in two leaves of 8 healthy and 8 FD-infected grapevines, at four timepoints: before the development of disease symptoms (21st June); and after symptoms appearance (ii) at veraison (2nd August); at post-veraison (11th September); and at harvest (25th September). At all timepoints, FD infected plants revealed a significant decrease in the studied physiological parameters, with a positive correlation with drone imaging data and portable apparatus analyses. Moreover, spectra of either drone imaging and portable apparatus showed clear differences between healthy and FD-infected grapevines, validating multispectral/ hyperspectral technology as a potential tool for the early detection of FD or other grapevine-associated diseases.
Authors: Manuel J.R.A. Oliveira1,2,3, Marta W. Vasconcelos1, Ana Monforte1, Óscar Moutinho4, Ricardo Mendes4, António Ferreira1, Assunta Bertaccini5 and Susana M.P. Carvalho2
1Universidade Católica Portuguesa, CBQF – Centro de Biotecnologia e Química Fina –Laboratório Associado, Escola Superior de Biotecnologia, Porto, Portugal
2GreenUPorto – Sustainable Agrifood Production Research Centre / Inov4Agro, DGAOT, Faculty of Sciences of University of Porto, Vairão, Portugal
3CoLAB Vines&Wines – National Collaborative Laboratory for the Portuguese Wine Sector, Associação para o Desenvolvimento da Viticultura Duriense (ADVID), Edifício Centro de Excelência da Vinha e do Vinho, Vila Real, Portugal
4Eye2Map – Soluções Geográficas para Ambiente e Engenharia, UPTEC Polo do Mar, Leça da Palmeira, Portugal
5Dipartimento di Scienze e Tecnologie Agro-Alimentari (DISTAL), Alma Mater Studiorum, University of Bologna, Bologna, Italy
Keywords: grapevine, photosynthetic rate, red edge, remote sensing, sustainable viticulture