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Volume 16
Issue 13
10.3390/su16135748
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Article

Precision Farming Multimodal Technologies Using Optical Sensors for the Detection of Citrus Tristeza Virus Endemics

by
Athanasios V. Argyriou
1,2,
Nikolaos Tektonidis
1,
Evangelos Alevizos
3,
Konstantinos P. Ferentinos
4,
Nektarios N. Kourgialas
5,* and
Matthaios M. Mathioudakis
1,*
1
Plant Pathology Laboratory, Institute of Olive Tree, Subtropical Crops and Viticulture, ELGO-DIMITRA, Karamanlis Ave. 167, 73134 Chania, Greece
2
Laboratory of Geophysical-Satellite Remote Sensing and Archaeoenvironment, Institute for Mediterranean Studies, Foundation for Research and Technology-Hellas (FORTH), 74100 Rethymno, Greece
3
Institute des Substances et Organismes de la Mer (ISOMer), Nantes Universite, UR 2160, F-44000 Nantes, France
4
Department of Agricultural Engineering, Soil & Water Resources Institute, ELGO-DIMITRA, 61 Dimokratias Av., 13561 Athens, Greece
5
Water Recourses-Irrigation & Environmental Geoinformatics Laboratory, Institute of Olive Tree, Subtropical Crops and Viticulture, ELGO-DIMITRA, Karamanlis Ave. 167, 73134 Chania, Greece
*
Authors to whom correspondence should be addressed.
Sustainability 2024, 16(13), 5748; https://doi.org/10.3390/su16135748
Submission received: 17 April 2024 / Revised: 29 May 2024 / Accepted: 3 July 2024 / Published: 5 July 2024
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Abstract

Citrus trees and their fruits have significant nutritional value and contain antioxidants that are important components of the Mediterranean diet. However, pathogenic diseases pose a threat to citriculture by reducing crop yield and quality. Therefore, there is a need for novel technologies to maintain healthy citrus crops and enable early and accurate detection of the related pathogens, such as the citrus tristeza virus (CTV). Remote sensing offers a non-destructive, cost effective and efficient method for assessing plant health dynamics. It can provide insights into chlorophyll content, water stress and disease presence. This study provides new insights by integrating a combination of remote sensing approaches (FCCs, NDVI, PCA), optical and proximal techniques with in situ field data collection as well as various serological/molecular technologies to detect CTV effectively and evaluate its temporal epidemiology pattern. In addition, the integration of the adopted techniques in case studies of known fields being infected by CTV provides the basis for remote sensing procedures, such as random forest machine learning algorithm, to become powerful in verifying and identifying new CTV-infected fields in a broader extent coverage area, reaching 89.7% accuracy assessment. Thus, it offers decision-makers a robust approach that contributes to CTV epidemiology monitoring and can aid in the development of effective and sustainable disease management strategies.
Keywords: vegetation stress; plant virus detection; remote sensing; sustainable agriculture vegetation stress; plant virus detection; remote sensing; sustainable agriculture

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MDPI and ACS Style

Argyriou, A.V.; Tektonidis, N.; Alevizos, E.; Ferentinos, K.P.; Kourgialas, N.N.; Mathioudakis, M.M. Precision Farming Multimodal Technologies Using Optical Sensors for the Detection of Citrus Tristeza Virus Endemics. Sustainability 2024, 16, 5748. https://doi.org/10.3390/su16135748

AMA Style

Argyriou AV, Tektonidis N, Alevizos E, Ferentinos KP, Kourgialas NN, Mathioudakis MM. Precision Farming Multimodal Technologies Using Optical Sensors for the Detection of Citrus Tristeza Virus Endemics. Sustainability. 2024; 16(13):5748. https://doi.org/10.3390/su16135748

Chicago/Turabian Style

Argyriou, Athanasios V., Nikolaos Tektonidis, Evangelos Alevizos, Konstantinos P. Ferentinos, Nektarios N. Kourgialas, and Matthaios M. Mathioudakis. 2024. "Precision Farming Multimodal Technologies Using Optical Sensors for the Detection of Citrus Tristeza Virus Endemics" Sustainability 16, no. 13: 5748. https://doi.org/10.3390/su16135748

APA Style

Argyriou, A. V., Tektonidis, N., Alevizos, E., Ferentinos, K. P., Kourgialas, N. N., & Mathioudakis, M. M. (2024). Precision Farming Multimodal Technologies Using Optical Sensors for the Detection of Citrus Tristeza Virus Endemics. Sustainability, 16(13), 5748. https://doi.org/10.3390/su16135748

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