A geostatistical fusion approach using UAV data for probabilistic estimation of Xylella fastidiosa subsp. pauca infection in olive trees

Castrignanò, Annamaria; Belmonte, Antonella; Antelmi, I.; Quarto, R.; Quarto, Francesco; Shaddad, Sameh M.; Sion, Valentina; Muolo, Maria Rita; Ranieri, N.; Gadaleta, Giovanni; Bartoccetti, Edoardo; Riefolo, Carmela; Ruggieri, Sergio; Nigro, Franco

doi:10.1016/j.scitotenv.2020.141814

Cited by 23 publications

(15 citation statements)

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“…Each polygon was first discretized in regular cells for the calculation of the areal (polygon) co-variance function, which was expressed as a weighted discrete summation of the point (pixel) covariance functions calculated at the centroid point of each cell. In this procedure, the weights correspond to the proportion of cell falling inside the polygon [38].…”

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“…After that, the calculation proceeded according to the standard formulation of the block cokriging, as exhaustively described in several geostatistical manuals [36][37][38]. Here, it is only intended to underline that the spatial correlation structure of the multitemporal and multi-band UAV data for each field has been analyzed by adopting a linear model of co-regionalization (LMC) to the reflectivity data of the four bands recorded on the four, flight dates for a total of 16 variables.…”

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Semi-Automatic Method for Early Detection of Xylella fastidiosa in Olive Trees Using UAV Multispectral Imagery and Geostatistical-Discriminant Analysis

et al. 2020

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Xylella fastidiosa subsp. pauca (Xfp) is one of the most dangerous plant pathogens in the world. Identified in 2013 in olive trees in south–eastern Italy, it is spreading to the Mediterranean countries. The bacterium is transmitted by insects that feed on sap, and causes rapid wilting in olive trees. The paper explores the use of Unmanned Aerial Vehicle (UAV) in combination with a multispectral radiometer for early detection of infection. The study was carried out in three olive groves in the Apulia region (Italy) and involved four drone flights from 2017 to 2019. To classify Xfp severity level in olive trees at an early stage, a combined method of geostatistics and discriminant analysis was implemented. The results of cross-validation for the non-parametric classification method were of overall accuracy = 0.69, mean error rate = 0.31, and for the early detection class of accuracy 0.77 and misclassification probability 0.23. The results are promising and encourage the application of UAV technology for the early detection of Xfp infection.

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Semi-Automatic Method for Early Detection of Xylella fastidiosa in Olive Trees Using UAV Multispectral Imagery and Geostatistical-Discriminant Analysis

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“…Clustering, as a multi-spatial methodological approach [32,33], elicit the effect of vegetation traits and landscape structure on animal diversity and allows for a better understanding of an ongoing alien-biota invasion like Xf, as well as for its effective monitoring and surveillance management costs. Based on this visual evidence [34][35][36], our assessment of the combination of six indicators provides a useful tool for local authorities by clustering the study area into six zones. Across these zones, our analysis identifies a total of close to 29 thousand polygons (Table 3) that are attributable to olive groves in the study area with a total area and total average of 235,940 and 8.14 Ha, respectively.…”

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Landscape and Vegetation Patterns Zoning Is a Methodological Tool for Management Costs Implications Due to Xylella fastidiosa Invasion

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Frem

Fucilli

et al. 2022

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Philaenus spumarius (Linnaeus 1758, hereafter Ps) is considered one of the main insect vectors responsible for the spread of an alien biota, Xylella fastidiosa (Wells 1987, hereafter Xf), in the Salento area, Apulia region (Southern Italy). Effective management of this biological invader depends on the continuous surveillance and monitoring of its insect vector. As such, this research elicits the invasion drivers (i.e., landscape and vegetation indicators) that influence the abundance and the dynamics of this vector and, consequently, the spatial spread of this bacterium in this Italian region. For this purpose, a spatial pattern clustering methodological approach is considered. The results reveal that spatial variation and territorial differentiation may differ from zone to zone in the same invaded area, for which effective management and monitoring planning should be addressed. Further, six agro-ecosystems zones have been identified with respect to five indicators: (i) vegetation index, (ii) intensity of cultivation, (iii) cultural diversity, (iv) density of agricultural landscape elements, and (v) altitude. This paper has public implications and contributes to an understanding of how zoning of an infected area, by an alien biota, into homogenous zones may impact its effective management costs. This approach could also be applied in other countries affected or potentially affected by the phenomenon of Xf invasion.

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“…Therefore, there is a continual risk of spreading Xylella fastidiosa across the world, which has led to recent serious outbreaks. Consequently, countries classified in the high-risk zone should constantly perform specialized pest risk analysis (PRA), implement preventive phytosanitary measures, and focus on enhancing inspection systems, while raising awareness about Xylella fastidiosa in order to reduce its economic and ecological impacts (Castrignanò et al 2020;Frem et al 2020) and ensure its early detection in asymptomatic plants and vectors (Riefolo et al 2021).…”

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The potential direct economic impact and private management costs of an invasive alien species: Xylella fastidiosa on Lebanese wine grapes

Frem¹,

Fucilli²,

Nigro³

et al. 2021

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Since its outbreak in 2013 in Italy, the harmful bacterium Xylella fastidiosa has continued to spread throughout the Euro-Mediterranean basin and, more recently, in the Middle East region. Xylella fastidiosa subsp. fastidiosa is the causal agent of Pierce’s disease on grapevines. At present, this alien subspecies has not been reported in Lebanon but if this biological invader was to spread with no cost-effective and sustainable management, it would put Lebanese vineyards at a certain level of risk. In the absence of an Xylella fastidiosa subsp. fastidiosa outbreak, the gross revenue generated by Lebanese wine growers is estimated as close to US$22 million/year for an average period of 5 years (2015–2019). The potential quantitative economic impacts of an Xylella fastidiosa subsp. fastidiosa outbreak and particularly, the private control costs have not been assessed yet for this country as well as for others which Xylella fastidiosa may invade. Here, we have aimed to estimate the potential direct economic impact on growers’ livelihoods and provide the first estimate of the private management costs that a theoretical Xylella fastidiosa subsp. fastidiosa outbreak in Lebanon would involve. For this purpose, we used a Partial Budget approach at the farm gate. For the country as a whole, we estimated that a hypothetical full spread of Xylella fastidiosa subsp. fastidiosa on Lebanese wine grapes would lead to maximum potential gross revenue losses of almost US$ 11 million for an average recovery period of 4 years, to around US$ 82.44 million for an average grapevine life span period of 30 years in which infected plants are not replaced at all. The first yearly estimated additional management cost is US$853 per potentially infected hectare. For a recovery period of 4 years, the aggregate estimated additional cost would reach US$2374/ha, while the aggregate net change in profit would be US$-4046/ha. Furthermore, additional work will be needed to estimate the public costs of an Xylella fastidiosa subsp. fastidiosa outbreak in Lebanon. The observed costs in this study support the concerned policy makers and stakeholders to implement a set of reduction management options against Xylella fastidiosa subsp. fastidiosa at both national and wine growers’ levels. This re-emerging alien biota should not be neglected in this country. This understanding of the potential direct economic impact of Xylella fastidiosa subsp. fastidiosa and the private management costs can also benefit further larger-scale studies covering other potential infection areas and plant hosts.

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A geostatistical fusion approach using UAV data for probabilistic estimation of Xylella fastidiosa subsp. pauca infection in olive trees

Cited by 23 publications

References 49 publications

Semi-Automatic Method for Early Detection of Xylella fastidiosa in Olive Trees Using UAV Multispectral Imagery and Geostatistical-Discriminant Analysis

Semi-Automatic Method for Early Detection of Xylella fastidiosa in Olive Trees Using UAV Multispectral Imagery and Geostatistical-Discriminant Analysis

Landscape and Vegetation Patterns Zoning Is a Methodological Tool for Management Costs Implications Due to Xylella fastidiosa Invasion

The potential direct economic impact and private management costs of an invasive alien species: Xylella fastidiosa on Lebanese wine grapes

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A geostatistical fusion approach using UAV data for probabilistic estimation of Xylella fastidiosa subsp. pauca infection in olive trees

Cited by 23 publications

References 49 publications

Semi-Automatic Method for Early Detection of Xylella fastidiosa in Olive Trees Using UAV Multispectral Imagery and Geostatistical-Discriminant Analysis

Semi-Automatic Method for Early Detection of Xylella fastidiosa in Olive Trees Using UAV Multispectral Imagery and Geostatistical-Discriminant Analysis

Landscape and Vegetation Patterns Zoning Is a Methodological Tool for Management Costs Implications Due to Xylella fastidiosa Invasion

﻿The potential direct economic impact and private management costs of an invasive alien species: Xylella fastidiosa on Lebanese wine grapes

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The potential direct economic impact and private management costs of an invasive alien species: Xylella fastidiosa on Lebanese wine grapes