Centre de documentation
scientifique

Is Xylella fastidiosa a serious threat to European forests? / Marie-Laure Desprez-Loustau in Forestry, an international journal of forest research, vol 94 n° 1 (January 2021)  

Public [article]  inForestry, an international journal of forest research > vol 94 n° 1 (January 2021) . - pp 1 - 17 Titre : Is Xylella fastidiosa a serious threat to European forests? Type de document : Article/Communication Auteurs : Marie-Laure Desprez-Loustau, Auteur ; Yialmaz Balci, Auteur ; Daniele Cornara, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1 - 17 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Acer pseudoplatanus [Termes IGN] Amérique du nord [Termes IGN] dépérissement [Termes IGN] écosystème forestier [Termes IGN] Europe (géographie politique) [Termes IGN] Italie [Termes IGN] maladie bactérienne [Termes IGN] Olea europaea [Termes IGN] Quercus (genre) [Termes IGN] Ulmus (genre) [Termes IGN] viticulture [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) The recent emergence of Olive Quick Decline Syndrome in Italy, caused by Xylella fastidiosa, has drawn attention to the risks posed by this vector-borne bacterium to important crops in Europe (especially fruit trees and grapevine). Comparatively very little is known on actual and potential impacts of this pathogen in forests, in the native (North American) and introduced (European) regions, respectively. The present review aims to address important questions related to the threat posed by X. fastidiosa to European forests, such as the following: What are the symptoms, hosts and impact of bacterial leaf scorch caused by X. fastidiosa on trees in North America? Which forest tree species have been found infected in the introduction area in Europe? How does X. fastidiosa cause disease in susceptible hosts? Are there any X. fastidiosa genotypes (subspecies and sequence types) specifically associated with forest trees? How is X. fastidiosa transmitted? What are the known and potential vectors for forest trees? How does vector ecology affect disease? Is the distribution of X. fastidiosa, especially the strains associated with trees, restricted by climatic factors? Is disease risk for trees different in forest ecosystems as compared with urban settings? We conclude by pointing to important knowledge gaps related to all these questions and strongly advocate for more research about the Xylella-forest pathosystems, in both North America and Europe. Numéro de notice : A2021-072 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/forestry/cpaa029 Date de publication en ligne : 06/08/2020 En ligne : https://doi.org/10.1093/forestry/cpaa029 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96805 [article]

Detection of Xylella fastidiosa infection symptoms with airborne multispectral and thermal imagery: Assessing bandset reduction performance from hyperspectral analysis / T. Poblete in ISPRS Journal of photogrammetry and remote sensing, vol 162 (April 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 162 (April 2020) . - pp 27 - 40 Titre : Detection of Xylella fastidiosa infection symptoms with airborne multispectral and thermal imagery: Assessing bandset reduction performance from hyperspectral analysis Type de document : Article/Communication Auteurs : T. Poblete, Auteur ; C. Camino, Auteur ; P.S.A. Beck, Auteur Année de publication : 2020 Article en page(s) : pp 27 - 40 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] chlorophylle [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] espèce végétale [Termes IGN] fluorescence [Termes IGN] image hyperspectrale [Termes IGN] image multibande [Termes IGN] image satellite [Termes IGN] image thermique [Termes IGN] Italie [Termes IGN] maladie bactérienne [Termes IGN] maladie phytosanitaire [Termes IGN] Olea europaea [Termes IGN] stress hydrique [Termes IGN] surveillance de la végétation [Termes IGN] télédétection aérienne [Termes IGN] traitement d'image Résumé : (auteur) Xylella fastidiosa (Xf) is a harmful plant pathogenic bacterium, able to infect over 500 plant species worldwide. Successful eradication and containment strategies for harmful pathogens require large-scale monitoring techniques for the detection of infected hosts, even when they do not display visual symptoms. Although a previous study using airborne hyperspectral and thermal imagery has shown promising results for the early detection of Xf-infected olive (Olea europaea) trees, further work is needed when adopting these techniques for large scale monitoring using multispectral cameras on board airborne platforms and satellites. We used hyperspectral and thermal imagery collected during a two-year airborne campaign in a Xf-infected area in southern Italy to assess the performance of spectrally constrained machine-learning algorithms for this task. The algorithms were used to assess multispectral bandsets, selected from the original hyperspectral imagery, that were compatible with large-scale monitoring from unmanned platforms and manned aircraft. In addition, the contribution of solar–induced chlorophyll fluorescence (SIF) and the temperature-based Crop Water Stress Index (CWSI) retrieved from hyperspectral and thermal imaging, respectively, were evaluated to quantify their relative importance in the algorithms used to detect Xf infection. The detection performance using support vector machine algorithms decreased from ∼80% (kappa, κ = 0.42) when using the original full hyperspectral dataset including SIF and CWSI to ∼74% (κ = 0.36) when the optimal set of six spectral bands most sensitive to Xf infection were used in addition to the CWSI thermal indicator. When neither SIF nor CWSI were used, the detection yielded less than 70% accuracy (decreasing κ to very low performance, 0.29), revealing that tree temperature was more important than chlorophyll fluorescence for the Xf detection. This work demonstrates that large-scale Xf monitoring can be supported using airborne platforms carrying multispectral and thermal cameras with a limited number of spectral bands (e.g., six to 12 bands with 10 nm bandwidths) as long as they are carefully selected by their sensitivity to the Xf symptoms. More precisely, the blue (bands between 400 and 450 nm to derive the NPQI index) and thermal (to derive CWSI from tree temperature) were the most critical spectral regions for their sensitivity to Xf symptoms in olive. Numéro de notice : A2020-120 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.02.010 Date de publication en ligne : 18/02/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.02.010 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94745 [article]

Spatial aspects of MRSA epidemiology: a case study using stochastic simulation, kernel estimation and SaTScan / Lucy Bastin in International journal of geographical information science IJGIS, vol 21 n° 6-7 (july 2007)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 21 n° 6-7 (july 2007) . - pp 811 - 836 Titre : Spatial aspects of MRSA epidemiology: a case study using stochastic simulation, kernel estimation and SaTScan Type de document : Article/Communication Auteurs : Lucy Bastin, Auteur ; J. Rollason, Auteur ; A. Hilton, Auteur ; et al., Auteur Année de publication : 2007 Article en page(s) : pp 811 - 836 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] analyse de groupement [Termes IGN] analyse spatiale [Termes IGN] épidémie [Termes IGN] estimation par noyau [Termes IGN] Grande-Bretagne [Termes IGN] maladie bactérienne [Termes IGN] simulation [Termes IGN] surveillance sanitaire Résumé : (Auteur) The identification of disease clusters in space or space-time is of vital importance for public health policy and action. In the case of methicillin-resistant Staphylococcus aureus (MRSA), it is particularly important to distinguish between community and health care-associated infections, and to identify reservoirs of infection. 832 cases of MRSA in the West Midlands (UK) were tested for clustering and evidence of community transmission, after being geo-located to the centroids of UK unit postcodes (postal areas roughly equivalent to Zip+4 zip code areas). An age-stratified analysis was also carried out at the coarser spatial resolution of UK Census Output Areas. Stochastic simulation and kernel density estimation were combined to identify significant local clusters of MRSA (p Numéro de notice : A2007-273 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810601135767 En ligne : https://doi.org/10.1080/13658810601135767 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28636 [article]

Exemplaires(2)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-07041	RAB	Revue	Centre de documentation	En réserve L003	Disponible
079-07042	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Modelling a discrete spatial response using generalized linear mixed models: application to Lyme disease vectors / Abhik Das in International journal of geographical information science IJGIS, vol 16 n° 2 (march 2002)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 16 n° 2 (march 2002) . - pp 151 - 166 Titre : Modelling a discrete spatial response using generalized linear mixed models: application to Lyme disease vectors Type de document : Article/Communication Auteurs : Abhik Das, Auteur ; S.R. Lele, Auteur ; G.E. Glass, Auteur ; T. Shields, Auteur ; J. Patz, Auteur Année de publication : 2002 Article en page(s) : pp 151 - 166 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] corrélation automatique de points homologues [Termes IGN] distribution de Poisson [Termes IGN] distribution spatiale [Termes IGN] maladie bactérienne [Termes IGN] modélisation spatiale Résumé : (Auteur) Predicting disease risk by identifying environmental factors responsible for the geographical distribution of disease vectors can help target control strategies and optimize preventive measures. In this study we present a hierarchical approach to model the distribution of Lyme disease ticks as a function of environmental factors. We use the Poisson framework natural for count data while allowing for spatial correlations. To help identify environmental factors that best explain tick abundance, we develop an intuitive procedure for covariate selection in the spatial context. These methods could be useful in analysing effects of environmental and climatological changes on the distribution of disease vectors, and the spatial extrapolation of vector abundance under such scenarios. Numéro de notice : A2002-025 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1080/13658810110099134 En ligne : https://doi.org/10.1080/13658810110099134 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21942 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-02021	RAB	Revue	Centre de documentation	En réserve L003	Disponible