Etiología, epidemiología y control del Mildiu de la adormidera

La adormidera es uno de los cultivos más importantes para la industria farmacéutica en España ya que constituye la única fuente de morfina, codeína y tebaína. Durante los últimos años, los rendimientos del cultivo de adormidera han venido disminuyendo como consecuencia de ataques de una enfermedad. El objetivo de esta Tesis Doctoral ha sido el obtener nuevos conocimientos sobre la etiología, biología y epidemiología del Mildiu de la adormidera, así como sobre la caracterización y detección molecular específica del agente causal, que permitan establecer las bases científicas para el desarrollo de estrategias eficientes para el control integrado de la enfermedad. Se ha determinado el agente causal del mildiu de la adormidera en España y Francia como Peronospora arborescens y su diversidad genética en los cultivos de adormidera. Además se han desarrollado tres protocolos de detección molecular mediante PCR y cebadores específicos recogidos en la patente española Nº P200603319, y extendida internacionalmente con la aplicación Nº PCT/ES2007/000781, los cuales han sido empleado para responder de forma eficiente a diferentes cuestiones sobre este patosistema: i) PCR simple: con tres parejas de cebadores que permitió detectar eficientemente P. arborescens en diferentes tejidos sintomáticos y asintomáticos de la planta y permitió demostrar que P. arborescens puede ser trasmitido por semillas; ii) PCR aninada: Con dos parejas de cebadores la cual supuso un incremento en la sensibilidad de detección y permitió amplificar P. arborescens en muestras de herbario y/o asintomáticas de Papaver spp., así como demostrar que P. arborescens puede generar infecciones sistémicas asintomáticas en adormidera; iii) PCR cuantitativa, con excelentes propiedades de reproducibilidad, eficiencia y valores de correlación. Además se desarrolló un modelo robusto y universal como control de la cuantificación que permitió cuantificar niveles de ADN de P. arborescens en diferentes tejidos de adormidera y lote de semillas. Finalmente se abordó el estudio del patosistema determinando cuestiones relaciones con naturaleza de inóculo e infecciones determinantes para el desarrollo de epidemias mediante un abordaje experimental integrador de técnicas clásicas y moleculares que ha demostrado la trasmisión del patógeno en semillas que pueden ser infectadas/infestadas debido a infecciones sistémicas primarias por oosporas así como por infecciones secundarias por esporangios, que a su vez pueden ser sistémicas o no, y sintomáticas o asintomáticas. Los esporangios desarrollados en plantas son eficientes en producir nuevas infecciones secundarias que diseminan la enfermedad a plantas asintomáticas. A su vez, estas infecciones pueden ser sistémicas o no. Las oosporas contenidas en restos de cosecha infestados o en suelo infestado son eficientes en originar infecciones en los órganos subterráneos de plántulas de adormidera durante el establecimiento del cultivo y originar infecciones sistémicas sintomáticas o asintomáticas. Esta Tesis Doctoral ha permitido por tanto desarrollar nuevas tecnologías que permitirán establecer medidas efectivas de control de la enfermedad, fundamentalmente basadas en los principios de exclusión y erradicación, aplicables fundamentalmente sobre semillas infectadas o sobre cultivos de adormidera comerciales. Además, la presente Tesis Doctoral ha establecido las bases científicas y tecnológicas para el desarrollo de (i) programas de certificación sanitaria de semilla de adormidera, (ii) evaluación de material vegetal en programas de mejora genética de variedades resistentes/tolerantes, y (iii) estudios sobre la epidemiología y dispersión del agente causal; aspectos fundamentales para el Control de la enfermedad

Método para la detección, identificación y cuantificación de Peronospora arborescens por PCR cuantitativa en tiempo real

Método para la detección, identificación y cuantificación de Peronospora arborescens por PCR cuantitativa en tiempo real. El método para la cuantificación de Peronospora arborescens por PCR cuantitativa (qPCR) en una muestra biológica, comprende extraer el ADN contenido en dicha muestra biológica y amplificarlo mediante qPCR. De aplicación en la cuantificación de P. arborescens.Peer reviewedConsejo Superior de Investigaciones Científicas (España), ALCALIBER SA, Universidad de CórdobaA1 Solicitud de patentes con informe sobre el estado de la técnic

Combined use of a new SNP-based assay and multilocus SSR markers to assess genetic diversity of Xylella fastidiosa subsp. pauca infecting citrus and coffee plants

Two haplotypes of Xylella fastidiosa subsp. pauca (Xfp) that correlated with their host of origin were identified in a collection of 90 isolates infecting citrus and coffee plants in Brazil, based on a single-nucleotide polymorphism in the gyrB sequence. A new single-nucleotide primer extension (SNuPE) protocol was designed for rapid identification of Xfp according to the host source. The protocol proved to be robust for the prediction of the Xfp host source in blind tests using DNA from cultures of the bacterium, infected plants, and insect vectors allowed to feed on Xfp-infected citrus plants. AMOVA and STRUCTURE analyses of microsatellite data separated most Xfp populations on the basis of their host source, indicating that they were genetically distinct. The combined use of the SNaPshot protocol and three previously developed multilocus SSR markers showed that two haplotypes and distinct isolates of Xfp infect citrus and coffee in Brazil and that multiple, genetically different isolates can be present in a single orchard or infect a single tree. This combined approach will be very useful in studies of the epidemiology of Xfp-induced diseases, host specificity of bacterial genotypes, the occurrence of Xfp host jumping, vector feeding habits, etc., in economically important cultivated plants or weed host reservoirs of Xfp in Brazil and elsewhere [Int Microbiol 2015; 18(1):13-24]Keywords: Citrus variegated chlorosis · coffee leaf scorch · vector transmission· xylem-limited bacteria · haplotype characterization · host-plant associatio

Combined use of a new SNP-based assay and multilocus SSR markers to assess genetic diversity of Xylella fastidiosa subsp. pauca infecting citrus and coffee plants

Two haplotypes of Xylella fastidiosa subsp. pauca (Xfp) that correlated with their host of origin were identified in a collection of 90 isolates infecting citrus and coffee plants in Brazil, based on a single-nucleotide polymorphism in the gyrB sequence. A new single-nucleotide primer extension (SNuPE) protocol was designed for rapid identification of Xfp according to the host source. The protocol proved to be robust for the prediction of the Xfp host source in blind tests using DNA from cultures of the bacterium, infected plants, and insect vectors allowed to feed on Xfp- infected citrus plants. AMOVA and STRUCTURE analyses of microsatellite data separated most Xfp populations on the basis of their host source, indicating that they were genetically distinct. The combined use of the SNaPshot protocol and three previously developed multilocus SSR markers showed that two haplotypes and distinct isolates of Xfp infect citrus and coffee in Brazil and that multiple, genetically different isolates can be present in a single orchard or infect a single tree. This combined approach will be very useful in studies of the epidemiology of Xfp- induced diseases, host specificity of bacterial genotypes, the occurrence of Xfp host jumping, vector feeding habits, etc., in economically important cultivated plants or weed host reservoirs of Xfp in Brazil and elsewhere [Int Microbiol 2015; 18(1):13-24].We acknowledge financial support from the EU grant ICA4-CT-2001-10005 and an ‘Intramural Project’ to B. B. Landa from the Spanish National Research Council (CSIC), as well as CNPq for a scholarship to J. R. S. Lopes in Brazil.Peer reviewe

Draft Genome Sequence of Xylella fastidiosa subsp. Fastidiosa Strain IVIA5235, Isolated from Prunus avium in Mallorca Island, Spain

We report the complete annotated genome sequence of the plant-pathogenic bacterium Xylella fastidiosa subsp. fastidiosa strain IVIA5235. This strain was recovered from a cherry tree in Mallorca, Spain

Detection of Xylella fastidiosa in almond orchards by synergic use of an epidemic spread model and remotely sensed plant traits

The early detection of Xylella fastidiosa (Xf) infections is critical to the management of this dangerous plan pathogen across the world. Recent studies with remote sensing (RS) sensors at different scales have shown that Xf-infected olive trees have distinct spectral features in the visible and infrared regions (VNIR). However, further work is needed to integrate remote sensing in the management of plant disease epidemics. Here, we research how the spectral changes picked up by different sets of RS plant traits (i.e., pigments, structural or leaf protein content), can help capture the spatial dynamics of Xf spread. We coupled a spatial spread model with the probability of Xf-infection predicted by a RS-driven support vector machine (RS-SVM) model. Furthermore, we analyzed which RS plant traits contribute most to the output of the prediction models. For that, in almond orchards affected by Xf (n = 1426 trees), we conducted a field campaign simultaneously with an airborne campaign to collect high-resolution thermal images and hyperspectral images in the visible-near-infrared (VNIR, 400–850 nm) and short-wave infrared regions (SWIR, 950–1700 nm). The best performing RS-SVM model (OA = 75%; kappa = 0.50) included as predictors leaf protein content, nitrogen indices (NIs), fluorescence and a thermal indicator (Tc), alongside pigments and structural parameters. Leaf protein content together with NIs contributed 28% to the explanatory power of the model, followed by chlorophyll (22%), structural parameters (LAI and LIDFa), and chlorophyll indicators of photosynthetic efficiency. Coupling the RS model with an epidemic spread model increased the accuracy (OA = 80%; kappa = 0.48). In the almond trees where the presence of Xf was assayed by qPCR (n = 318 trees), the combined RS-spread model yielded an OA of 71% and kappa = 0.33, which is higher than the RS-only model and visual inspections (both OA = 64–65% and kappa = 0.26–31). Our work demonstrates how combining spatial epidemiological models and remote sensing can lead to highly accurate predictions of plant disease spatial distribution

Aplicaciones de metodologías moleculares y biotecnológicas en la investigación sobre las enfermedades de cultivos en la Agricultura Sostenible

Las enfermedades son un componente de significación en la producción agrícola actual porque pueden reducir el rendimiento potencial o causar devastación en los cultivos de plantas; y la extensión y severidad de sus ataques va unida a los cambios que se están produciendo en los sistemas de manejo que dan lugar a mejoras en el rendimiento o modificaciones en los ambientes de producción. El control eficiente de las enfermedades requiere necesariamente la determinación exacta, rápida e informativa de su etiología, incluyendo la evaluación de la historia y potencial evolutivo en las poblaciones del agente causal, así como de la composición y diversidad de la microbiota beneficiosa asociada con el crecimiento vegetal, que hagan posible la aplicación eficiente de las acciones de prevención en que se fundamenta el manejo sostenible de dichas enfermedades. Las tecnologías de base molecular y biotecnológica ofrecen una excelente oportunidad para mejorar nuestras capacidades para satisfacer dichos requisitos. En este trabajo se ilustran tales oportunidades utilizando como ejemplo los resultados alcanzados por el Grupo AGR136 ‘Sanidad Vegetal’ durante el desarrollo de programa de investigación llevados a cabo sobre enfermedades importantes en la agricultura andaluz

Progress and achievements on the early detection of Xylella fastidiosa infection and symptom development with hyperspectral and thermal remote sensing imagery

Trabajo presentado en la 3rd European Conference on Xylella fastidiosa (Building knowledge, protecting plant health), celebrada online el 29 y 30 de abril de 2021.Remote sensing efforts made as part of European initiatives via POnTE, XF-ACTORS and the JRC, as well as through regional programs, have focused, among others, on the development of algorithms for the early detection of Xylella fastidiosa (Xf)-induced symptoms. Airborne campaigns carried out between 2016 and 2019 collected high-resolution hyperspectral and thermal images from infected areas in the Apulia region (Italy), in the province of Alicante and on the island of Mallorca (Spain). The remote sensing imagery collections were performed alongside field surveys and laboratory analyses to assess the presence of Xf, and the severity and incidence of disease in olive and almond trees. Radiative transfer models and machine learning algorithms were used to quantify spectral plant traits for each individual infected tree, assessing their importance as pre visual indicators of Xf-induced stress. These studies conducted across species have demonstrated that specific spectral plant traits successfully revealed Xf induced symptoms at early stages, i.e., before visual symptoms appear. The results show that spectral plant traits contribute differently to symptom detection across host species (olive vs. almond), and that abiotic-induced stress affects the performance of the algorithms used for detecting infected trees. Together, the different European initiatives studying the use of remote sensing to support the monitoring of landscapes for Xylella fastidiosa detection lead us to conclude that the early detection of Xf-induced symptoms is feasible when high-resolution hyperspectral imagery and physically-based plant trait retrievals are used, obtaining accuracies exceeding 92% (kappa>0.8). These results are essential to enable the implementation of effective control and management of plant diseases using airborne- droneand satellite-based remote sensing technologies. Moreover, these large-scale hyperspectral and thermal imaging methods greatly contribute to the future operational monitoring of infected areas at large scales, well beyond what is possible from field surveys and laboratory analyses alone

Development of a petrographic classification of fly-ash components from coal combustion and co-combustion. (An ICCP Classification System, Fly-Ash Working Group – Commission III.)

A new system for the microscopic classification of fly-ash components has been developed by the Fly-Ash Working Group, Commission III of the ICCP and is presented herein. The studied fly-ashes were obtained from the combustion of single coals of varied rank, coal blends, and coals blended with other fuels (biomass, petroleum coke), in different operating conditions and by means of different technologies. Microscopic images of the fly-ash samples were used to test the optical criteria proposed for classifying the fly-ash components. The classification system developed is based on a small number of microscopic criteria, subdivided into six independent levels or categories, three of which are directed at whole particle identification on the basis of nature, origin and type of fly-ash particle, while the other three levels are directed at the smaller section identification on the basis of character, structure and optical texture of unburned carbons. To classify the inorganic components of the fly-ash, the criterion proposed is composition in terms of metallic/non-metallic character. To establish the classification criteria the petrographers involved in the work performed three successive round robins. Evaluation of the results by using firstly descriptive statistics and then the criteria and parameters employed by the ICCP in their accreditation programs indicated that the classification of the fly-ash components was accurate and that there was only a minor bias. The main conclusion of this study was that the proposed criteria are valuable for identifying, and classifying fly-ash components and for describing the optical properties of fly-ash particles