22 research outputs found
Imaging and proteomic techniques for monitoring the interactions virus-host plant
Tesis Univ. Granada. Departamento de Fisiología Vegetal. Leída el 27 del 4 del 200
An overview of the special issue on plant phenotyping for disease detection
According to the latest United Nations estimates in September 2021, the world’s population is now 7 [...
Health status of oilseed rape plants grown under potential future climatic conditions assessed by invasive and non-invasive techniques
Environmental conditions affect many plant traits such as biochemistry, physiology, morphology, and even their distribution around the world. Human activities have increased greenhouse gas emissions, which will promote a global rise in temperatures. The impact of climate change on natural vegetation and crops is difficult to predict, making it necessary to conduct experiments that mimic potential future climate conditions. Here, oilseed rape has been grown under environmental conditions that reproduce severe and intermediate climate change, setting the current climatic conditions as a control, with the main objective of evaluating the impact of climate change on the health status of this plant of agronomic interest. For such a purpose, two approaches (invasive and non-invasive) have been applied. Invasive quantitative measurements are based on the absorbance of biochemical compounds. Non-invasive methods such as thermal, multicolor fluorescence, and hyperspectral reflectance imaging sensors rely on the spectral properties of the plants. The results revealed that climate change induced lipid peroxidation, as well as alterations in pigment composition, transpiration, photosynthesis, and secondary plant metabolism. Those changes were more drastic the more severe the climatic condition imposed. Novel vegetation indices obtained from hyperspectral reflectance and specifically tailored to detect stress in brassicas correlated with physiological traits such as lipid peroxidation and secondary plant metabolism.This work was supported by grant number RTI2018-094652-B-I00 funded by Ministerio de Ciencia e Innovación and Agencia Estatal de Investigación: MCIN/AEI/10.13039/501100011033, and by “European Regional Development Fund, ERDF: A way of making Europe”. The free open access publication was partially funded by Consejo Superior de Investigaciones Científicas (CSIC) through the Unidad de Recursos de Información Científica para la Investigación (URICI)
Assessment of black rot in oilseed rape grown under climate change conditions using biochemical methods and computer vision
Global warming is a challenge for plants and pathogens, involving profound changes in the physiology of both contenders to adapt to the new environmental conditions and to succeed in their interaction. Studies have been conducted on the behavior of oilseed rape plants and two races (1 and 4) of the bacterium Xanthomonas campestris pv. campestris (Xcc) and their interaction to anticipate our response in the possible future climate. Symptoms caused by both races of Xcc were very similar to each other under any climatic condition assayed, although the bacterial count from infected leaves differed for each race. Climate change caused an earlier onset of Xcc symptoms by at least 3 days, linked to oxidative stress and a change in pigment composition. Xcc infection aggravated the leaf senescence already induced by climate change. To identify Xcc-infected plants early under any climatic condition, four classifying algorithms were trained with parameters obtained from the images of green fluorescence, two vegetation indices and thermography recorded on Xcc-symptomless leaves. Classification accuracies were above 0.85 out of 1.0 in all cases, with k-nearest neighbor analysis and support vector machines performing best under the tested climatic conditions.This work was supported by grant number RTI2018-094652-B-I00, funded by Ministerio de Ciencia e Innovación and Agencia Estatal de Investigación: MCIN/AEI/10.13039/501100011033/, and by “European Regional Development Fund, ERDF: A way of making Europe”; and by grant Proyecto Intramural 202340E012 funded by Consejo Superior de Investigaciones Científicas (CSIC
Thermal Imaging for Plant Stress Detection and Phenotyping
© 2020 by the authors.In the last few years, large efforts have been made to develop new methods to optimize stress detection in crop fields. Thus, plant phenotyping based on imaging techniques has become an essential tool in agriculture. In particular, leaf temperature is a valuable indicator of the physiological status of plants, responding to both biotic and abiotic stressors. Often combined with other imaging sensors and data-mining techniques, thermography is crucial in the implementation of a more automatized, precise and sustainable agriculture. However, thermal data need some corrections related to the environmental and measuring conditions in order to achieve a correct interpretation of the data. This review focuses on the state of the art of thermography applied to the detection of biotic stress. The work will also revise the most important abiotic stress factors affecting the measurements as well as practical issues that need to be considered in order to implement this technique, particularly at the field scale.This research was funded by Junta de Andalucía, grant number P12-AGR-0370, and Ministerio de Ciencia, Innovación y Universidades (MCIU) by Agencia Estatal de Investigación (AEI) and European Regional Development Fund (ERDF), grant number RTI2018-094652-B-I00.Peer reviewe
Picturing pathogen infection in plants
Several imaging techniques have provided valuable tools to evaluate the impact of biotic stress on host plants. The use of these techniques enables the study of plant-pathogen interactions by analysing the spatial and temporal heterogeneity of foliar metabolism during pathogenesis. In this work we review the use of imaging techniques based on chlorophyll fluorescence, multicolour fluorescence and thermography for the study of virus, bacteria and fungi-infected plants. These studies have revealed the impact of pathogen challenge on photosynthetic performance, secondary metabolism, as well as leaf transpiration as a promising tool for field and greenhouse management of diseases. Images of standard chlorophyll fluorescence (Chl-F) parameters obtained during Chl-F induction kinetics related to photochemical processes and those involved in energy dissipation, could be good stress indicators to monitor pathogenesis. Changes on UV-induced blue (F440) and green fluorescence (F520) measured by multicolour fluorescence imaging in pathogen-challenged plants seem to be related with the up-regulation of the plant secondary metabolism and with an increase in phenolic compounds involved in plant defence, such as scopoletin, chlorogenic or ferulic acids. Thermal imaging visualizes the leaf transpiration map during pathogenesis and emphasizes the key role of stomata on innate plant immunity. Using several imaging techniques in parallel could allow obtaining disease signatures for a specific pathogen. These techniques have also turned out to be very useful for presymptomatic pathogen detection, and powerful non-destructive tools for precision agriculture. Their applicability at lab-scale, in the field by remote sensing, and in high-throughput plant phenotyping, makes them particularly useful. Thermal sensors are widely used in crop fields to detect early changes in leaf transpiration induced by both air-borne and soil-borne pathogens. The limitations of measuring photosynthesis by Chl-F at the canopy level are being solved, while the use of multispectral fluorescence imaging is very challenging due to the type of light excitation that is used.This work was supported by a grant from Junta de Andalucía (P12-AGR-0370)Peer Reviewe
Imaging sensors for stress detection and plant phenotyping
1 página - Conferencia invitada presentada en: Understanding plant responses to climate change: redox-based strategies. Universidad Internacional de Andalucía, Baeza, Jaén. 20-22 septiembre 2021.This work was supported by grants from Junta de Andalucía (P12-AGR-0370) and the Spanish Ministry of Science and Education/AEI/ERDF, EU (RTI2018-094652-B-I00
Use of multicolour fluorescence imaging in plant phenotyping
We have explored the use of MCFI for the detection of a wide range of pathogens infecting crop plants: parasitic weed (broomrape in sunflower); virus (Grapevine Leafroll Associated Virus 3 in grapevine); bacteria (Pseudomonas syringae pvs. in bean and tomato); fungus (Podosphaera fusca on cucurbits). The application of MCFI to the detection of biotic stress on crop plants at lab scale shows the convenience of this technique in plant disease detection and its applicability in plant phenotyping programs.Peer Reviewe
Detection of bacterial infection in melon plants by classification methods based on imaging data
The bacterium Dickeya dadantii is responsible of important economic losses in crop yield worldwide. In melon leaves, D. dadantii produced multiple necrotic spots surrounded by a chlorotic halo, followed by necrosis of the whole infiltrated area and chlorosis in the surrounding tissues. The extent of these symptoms, as well as the day of appearance, was dose-dependent. Several imaging techniques (variable chlorophyll fluorescence, multicolor fluorescence, and thermography) provided spatial and temporal information about alterations in the primary and secondary metabolism, as well as the stomatal activity in the infected leaves. Detection of diseased leaves was carried out by using machine learning on the numerical data provided by these imaging techniques. Mathematical algorithms based on data from infiltrated areas offered 96.5 to 99.1% accuracy when classifying them as mock vs. bacteria-infiltrated. These algorithms also showed a high performance of classification of whole leaves, providing accuracy values of up to 96%. Thus, the detection of disease on whole leaves by a model trained on infiltrated areas appears as a reliable method that could be scaled-up for use in plant breeding programs or precision agriculture
Phenotyping Plant Responses to Biotic Stress by Chlorophyll Fluorescence Imaging
Photosynthesis is a pivotal process in plant physiology, and its regulation plays an important role in plant defense against biotic stress. Interactions with pathogens and pests often cause alterations in the metabolism of sugars and sink/source relationships. These changes can be part of the plant defense mechanisms to limit nutrient availability to the pathogens. In other cases, these alterations can be the result of pests manipulating the plant metabolism for their own benefit. The effects of biotic stress on plant physiology are typically heterogeneous, both spatially and temporarily. Chlorophyll fluorescence imaging is a powerful tool to mine the activity of photosynthesis at cellular, leaf, and whole-plant scale, allowing the phenotyping of plants. This review will recapitulate the responses of the photosynthetic machinery to biotic stress factors, from pathogens (viruses, bacteria, and fungi) to pests (herbivory) analyzed by chlorophyll fluorescence imaging both at the lab and field scale. Moreover, chlorophyll fluorescence imagers and alternative techniques to indirectly evaluate photosynthetic traits used at field scale are also revised.This work was supported by grants from CICE-Junta de Andalucía (P12-AGR-0370) and Ministerio de Ciencia, Innovación y Universidades (RTI2018-094652-B-I00).Peer Reviewe