Diverse projected climate change scenarios affect the physiology of broccoli plants to different extents.

Climate change caused by global warming involves crucial plant growth factors such as atmospheric CO2 concentration, ambient temperature or water availability. These stressors usually co-occur, causing intricate alterations in plant physiology and development. This work focuses on how elevated atmospheric CO2 levels, together with the concomitant high temperature, would affect the physiology of a relevant crop, such as broccoli. Particular attention has been paid to those defence mechanisms that contribute to plant fitness under abiotic stress. Results show that both photosynthesis and leaf transpiration were reduced in plants grown under climate change environments compared to those grown under current climate conditions. Furthermore, an induction of carbohydrate catabolism pointed to a redistribution from primary to secondary metabolism. This result could be related to a reinforcement of cell walls, as well as to an increase in the pool of antioxidants in the leaves. Broccoli plants, a C3 crop, grown under an intermediate condition showed activation of those adaptive mechanisms, which would contribute to coping with abiotic stress, as confirmed by reduced levels of lipid peroxidation relative to current climate conditions. On the contrary, the most severe climate change scenario exceeded the adaptive capacity of broccoli plants, as shown by the inhibition of growth and reduced vigour of plants. In conclusion, only a moderate increase in atmospheric CO2 concentration and temperature would not have a negative impact on broccoli crop yields.

Virulence determines beneficial trade-offs in the response of virus-infected plants to drought via induction of salicylic acid.

It has been hypothesized that plants can get beneficial trade-offs from viral infections when grown under drought conditions. However, experimental support for a positive correlation between virus-induced drought tolerance and increased host fitness is scarce. We investigated whether increased virulence exhibited by the synergistic interaction involving Potato virus X (PVX) and Plum pox virus (PPV) improves tolerance to drought and host fitness in Nicotiana benthamiana and Arabidopsis thaliana. Infection by the pair PPV/PVX and by PPV expressing the virulence protein P25 of PVX conferred an enhanced drought-tolerant phenotype compared with single infections with either PPV or PVX. Decreased transpiration rates in virus-infected plants were correlated with drought tolerance in N. benthamiana but not in Arabidopsis. Metabolite and hormonal profiles of Arabidopsis plants infected with the different viruses showed a range of changes that positively correlated with a greater impact on drought tolerance. Virus infection enhanced drought tolerance in both species by increasing salicylic acid accumulation in an abscisic acid-independent manner. Viable offspring derived from Arabidopsis plants infected with PPV increased relative to non-infected plants, when exposed to drought. By contrast, the detrimental effect caused by the more virulent viruses overcame potential benefits associated with increased drought tolerance on host fitness.

Alterations in primary and secondary metabolism in Vitis vinifera 'Malvasía de Banyalbufar' upon infection with Grapevine leafroll-associated virus 3.

Plant defense mechanisms against pathogens result in differential regulation of various processes of primary and secondary metabolism. Imaging techniques, such as fluorescence imaging and thermography, are very valuable tools providing spatial and temporal information about these processes. In this study, effects of Grapevine leafroll-associated virus 3 (GLRaV-3) on grapevine physiology were analyzed in pot-grown asymptomatic plants of the white cultivar Malvasía de Banyalbufar. The virus triggered changes in the activity of photosynthesis and secondary metabolism. There was a decrease in the photorespiratory intermediates glycine and serine in infected plants, possibly as a defense response against the infection. The content of malate, which plays an important role in plant metabolism, also decreased. These results correlate with the increased non-photochemical quenching found in infected plants. On the other hand, the concentration of flavonols (represented by myricetin, kaempferol and quercetin derivatives) and hydroxycinnamic acids (which include derivatives of caffeic acid) increased following infection by the virus. These compounds could be responsible for the increase in multicolor fluorescence F440 (blue fluorescence) and F520 (green fluorescence) on the leaves, and changes in the fluorescence parameters F440/F680, F440/F740, F520/F680, F520/F740 and F680/F740. The combined analysis of chlorophyll fluorescence kinetics and blue-green fluorescence emitted by phenolics could constitute disease signatures allowing the discrimination between GLRaV-3 infected and non-infected plants at very early stage of infection, prior to the development of symptoms.

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.

Contribution of the non-effector members of the HrpL regulon, iaaL and matE, to the virulence of Pseudomonas syringae pv. tomato DC3000 in tomato plants.

BACKGROUND: The phytohormone indole-3-acetic acid (IAA) is widely distributed among plant-associated bacteria. Certain strains of the Pseudomonas syringae complex can further metabolize IAA into a less biologically active amino acid conjugate, 3-indole-acetyl-ε-L-lysine, through the action of the iaaL gene. In P. syringae and Pseudomonas savastanoi strains, the iaaL gene is found in synteny with an upstream gene, here called matE, encoding a putative MATE family transporter. In P. syringae pv. tomato (Pto) DC3000, a pathogen of tomato and Arabidopsis plants, the HrpL sigma factor controls the expression of a suite of virulence-associated genes via binding to hrp box promoters, including that of the iaaL gene. However, the significance of HrpL activation of the iaaL gene in the virulence of Pto DC3000 is still unclear. RESULTS: A conserved hrp box motif is found upstream of the iaaL gene in the genomes of P. syringae strains. However, although the promoter region of matE is only conserved in genomospecies 3 of this bacterial group, we showed that this gene also belongs to the Pto DC3000 HrpL regulon. We also demonstrated that the iaaL gene is transcribed both independently and as part of an operon with matE in this pathogen. Deletion of either the iaaL or the matE gene resulted in reduced fitness and virulence of Pto DC3000 in tomato plants. In addition, we used multicolor fluorescence imaging to visualize the responses of tomato plants to wild-type Pto DC3000 and to its ΔmatE and ΔiaaL mutants. Activation of secondary metabolism prior to the development of visual symptoms was observed in tomato leaves after bacterial challenges with all strains. However, the observed changes were strongest in plants challenged by the wild-type strain, indicating lower activation of secondary metabolism in plants infected with the ΔmatE or ΔiaaL mutants. CONCLUSIONS: Our results provide new evidence for the roles of non-type III effector genes belonging to the Pto DC3000 HrpL regulon in virulence.

Spatial and temporal dynamics of primary and secondary metabolism in Phaseolus vulgaris challenged by Pseudomonas syringae.

Many defense mechanisms contribute to the plant immune system against pathogens, involving the regulation of different processes of the primary and secondary metabolism. At the same time, pathogens have evolved mechanisms to hijack the plant defense in order to establish the infection and proliferate. Localization and timing of the host response are essential to understand defense mechanisms and resistance to pathogens (Rico et al. 2011). Imaging techniques, such as fluorescence imaging and thermography, are a very valuable tool providing spatial and temporal information about a series of plant processes. In this study, bean plants challenged with two pathovars of Pseudomonas syringae have been investigated. Pseudomonas syringae pv. phaseolicola 1448A and P. syringae pv. tomato DC3000 elicit a compatible and incompatible interaction in bean, respectively. Both types of host-pathogen interaction triggered different changes in the activity of photosynthesis and the secondary metabolism. We conclude that the combined analysis of leaf temperature, chlorophyll fluorescence and green fluorescence emitted by phenolics allows to discriminate compatible from incompatible P. syringae-Phaseolus vulgaris interactions in very early times of the infection, prior to the development of symptoms. These can constitute disease signatures that would allow an early identification of emerging plagues in crops.

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.

Novel Vegetation Indices to Identify Broccoli Plants Infected With Xanthomonas campestris pv. campestris.

A rapid diagnosis of black rot in brassicas, a devastating disease caused by Xanthomonas campestris pv. campestris (Xcc), would be desirable to avoid significant crop yield losses. The main aim of this work was to develop a method of detection of Xcc infection on broccoli leaves. Such method is based on the use of imaging sensors that capture information about the optical properties of leaves and provide data that can be implemented on machine learning algorithms capable of learning patterns. Based on this knowledge, the algorithms are able to classify plants into categories (healthy and infected). To ensure the robustness of the detection method upon future alterations in climate conditions, the response of broccoli plants to Xcc infection was analyzed under a range of growing environments, taking current climate conditions as reference. Two projections for years 2081-2100 were selected, according to the Assessment Report of Intergovernmental Panel on Climate Change. Thus, the response of broccoli plants to Xcc infection and climate conditions has been monitored using leaf temperature and five conventional vegetation indices (VIs) derived from hyperspectral reflectance. In addition, three novel VIs, named diseased broccoli indices (DBI1-DBI3), were defined based on the spectral reflectance signature of broccoli leaves upon Xcc infection. Finally, the nine parameters were implemented on several classifying algorithms. The detection method offering the best performance of classification was a multilayer perceptron-based artificial neural network. This model identified infected plants with accuracies of 88.1, 76.9, and 83.3%, depending on the growing conditions. In this model, the three Vis described in this work proved to be very informative parameters for the disease detection. To our best knowledge, this is the first time that future climate conditions have been taken into account to develop a robust detection model using classifying algorithms.

An extremely low stomatal density mutant overcomes cooling limitations at supra-optimal temperature by adjusting stomatal size and leaf thickness.

The impact of global warming on transpiration and photosynthesis would compromise plant fitness, impacting on crop yields and ecosystem functioning. In this frame, we explored the performance of a set of Arabidopsis mutants carrying partial or total loss-of-function alleles of stomatal development genes and displaying distinct stomatal abundances. Using microscopy and non-invasive imaging techniques on this genotype collection, we examined anatomical leaf and stomatal traits, plant growth and development, and physiological performance at optimal (22°C) and supra-optimal (30°C) temperatures. All genotypes showed thermomorphogenetic responses but no signs of heat stress. Data analysis singled out an extremely low stomatal abundance mutant, spch-5. At 22°C, spch-5 had lower transpiration and warmer leaves than the wild type. However, at 30°C, this mutant developed larger stomata and thinner leaves, paralleled by a notable cooling capacity, similar to that of the wild type. Despite their low stomatal density (SD), spch-5 plants grown at 30°C showed no photosynthesis or growth penalties. The behavior of spch-5 at supra-optimal temperature exemplifies how the effect of very low stomatal numbers can be counteracted by a combination of larger stomata and thinner leaves. Furthermore, it provides a novel strategy for coping with high growth temperatures.

Photosynthesis limitations during water stress acclimation and recovery in the drought-adapted Vitis hybrid Richter-110 (V. berlandierixV. rupestris).

The hybrid Richter-110 (Vitis berlandierixVitis rupestris) has the reputation of being a genotype strongly adapted to drought. A study was performed with plants of R-110 subjected to sustained water-withholding to induce acclimation to two different levels of water stress, followed by rewatering to induce recovery. The goal was to analyse how photosynthesis is regulated during acclimation to water stress and recovery. In particular, the regulation of stomatal conductance (g(s)), mesophyll conductance to CO(2) (g(m)), leaf photochemistry (chlorophyll fluorescence and thermoluminescence), and biochemistry (V(c,max)) were assessed. During water stress, g(s) declined to 0.1 and less than 0.05 mol CO(2) m(-2) s(-1) in moderately and severely water-stressed plants, respectively, and was kept quite constant during an acclimation period of 1-week. Leaf photochemistry proved to be very resistant to the applied water-stress conditions. By contrast, g(m) and V(c,max) were affected by water stress, but they were not kept constant during the acclimation period. g(m) was initially unaffected by water stress, and V(c,max) even increased above control values. However, after several days of acclimation to water stress, both parameters declined below (g(m)) or at (V(c,max)) control values. For the latter two parameters there seemed to be an interaction between water stress and cumulative irradiance, since both recovered to control values after several cloudy days despite water stress. A photosynthesis limitation analysis revealed that diffusional limitations and not biochemical limitations accounted for the observed decline in photosynthesis during water stress and slow recovery after rewatering, both in moderately and severely stressed plants. However, the relative contribution of stomatal (SL) and mesophyll conductance (MCL) limitations changes during acclimation to water stress, from predominant SL early during water stress to similar SL and MCL after acclimation. Finally, photosynthesis recovery after rewatering was mostly limited by SL, since stomatal closure recovered much more slowly than g(m).

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.

Noninvasive determination of toxic stress biomarkers by high-throughput screening of photoautotrophic cell suspension cultures with multicolor fluorescence imaging.

BACKGROUND: With increasing pollution, herbicide application and interest in plant phenotyping, sensors capturing early responses to toxic stress are demanded for screening susceptible or resistant plant varieties. Standard toxicity tests on plants are laborious, demanding in terms of space and material, and the measurement of growth-inhibition based endpoints takes relatively long time. The aim of this work was to explore the potential of photoautotrophic cell suspension cultures for high-throughput early toxicity screening based on imaging techniques. The investigation of the universal potential of fluorescence imaging methods involved testing of three toxicants with different modes of action (DCMU, glyphosate and chromium). RESULTS: The increased pace of testing was achieved by using non-destructive imaging methods-multicolor fluorescence (MCF) and chlorophyll fluorescence (ChlF). These methods detected the negative effects of the toxicants earlier than it was reflected in plant growth inhibition (decrease in leaf area and final dry weight). Moreover, more subtle and transient effects not resulting in growth inhibition could be detected by fluorescence. The pace and sensitivity of stress detection was further enhanced by using photoautotrophic cell suspension cultures. These reacted sooner, more pronouncedly and to lower concentrations of the tested toxicants than the plants. Toxicant-specific stress signatures were observed as a combination of MCF and ChlF parameters and timing of the response. Principal component analysis was found to be useful for reduction of the collected multidimensional data sets to a few informative parameters allowing comparison of the toxicant signatures. CONCLUSIONS: Photoautotrophic cell suspension cultures have proved to be useful for rapid high-throughput screening of toxic stress and display a potential for employment as an alternative to tests on whole plants. The MCF and ChlF methods are capable of distinguishing early stress signatures of at least three different modes of action.

RNA-seq analysis and fluorescence imaging of melon powdery mildew disease reveal an orchestrated reprogramming of host physiology.

The cucurbit powdery mildew elicited by Podosphaera xanthii is one of the most important limiting factors in cucurbit production. Our knowledge of the genetic and molecular bases underlying the physiological processes governing this disease is very limited. We used RNA-sequencing to identify differentially expressed genes in leaves of Cucumis melo upon inoculation with P. xanthii, using RNA samples obtained at different time points during the early stages of infection and their corresponding uninfected controls. In parallel, melon plants were phenotypically characterized using imaging techniques. We found a high number of differentially expressed genes (DEGs) in infected plants, which allowed for the identification of many plant processes that were dysregulated by the infection. Among those, genes involved in photosynthesis and related processes were found to be upregulated, whereas genes involved in secondary metabolism pathways, such as phenylpropanoid biosynthesis, were downregulated. These changes in gene expression could be functionally validated by chlorophyll fluorescence imaging and blue-green fluorescence imaging analyses, which corroborated the alterations in photosynthetic activity and the suppression of phenolic compound biosynthesis. The powdery mildew disease in melon is a consequence of a complex and multifaceted process that involves the dysregulation of many plant pathways such as primary and secondary metabolism.

Opportunities and Limitations of Crop Phenotyping in Southern European Countries.

The Mediterranean climate is characterized by hot dry summers and frequent droughts. Mediterranean crops are frequently subjected to high evapotranspiration demands, soil water deficits, high temperatures, and photo-oxidative stress. These conditions will become more severe due to global warming which poses major challenges to the sustainability of the agricultural sector in Mediterranean countries. Selection of crop varieties adapted to future climatic conditions and more tolerant to extreme climatic events is urgently required. Plant phenotyping is a crucial approach to address these challenges. High-throughput plant phenotyping (HTPP) helps to monitor the performance of improved genotypes and is one of the most effective strategies to improve the sustainability of agricultural production. In spite of the remarkable progress in basic knowledge and technology of plant phenotyping, there are still several practical, financial, and political constraints to implement HTPP approaches in field and controlled conditions across the Mediterranean. The European panorama of phenotyping is heterogeneous and integration of phenotyping data across different scales and translation of "phytotron research" to the field, and from model species to crops, remain major challenges. Moreover, solutions specifically tailored to Mediterranean agriculture (e.g., crops and environmental stresses) are in high demand, as the region is vulnerable to climate change and to desertification processes. The specific phenotyping requirements of Mediterranean crops have not yet been fully identified. The high cost of HTPP infrastructures is a major limiting factor, though the limited availability of skilled personnel may also impair its implementation in Mediterranean countries. We propose that the lack of suitable phenotyping infrastructures is hindering the development of new Mediterranean agricultural varieties and will negatively affect future competitiveness of the agricultural sector. We provide an overview of the heterogeneous panorama of phenotyping within Mediterranean countries, describing the state of the art of agricultural production, breeding initiatives, and phenotyping capabilities in five countries: Italy, Greece, Portugal, Spain, and Turkey. We characterize some of the main impediments for development of plant phenotyping in those countries and identify strategies to overcome barriers and maximize the benefits of phenotyping and modeling approaches to Mediterranean agriculture and related sustainability.

Multicolor fluorescence imaging of leaves--a useful tool for visualizing systemic viral infections in plants.

Multicolor fluorescence induced by UV light is a sensitive and specific tool that may be used to provide information about the primary and secondary metabolism of plants by monitoring signals of the chlorophyll fluorescence (Chl-F) and blue-green fluorescence (BGF), respectively. We have followed the systemic infection of Nicotiana benthamiana plants with the Pepper mild mottle virus (PMMoV) by means of a multicolor fluorescence-imaging system, to detect differences between two strains of PMMoV during the infection process and to establish a correlation between the virulence and changes induced in the host plant. Changes in both BGF and Chl-F were monitored. BGF increased mainly in the abaxial side of the leaf during pathogenesis and the corresponding images showed a clear vein-associated pattern in leaves of infected plants. HPLC analysis of leaf extracts was carried out to identify compounds emitting BGF, and determined that chlorogenic acid was one of the main contributors. BGF imaging was able to detect viral-induced changes in asymptomatic (AS) leaves before detection of the virus itself. Chl-F images confirmed our previous results of alterations in the photosynthetic apparatus of AS leaves from infected plants that were detected with other imaging techniques. Fluorescence ratios F440/F690 and F440/F740, which increase during pathogenesis, were excellent indicators of biotic stress.

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.

Copper and cadmium tolerance, uptake and effect on chloroplast ultrastructure. Studies on Salix purpurea and Phragmites australis.

We have compared the effect of toxic Cu and Cd concentrations on growth, metal accumulation, and chloroplast ultrastructure of willow (Salix purpurea L.) and reed [Phragmites australis (Cav.) Trin. ex Steud.]. After a 10-day treatment, both species have tolerated to some extent the lowest concentration of both metals; however, plant growth was strongly reduced at the highest Cu and Cd concentrations. These plants could be described as Cu-tolerant at the lowest concentration tested, showing a higher tolerance index in reed than in willow; in contrast, willow exhibited higher tolerance against Cd. Both plants appeared to be moderate root accumulators of Cu and Cd. Ultrastructural studies revealed special features that can provide some protection against heavy metals stress, such as ferritin aggregates in the stroma. In addition, Cu and Cd induced distortion of thylakoids, reduction of grana stacks, as well as an increased number and size of plastoglobuli and peripheral vesicles.

Use of multicolour fluorescence imaging for diagnosis of bacterial and fungal infection on zucchini by implementing machine learning.

Zucchini (Cucurbita pepo L.) is a cucurbitaceous plant ranking high in economic importance among vegetable crops worldwide. Pathogen infections cause alterations in plants primary and secondary metabolism that lead to a significant decrease in crop quality and yield. Such changes can be monitored by remote and proximal sensing, providing spatial and temporal information about the infection process. Remote sensing can also provide specific signatures of disease that could be used in phenotyping and to detect a pest, forecast its evolution and predict crop yield. In this work, metabolic changes triggered by soft rot (caused by Dickeya dadantii) and powdery mildew (caused by Podosphaera fusca) on zucchini leaves have been studied by multicolour fluorescence imaging and by thermography. The fluorescence parameter F520/F680 showed statistically significant differences between infected (with D. dadantii or P. fusca) and mock-control leaves during the whole period of study. Artificial neural networks, logistic regression analyses and support vector machines trained with a set of features characterising the histograms of F520/F680 images could be used as classifiers, discriminating between healthy and infected leaves. These results show the applicability of multicolour fluorescence imaging on plant phenotyping.

Use of Blue-Green Fluorescence and Thermal Imaging in the Early Detection of Sunflower Infection by the Root Parasitic Weed Orobanche cumana Wallr.

Although the impact of Orobanche cumana Wallr. on sunflower (Helianthus annuus L.) becomes evident with emergence of broomrape shoots aboveground, infection occurs early after sowing, the host physiology being altered during underground parasite stages. Genetic resistance is the most effective control method and one of the main goals of sunflower breeding programmes. Blue-green fluorescence (BGF) and thermal imaging allow non-destructive monitoring of plant diseases, since they are sensitive to physiological disorders in plants. We analyzed the BGF emission by leaves of healthy sunflower plantlets, and we implemented BGF and thermal imaging in the detection of the infection by O. cumana during underground parasite development. Increases in BGF emission were observed in leaf pairs of healthy sunflowers during their development. Lower BGF was consistently detected in parasitized plants throughout leaf expansion and low pigment concentration was detected at final time, supporting the interpretation of a decrease in secondary metabolites upon infection. Parasite-induced stomatal closure and transpiration reduction were suggested by warmer leaves of inoculated sunflowers throughout the experiment. BGF imaging and thermography could be implemented for fast screening of sunflower breeding material. Both techniques are valuable approaches to assess the processes by which O. cumana alters physiology (secondary metabolism and photosynthesis) of sunflower.

Multicolor Fluorescence Imaging as a Candidate for Disease Detection in Plant Phenotyping.

The negative impact of conventional farming on environment and human health make improvements on farming management mandatory. Imaging techniques are implemented in remote sensing for monitoring crop fields and plant phenotyping programs. The increasingly large size and complexity of the data obtained by these techniques, makes the implementation of powerful mathematical tools necessary in order to identify informative parameters and to apply them in precision agriculture. Multicolor fluorescence imaging is a useful approach for the study of plant defense responses to stress factors at bench scale. However, it has not been fully applied to plant phenotyping. This work evaluates the possible application of multicolor fluorescence imaging in combination with thermography for the particular case of zucchini plants affected by soft-rot, caused by Dickeya dadantii. Several statistical models -based on logistic regression analysis (LRA) and artificial neural networks (ANN)- were obtained for the experimental system zucchini-D. dadantii, which classify new samples as "healthy" or "infected." The LRA worked best in identifying high dose-infiltrated leaves (in infiltrated and non-infiltrated areas) whereas ANN offered a higher accuracy at identifying low dose-infiltrated areas. To assess the applicability of these results to cucurbits in a more general way, these models were validated for melon infected by the same pathogen, achieving accurate predictions for the infiltrated areas. The values of accuracy achieved are comparable to those found in the literature for classifiers identifying other infections based on data obtained by different techniques. Thus, MCFI in combination with thermography prove useful at providing data at lab scale that can be analyzed by machine learning. This approach could be scaled up to be applied in plant phenotyping.