Distinct colonization patterns and cDNA-AFLP transcriptome profiles in compatible and incompatible interactions between melon and different races of Fusarium oxysporum f. sp. melonis

Background: Fusarium oxysporum f. sp. melonis Snyd. & Hans. (FOM) causes Fusarium wilt, the most important infectious disease of melon (Cucumis melo L.). The four known races of this pathogen can be distinguished only by infection on appropriate cultivars. No molecular tools are available that can discriminate among the races, and the molecular basis of compatibility and disease progression are poorly understood. Resistance to races 1 and 2 is controlled by a single dominant gene, whereas only partial polygenic resistance to race 1,2 has been described. We carried out a large-scale cDNA-AFLP analysis to identify host genes potentially related to resistance and susceptibility as well as fungal genes associated with the infection process. At the same time, a systematic reisolation procedure on infected stems allowed us to monitor fungal colonization in compatible and incompatible host-pathogen combinations. Results: Melon plants (cv. Charentais Fom-2), which are susceptible to race 1,2 and resistant to race 1, were artificially infected with a race 1 strain of FOM or one of two race 1,2 w strains. Host colonization of stems was assessed at 1, 2, 4, 8, 14, 16, 18 and 21 days post inoculation (dpi), and the fungus was reisolated from infected plants. Markedly different colonization patterns were observed in compatible and incompatible host-pathogen combinations. Five time points from the symptomless early stage (2 dpi) to obvious wilting symptoms (21 dpi) were considered for cDNA-AFLP analysis. After successful sequencing of 627 transcript-derived fragments (TDFs) differentially expressed in infected plants, homology searching retrieved 305 melon transcripts, 195 FOM transcripts expressed in planta and 127 orphan TDFs. RNA samples from FOM colonies of the three strains grown in vitro were also included in the analysis to facilitate the detection of in planta-specific transcripts and to identify TDFs differentially expressed among races/strains. Conclusion: Our data suggest that resistance against FOM in melon involves only limited transcriptional changes, and that wilting symptoms could derive, at least partially, from an active plant response. We discuss the pathogen-derived transcripts expressed in planta during the infection process and potentially related to virulence functions, as well as transcripts that are differentially expressed between the two FOM races grown in vitro. These transcripts provide candidate sequences that can be further tested for their ability to distinguish between races. Sequence data from this article have been deposited in GenBank, Accession Numbers: HO867279-HO867981

Application of Multilayer Perceptron with Automatic Relevance Determination on Weed Mapping Using UAV Multispectral Imagery

Remote sensing techniques are routinely used in plant species discrimination and of weed mapping. In the presented work, successful Silybum marianum detection and mapping using multilayer neural networks is demonstrated. A multispectral camera (green-red-near infrared) attached on a fixed wing unmanned aerial vehicle (UAV) was utilized for the acquisition of high-resolution images (0.1 m resolution). The Multilayer Perceptron with Automatic Relevance Determination (MLP-ARD) was used to identify the S. marianum among other vegetation, mostly Avena sterilis L. The three spectral bands of Red, Green, Near Infrared (NIR) and the texture layer resulting from local variance were used as input. The S. marianum identification rates using MLP-ARD reached an accuracy of 99.54%. Τhe study had an one year duration, meaning that the results are specific, although the accuracy shows the interesting potential of S. marianum mapping with MLP-ARD on multispectral UAV imagery