The use of black & white air photographs for the production of historic land cover maps can be done by image classification, using additional texture features. In this paper we evaluate the importance of a number of parameters in the image classification process based on texture, such as the quantization level, the window size used to produce the texture features, the feature selection criteria and the image spatial resolution. The evaluation was performed using 4 photographs from the 1950s. The influence of the classification method, the number of classes searched for in the images and the post-processing tasks were also investigated. The importance of each of these parameters for the classification accuracy was evaluated by cross validation. The selection of the best parameters was performed based on the validation results, and also on the computation load involved for each case and the end user requirements. An average accuracy of 85.2% was achieved for 4 land cover classes.New Developments and Challenges in Remote Sensing, Z. Bochenek (ed.) ß2007 Millpress, Rotterdam,

BackgroundBacterial spot-causing xanthomonads (BSX) are quarantine phytopathogenic bacteria responsible for heavy losses in tomato and pepper production. Despite the research on improved plant spraying methods and resistant cultivars, the use of healthy plant material is still considered as the most effective bacterial spot control measure. Therefore, rapid and efficient detection methods are crucial for an early detection of these phytopathogens.MethodologyIn this work, we selected and validated novel DNA markers for reliable detection of the BSX Xanthomonas euvesicatoria (Xeu). Xeu-specific DNA regions were selected using two online applications, CUPID and Insignia. Furthermore, to facilitate the selection of putative DNA markers, a customized C program was designed to retrieve the regions outputted by both databases. The in silico validation was further extended in order to provide an insight on the origin of these Xeu-specific regions by assessing chromosomal location, GC content, codon usage and synteny analyses. Primer-pairs were designed for amplification of those regions and the PCR validation assays showed that most primers allowed for positive amplification with different Xeu strains. The obtained amplicons were labeled and used as probes in dot blot assays, which allowed testing the probes against a collection of 12 non-BSX Xanthomonas and 23 other phytopathogenic bacteria. These assays confirmed the specificity of the selected DNA markers. Finally, we designed and tested a duplex PCR assay and an inverted dot blot platform for culture-independent detection of Xeu in infected plants.SignificanceThis study details a selection strategy able to provide a large number of Xeu-specific DNA markers. As demonstrated, the selected markers can detect Xeu in infected plants both by PCR and by hybridization-based assays coupled with automatic data analysis. Furthermore, this work is a contribution to implement more efficient DNA-based methods of bacterial diagnostics.

Phytosanitary regulations and the provision of plant health certificates still rely mainly on long and laborious culture-based methods of diagnosis, which are frequently inconclusive. DNA-based methods of detection can circumvent many of the limitations of currently used screening methods, allowing a fast and accurate monitoring of samples. The genus Xanthomonas includes 13 phytopathogenic quarantine organisms for which improved methods of diagnosis are needed. In this work, we propose 21 new Xanthomonas-specific molecular markers, within loci coding for Xanthomonas-specific protein domains, useful for DNA-based methods of identification of xanthomonads. The specificity of these markers was assessed by a dot blot hybridization array using 23 non-Xanthomonas species, mostly soil dwelling and/or phytopathogens for the same host plants. In addition, the validation of these markers on 15 Xanthomonas spp. suggested species-specific hybridization patterns, which allowed discrimination among the different Xanthomonas species. Having in mind that DNAbased methods of diagnosis are particularly hampered for unsequenced species, namely, Xanthomonas fragariae, Xanthomonas axonopodis pv. phaseoli, and Xanthomonas fuscans subsp. fuscans, for which comparative genomics tools to search for DNA signatures are not yet applicable, emphasis was given to the selection of informative markers able to identify X. fragariae, X. axonopodis pv. phaseoli, and X. fuscans subsp. fuscans strains. In order to avoid inconsistencies due to operator-dependent interpretation of dot blot data, an image-processing algorithm was developed to analyze automatically the dot blot patterns. Ultimately, the proposed markers and the dot blot platform, coupled with automatic data analyses, have the potential to foster a thorough monitoring of phytopathogenic xanthomonads.Xanthomonas is a genus of Gammaproteobacteria that includes numerous phytopathogenic species, each characterized by a narrow host range. However, as a whole, the genus members are able to infect a broad range of plants, distributed over 124 monocotyledonous and 268 dicotyledonous plant species (15). The nomenclature of this complex genus is still under debate, and the taxonomic rank of many previously described pathovars has been revised (28,41,48). At the moment, the European and Mediterranean Plant Protection Organization (EPPO) recommends that 13 members of the genus Xanthomonas be considered quarantine pests. Therefore, reliable, fast, and technically and commercially accessible screening methods of detection and identification are needed to allow the survey of a large number of samples. This would ensure the phytosanitary certification of plants, prevent the spread of contaminated plant material, and facilitate the implementation of timely phytosanitation and quarantine measures (4).The current certified methods of bacterial detection rely mainly on culture-based approaches and plant bioassays (35). While these methods allow for a presumptive identification, they lack resolution of dete...

No abstract

No abstract