Occurrence of Fusarium spp. and Fumonisins in Stored Wheat Grains Marketed in Iran

Wheat grains are well known to be invaded by Fusarium spp. under field and storage conditions and contaminated with fumonisins. Therefore, determining Fusarium spp. and fumonisins in wheat grains is of prime importance to develop suitable management strategies and to minimize risk. Eighty-two stored wheat samples produced in Iran were collected from various supermarkets and tested for the presence of Fusarium spp. by agar plate assay and fumonisins by HPLC. A total of 386 Fusarium strains were isolated and identified through morphological characteristics. All these strains belonged to F. culmorum, F. graminearum, F. proliferatum and F. verticillioides. Of the Fusarium species, F. graminearum was the most prevalent species, followed by F. verticillioides, F. proliferatum and then F. culmorum. Natural occurrence of fumonisin B1 (FB1) could be detected in 56 (68.2%) samples ranging from 15–155 μg/kg, fumonisin B2 (FB2) in 35 (42.6%) samples ranging from 12–86 μg/kg and fumonisin B3 (FB3) in 26 (31.7%) samples ranging from 13–64 μg/kg. The highest FB1 levels were detected in samples from Eilam (up to 155 μg/kg) and FB2 and FB3 in samples from Gilan Gharb (up to 86 μg/kg and 64 μg/kg)

Exploitation of TerraSAR-X Data for Land use/Land Cover Analysis Using Object-Oriented Classification Approach in the African Sahel Area, Sudan.

Recently, object-oriented classification techniques based on image segmentation approaches are being studied using high-resolution satellite images to extract various thematic information. In this study different types of land use/land cover (LULC) types were analysed by employing object-oriented classification approach to dual TerraSAR-X images (HH and HV polarisation) at African Sahel. For that purpose, multi-resolution segmentation (MRS) of the Definiens software was used for creating the image objects. Using the feature space optimisation (FSO) tool the attributes of the TerraSAR-X image were optimised in order to obtain the best separability among classes for the LULC mapping. The backscattering coefficients (BSC) for some classes were observed to be different for HH and HV polarisations. The best separation distance of the tested spectral, shape and textural features showed different variations among the discriminated LULC classes. An overall accuracy of 84 % with a kappa value 0.82 was resulted from the classification scheme, while accuracy differences among the classes were kept minimal. Finally, the results highlighted the importance of a combine use of TerraSAR-X data and object-oriented classification approaches as a useful source of information and technique for LULC analysis in the African Sahel drylands

Urban use of VHR images on Bukavu (Democratic Republic of Congo)

peer reviewedThe main purpose of this study was to show potential uses of very high resolution (VHR) image in an urban analysis of Bukavu in the Democratic Republic of Congo. As for many of the Third-World cities, Bukavu grew up during the last decades and available topographical information on Bukavu dates back to the middle of the twentieth century. This lack of updated information can be compensated by an appropriate use of VHR images. In this study, IKONOS image recorded on the 14th February 2001 was used. Image registration are highly dependant on accurate Digital Elevation Models (DEM), these last ones are also useful in urban analyses. The range between the minimum and maximum altitudes observed in the image was more than 500 meters. Furthermore, the viewing inclination angle is more than 28 degrees. In this case, orthorectification is mandatory for correcting relief displacements. Nevertheless, the lack of good Ground Control Points (GPS’s) on the old topographic maps and the failure to collect field verification data in Bukavu explains the remaining global 2D RMSE of 10 meters. For easier image interpretation, multispectral (4m) and panchromatic (1m) images were fused together by means of the LMVM algorithm. Depending on the object, the Computer Aided Photo Interpretation (CAPI) uses or does not use the near infrared information (true or false colour composite). For a more detailed interpretation about the city morphology we draped the 1m multispectral fused image over the 1m resolution DEM grid. The Built-up Area Index (BAI) computed on the urban mask obtained by CAPI and classification of the vegetation, was compared with the 1954 situation interpreted from topographic maps. The present city shows higher BAI values and in the same time the centre of the city has clearly shifted southward. Statistical analyses are also done on built-up versus slope data. The lack of good GCP’s and the use of DEM produced inaccurate orthorectification which was not adequate for topographical features extraction. Nevertheless the present extensions of Bukavu built-up areas are more than the double of those observed at the beginning of the last half century. New constructions are located on steeper slopes where landslides are frequents. More features could be extracted from the Ikonos image if good GPS measurements were made and if verification by the city authorities was possible. Some practical applications of this study could involve determining better location of new Bukavu extensions