Identification of Fusarium Head Blight in Winter Wheat Ears Using Continuous Wavelet Analysis.

Fusarium head blight in winter wheat ears produces the highly toxic mycotoxin deoxynivalenol (DON), which is a serious problem affecting human and animal health. Disease identification directly on ears is important for selective harvesting. This study aimed to investigate the spectroscopic identification of Fusarium head blight by applying continuous wavelet analysis (CWA) to the reflectance spectra (350 to 2500 nm) of wheat ears. First, continuous wavelet transform was used on each of the reflectance spectra and a wavelet power scalogram as a function of wavelength location and the scale of decomposition was generated. The coefficient of determination R2 between wavelet powers and the disease infestation ratio were calculated by using linear regression. The intersections of the top 5% regions ranking in descending order based on the R2 values and the statistically significant (p-value of t-test < 0.001) wavelet regions were retained as the sensitive wavelet feature regions. The wavelet powers with the highest R2 values of each sensitive region were retained as the initial wavelet features. A threshold was set for selecting the optimal wavelet features based on the coefficient of correlation R obtained via the correlation analysis among the initial wavelet features. The results identified six wavelet features which include (471 nm, scale 4), (696 nm, scale 1), (841 nm, scale 4), (963 nm, scale 3), (1069 nm, scale 3), and (2272 nm, scale 4). A model for identifying Fusarium head blight based on the six wavelet features was then established using Fisher linear discriminant analysis. The model performed well, providing an overall accuracy of 88.7% and a kappa coefficient of 0.775, suggesting that the spectral features obtained using CWA can potentially reflect the infestation of Fusarium head blight in winter wheat ears.

Mapping wildfire vulnerability in Mediterranean Europe. Testing a stepwise approach for operational purposes.

Vulnerability assessment is a vital component of wildfire management. This research focused on the development of a framework to measure and map vulnerability levels in several areas within Mediterranean Europe, where wildfires are a major concern. The framework followed a stepwise approach to evaluate its main components, expressed by exposure, sensitivity and coping capacity. Data on population density, fuel types, protected areas location, roads infrastructure and surveillance activities, among others, were integrated to create composite indices, representing each component and articulated in multiple dimensions. Maps were created for several test areas, in northwest Portugal, southwest Sardinia in Italy and northeast Corsica in France, with the contribution of local participants from civil protection institutions and forest services. Results showed the influence of fuel sensitivity levels, population distribution and protected areas coverage for the overall vulnerability classes. Reasonable levels of accuracy were found on the maps provided through the validation procedure, with an overall match above 72% for the several sites. The systematic and flexible approach applied allowed for adjustments to local circumstances with regards to data availability and fire management procedures, without compromising its consistency and with substantial operational capabilities. The results obtained and the positive feedback of end-users encourage its further application, as a means to improve wildfire management strategies at multiple levels with the latest scientific outputs.

Remote sensing water observation for supporting Lake Victoria weed management.

This paper aims to assess the suitability of remote sensing for enhancing the management of water body resources and for providing an inexpensive way to gather, on a wide area, weed infestation extent and optical parameter linked to the water body status. Remotely sensed satellite images and ancillary ground true data were used to produce land cover maps, trough classification techniques, and water compounds maps, applying radiative transfer models. The study proposed within the framework of the cooperation between Italian Foreign Affair Ministry (through the University of Rome) and Kenyan Authorities has been carried out on the Kenyan part of the Lake Victoria. This lake is one of the largest freshwater bodies of the world where, over the last few years environmental challenges and human impact have perturbed the ecological balance affecting the biodiversity. The objective of this research study is to define the thematic products, retrievable from satellite images, like weed abundance maps and water compound concentrations. These products, if provided with an appropriate time frequency, are useful to identify the preconditions for the occurrence of hazard events like abnormal macrophyte proliferation and to develop an up-to-date decision support system devoted to an apprised territory, environment and resource management.