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The septoria leaf blotch of wheat in Central Kazakhstan: prognosis, evaluation and monitoring with remotely sensed data


Fungal diseases represent a widely spread natural phenomenon affecting many of wild and domesticated plants. In nature, all plant species forms plant communities of a mixed character, and the spatial pattern of dominant species is usually irregular and spotted. Some species are impregnable to a certain infection, which provides a kind of natural barrier to the infection spread within the natural community. Under the agricultural environment, when the single plant species may occupy a huge area, the species-specific parasite takes a great advantage to develop focal outbreaks and fast spreading of the infection within the area. The concentration of vulnerable plants and the absence of natural barriers within the agricultural areas provokes outbreaks of fungal diseases, that may have highly harmful consequences and result in significant yield losses. One of the purposes of the satellite optical data is an operative, cost-effective diagnostic and, in combination with climatic datasets and crop rotation information, a prognosis of fungal disease appearance and severity. In this paper, we describe the system of prognostic and monitoring measures to control the fungal diseases of wheat in Central Kazakhstan with special attention to septoria leaf blotch. The prognostic procedure provides a map of the probability of septoria leaf blotch appearance. The prognosis takes into consideration the combination of three main variables: the model of ecological niche for Septoria, the presence of wheat residue, and Vegetation Condition Index counted for the late spring (May) of the current year. The new spectral index, introduced in this paper, is the core component of monitoring activity. The index is sensitive to septoria leaf blotch severity at middle to late (stages 8-11, accordingly Feekes growth stages) periods of wheat development. Several other indices (RETA, VSDI, vegetation indices) may be of help in providing information on the spatial unevenness of wheat crops that may indicate the presence of fungal infection.


fungal wheat diseases, remote sensing, monitoring, prognosis



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