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

Abstract

Fungal diseases represent a widely spread natural phenomenon affecting many wild and domesticated plants. In nature, all plant species form 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 spreading within the natural community. Under the agricultural environment, when a 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 provoke 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 tool and, in combination with climatic datasets and crop rotation information, a prognosis of fungal disease appearance and severity. This paper describes the system of prognostic and monitoring measures to control the fungal diseases of wheat in Central Kazakhstan, with particular attention to Septoria leaf blotch. The prognostic procedure provides a map of the probability of septoria leaf blotch appearance. The prognosis considers the combination of three main variables: the model of ecological niche for Septoria, the presence of wheat residue, and the vegetation condition index counted for the late spring (May) of the current year. The novel spectral-based approach introduced in this paper is the core component of monitoring activity. The SLBS-equation appears to have high sensitivity to Septoria leaf blotch severity in the middle to late (stages 8–11, accordingly, Feekes growth stages) periods of wheat development. Several other spectral indices (RETA, VSDI, and vegetation indices) may help provide information on the spatial unevenness of wheat crops that may indicate the presence of fungal infection.