Scientific Journal of KubSAU

Barley is one of the important fodder crops. In modern Russia barley is sown throughout the farming areas. The effectiveness of barley cultivation in some years is reduced due to the infestation with helminthosporiosis. Net blotch of barley Drechslera teres is a widespread and highly destructive disease in the world including Russia. In recent years the disease has been progressing in all grain-producing countries. Yield reduction due to the strong development of the blotch can reach up to 45%. Most cultivated barley varieties are susceptible to Drechslera teres. Нelminthosporiosis are characterized by greater variability and rapid adaptation to new varieties of host plants. In order to solve successfully the problem of barley immunity to net blotch it’s necessary to conduct genetics and population studies of the Hordeum vulgare - Drechslera teres pathosystem

Assessment of barley for the blotch incidence is traditionally carried out by visual determination of leaf damage with the help of the available expert – phytopathologist , and with the account scales which allows to characterize a variety for resistance or susceptibility to the studied disease in field conditions. This method has a number of disadvantages that are proposed to be overcome by developing a new tool of a phytopathologist. The measuring tool of a phytopathologist should provide high accuracy of the assessment of plants damage caused by the disease, and the measurement procedure should be quick and easy. The aim of this work is to develop a mobile tool of a phytopathologist for quantitative fast assessment of winter barley leaves damage caused by blotch in field conditions. To achieve this goal the following tasks should be fulfilled. Objective 1: introduce the idea and concept of problem solution; Objective 2: justify the choice of method and solution tool; Objective 3: apply the selected method and tool to solve problems, i.e. to perform the following steps: – cognitive structuring of the subject area; – formalization of the subject area; – synthesis and verification of models; – improvement of the quality of the model and choice of the most reliable model – solving diagnostics problems within the most reliable model (classification, recognition, identification), decision support and research of the simulated subject area by studying its model. Objective 4: describe the effectiveness of the proposed solution. Objective 5: examine the limitations and disadvantages of the proposed solutions of the problem and prospects of its development by overcoming those limitations and disadvantages. The article provides a detailed numerical example of the solution of tasks on real data processed with the ASC- analysis and "Eidos" system