Relationships between host growth dynamics in maize rust pathosystem and spatio-temporal epidemics of Puccinia sorghi Schw. in Hararghe Highlands, Ethiopia

  • Zelalem Bekeko , Bekele Gelena
Keywords: Host growth, Pathosystem, Comparative Epidemiology, Epidemics, Models; Logistic regression, Logistic, Gompertz


An epidemic is the progress of disease in time and space. Each epidemic has a structure whose temporal dynamics and spatial patterns are jointly determined by the pathosystem characteristics and environmental conditions. One of the important objectives in epidemiology is to understand such spatio-temporal dynamics via mathematical and statistical modeling. Maize growth occurs during the course of an epidemic and these changes in maize leaf area may influence the rate at which the disease increases and the shape of the epidemic curve. Thus, erroneous conclusions about the nature of the observed disease progress may be drawn if host growth is disregarded in the analysis of epidemics. This limitation can be overcome by adopting methods of correcting for host growth when calculating the apparent infection rate. Host plant resistance is also an important factor that influences the rate of epidemic development. There are various types and levels of host plant resistance that may vary from small, where the rate of disease increase is slowed but only slightly, to large where incomplete pathogenesis occurs and pathogen reproduction is slowed to a greater extent. The dynamic interaction of the components of an epidemic and their changes over time due to the external variables influencing them can be quantitatively analyzed through modeling. Comparative epidemiology is regarded as an important research tool in which studies across plant disease epidemics are conducted. The aim is to evaluate the differences and similarities between diseases and their hosts, or their relevant attributes and parameters. For example, the influence of environmental factors and human interferences on epidemics may be compared across different climatic conditions or agricultural practices either within the same disease host combination or for multiple disease epidemics. Ultimately, comparative epidemiology is of great importance in developing integrated and sustainable crop protection strategies. In this paper, we outline common methodologies that are used to quantify and model spatio-temporal epidemic dynamics of plant diseases, with emphasis on developing temporal forecast models and on quantifying spatial patterns of common rust of maize. Therefore, the objective of this review article is to elucidate the role of host growth modeling and spatio-temporal epidemics of Puccinia sorghi under Ethiopian condition. This information can be used by plant pathologists and physiologists in designing and modeling the relationship between the effects of the pathogen on maize growth dynamics and the spatio-temporal epidemic progression of the disease before undertaking an ecologically based management strategies against the disease. Hence, it is recommended that modeling maize growth dynamics and the biology of the pathogen helps in easily understanding the nature of epidemic development of the disease on spatial and temporal scales.


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