Assessments of environmental determinants of the spatial distribution of Enset wilt disease in Yem Special Wereda, Southwest Ethiopia.

Abstract

Enset (Ensete ventricosum Welw. Cheesman) is a perennial crop, cultivated by millions of smallholder farmers in South, Central and Southwestern Ethiopia. However, its production has been endangered by one of the overwhelming Enset bacterial wilt (EXW) disease caused by Xanthomonas campestris pv. musacearum (Xcm). Although EXW has been described in Ethiopia for about five decades, the current disease burden and geographical distribution; and main causing environmental factors are not precisely known. Understanding the geographical distribution and identifying the environmental correlation of the disease distribution is important. Therefore, this study aims to determine the magnitude of Enset bacterial wilt (EXW) and identification of biophysical factors, which affect its spatial distribution using spatial statistical analysis techniques Yem Special Wereda, Southwest Ethiopia. Representative Kebele administrations were selected using purposive sampling method and spatial random sampling method was used to determine the households or enset plots. Data on EXW prevalence and incidence was collected from 135 enset plots found in 11 selected Kebeles. EXW prevalence and incidence were tested for spatial autocorrelation using the global Moran’s I and Getis-Ord G* statistics. The relationship between EXW and predicting environmental variables was modeled using logistic and linear regression analysis. Logistic regression was used to model the relationship between EXW prevalence and response variables, whereas both Ordinary Least Square (OLS) and Generalized Linear Model (GLM) were used to analyze the relationship between EXW incidence and response variables. 95% confidence interval and p-values, 0.05 were considered as significant. In the study area the EXW disease was widely distributed at varied degree of intensity. 135 enset plots assessed, 87 of them were found to be infected by EXW disease. The overall EXW prevalence and incidence rate in the study area was 64.4% and 20.11%, respectively. The highest prevalence was recorded for Kerewa Kebele (8 9%) and lowest for Asher Kebele (29%). The scale of EXW incidence ranges from 0% – 100% at enset plots, and 6.20% – 38.86% at Kebele level. Based on the spatial analysis results, the pattern of EXW prevalence and incidence were clustered and the null hypotheses were rejected. Predicting variables such as relative humidity, altitude, total annual precipitation and silty texture were positively correlated with EXW prevalence and significantly contributed to the model. Relative humidity, total annual precipitation, altitude, silty texture, soil pH and insect vector (leafhopper) were positively correlated with EXW incidence and significantly contributed to the model. Other variables such as agro-ecology, clayey soil textures and soil type were not significant predictors of EXW prevalence and incidence in the study area. Based on the finding, the concerned bodies should provide management options to control the spread of disease, for more vulnerable areas due to environmental factors. Particularly, providing insecticide where leafhopper is found. In addition, it could be concluding that the findings contribute to the growing research on the aetiology of EXW, and provide new starting points for further exploration of EXW aetiology using laboratory studies.