College of Agriculture & Natural Resources

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Browsing College of Agriculture & Natural Resources by Subject "Cocoa Swollen Shoot Virus (CSSV)"

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    Mapping Cocoa Swollen Shoot Virus Disease Distribution in Western Region, Ghana
    (2013) Lartey, Lilian Lucy
    Although the cocoa industry is the major backbone of Ghana’s economy, the industry is beset with a lot of problems with the cocoa swollen shoot virus (CSSV) disease being the major one. Available literature suggests that the mealy bug is the main vector which causes the CSSV disease. In addition, environmental factors including; temperature, precipitation, proximity to forest, elevation and aspect also influence the distribution trend of CSSV in the cocoa growing areas. Despite the conscious efforts made to eliminate or reduce CSSV disease, the eradication process of the mealy bug seems to be slow and ineffective. Little has been done on the study of the spatial distribution of CSSV disease with the aim of eradicating or containing the disease in the field. This has led to the fast spread of the CSSV disease from the earliest cocoa fields to new unaffected areas of production with the Western region being a typical example. Moreover where an outbreak may occur next is also not known. This study was therefore undertaken to model the distribution of CSSV disease, to determine the environmental variables and their relationship to the prevalence of CSSV disease, and to model probable sites for reintroduction of CSSV disease for effective management. The spatial distribution of CSSV was identify by the creation of distribution map, through literature research six environmental variables with influence of the prevalence of CSSV were identified. Statistical analysis was performed to select suitable environmental variables with significant influence on CSSV disease, overlay of presence points with environmental layers was executed to determine locations with influence of CSSV disease, and the probable sites for reintroduction of CSSV disease was model using MaXent to determine sites with greatest risk of CSSV infection. The result indicated that, mapping CSSV disease distribution with Geographic Information Systems (GIS) to determine the actual distribution of the CSSV disease is more efficient and reliable than the visual inspection of cocoa trees for manifestation of stem swelling and leaf symptoms of eradicating the disease. An overlay of CSSV presence points with environmental layers to establish the relationship between environmental variables and CSSV occurrence offered the opportunity to determine locations with influence of CSSV. Furthermore modelling the potential risk sites for reintroduction of CSSV with MaXent provide insight into areas of possible disease outbreaks.