Term of Award

Fall 2014

Degree Name

Master of Science in Biology (M.S.)

Document Type and Release Option

Thesis (open access)


Department of Biology

Committee Chair

Tiehang Wu

Committee Member 1

Chris Cutler

Committee Member 2

Lissa Leege


Agricultural practices affect soil microbial communities and health through the input of pesticides, herbicides, fertilizers, and cycling of crop rotation. By examining the microbial community structure, we analyzed how microbial species respond to the environment that individual farms create. Early detection of soil borne disease is essential for agricultural success. However, monitoring incidence of disease based on plant growth response to pathogenic inoculation may not reveal the amount of pathogenic DNA in soil. A comparative study of tomato production systems was conducted by analysis of soil microbial community structure from four farms in Southeast Georgia for the years 2012 and 2013, and incidence level of disease and plant growth of tomato plants grown in greenhouse soil were measured. The results indicated that the soil fungal, bacterial, and animal communities were unique to each farm (ANOSIM PSclerotiumrolfsii DNA (P=0.0454 and P=0.0278 respectively) in the inoculated than un-inoculated soil measured by quantitative polymerase chain reaction (Q-PCR). Fluorescent in situ hybridization (FISH) was used as an alternative for visual detection of Sclerotium rolfsii through whole cell hybridization. A higher hybridization signal was detected in soil with high Sclerotium DNA (15.55333 pg/µl) than in soil with low Sclerotium DNA (0.0155 pg/µl). In conclusion, this study suggested that farming management practices have an effect on the microbial community structure and chemical components of agricultural soil and that plant growth in a greenhouse setting was not a clear representation of the amount of pathogenic DNA in the soil. Molecular detection of pathogenic DNA in soil could provide important information on predicting the potential for disease development in agricultural ecosystems.

Key words: Microbial community structure, Q-PCR, FISH, Sclerotium rolfsii, Soil borne disease