The Effect Of Organic And Mineral Fertilizers On Soil Microbial Communities In Kabete Long-Term Experiment, Kenya

ABSTRACT 

Soil micro-organisms play a key role in determining soil quality. Over 70% of small holder farmers in the central high lands of Kenya are using crop manure, animal wastes and mineral fertilizers to increase their farms fertility and subsequent productivity. The dilemma with these practices is that less is known on the impact of these resources on the below ground biodiversity particularly the microbial communities. A field study was conducted at a site in Kabete where a long-term experiment that had been established in 1976 to investigate the effects of various organic and mineral fertilizers on total bacterial communities, fungal communities and denitrifying bacterial community structures. The objectives of this study were to determine the impact of continuous cropping with repeated applications of organic and mineral inputs on soil microbial communities. Denaturing gradient gel electrophoresis (DGGE) molecular technique of polymerase chain reaction-amplified 16S rRNA genes, 28S rRNA genes, nir K rRNA genes and nir S rRNA genes were used. The study comprised of two organic inputs; maize stover (R) all harvest returned to soil and farmyard manure (FYM) applied at 10 t ha-1 with or without 120 kg N, 52.8 kg P (N+P) mineral fertilizer, a virgin land (fallow) that had not been cultivated for the thirty two years and a complete control (C) with neither organic nor mineral fertilizer. Soil samples from the top soil (0-10cm depth) were analyzed for total bacterial, denitrifying bacteria and fungal communities‘ diversity as well as soil pH, carbon (C), nitrogen (N), and nitrates (NO3 - ). DGGE gels were then converted to graphs using the Total lab software and cluster analysis done to assess the similarity of communities between treatments. Shannon weaver index of diversity (H) was used to calculate the various microbial diversities. All data was analyzed with the Anova procedure of the GENSTAT statistical software and treatment means separated using least significant difference at (P