Abstract:
The Agriculture sector is the main stay of the Kenyan economic development contributing over 70% of the Gross
Domestic Product (GDP). The sector is faced with numerous challenges leading to frequent and recurrent food shortages.
Declining maize grain yield is one among the major challenges that call for urgent interventions to address the looming food
crisis in the country. Maize play a big role in the Kenyan food security and in most case lack of the same is taken to mean food
insecurity. It is due the importance attached to the crop that a Long Term Agricultural Experiments (LTAE) was set up
specifically to research on the Maize grain yield. Many paper published on the LTAE in the country are only single factors
analysis and lack the application of Response Surface Methodology (RSM) approaches in solving challenges facing the low
and declining maize grain yield ( y 1 ), total microbe population ( y 2 ) a crucial component of Soil Organic Matter (SOM) and
their optimization. The focus of this paper therefore is the application of RSM in maize grain yield and total microbial
population optimization. Specifically, the paper determined the most significant factors for maize grain yield and total
microbial population (bacteria, fungi, actinomycetes, rhizobia), (screening phase of the paper), constructed of an efficient and
appropriate experimental design for evaluating the optimal settings of maize yield and total microbial population count and
determined univariate optimal settings for maize grain yield and total microbial population. The primary data was summarized
from LTAE in National Agricultural Research Laboratories (NARL) in Kabete under the Kenya Agriculture and Livestock
Research Organization (KALRO) and secondary data imputed for experimental points falling outside the set field experimental
design points. Two treatment factors were identified as the most significant treatment factors (Farm Yard Manure (FYM) and
Nitrogen and Phosphorus (NP)) at their low levels and Circumscribed Central Composite Design (CCCD) with two star points
as the most efficient design. CCCD passed most optimal criteria of DAET. Univariately, optimal setting for maize grain yield
was realized at 3.8x10 3 kg/ha and that of the total microbial population at 3.6x10 6 count. The study confirmed that it was
possible to optimize the input treatment factor that lead to the optimization of both maize grain yield and maintaining maximal
total microbial population count at its optimal levels.
