Evaluation of the Most Significant Treatment Factors for Maize Grain Yields and Total Microbial Count in Long Term Agricultural Experiment (LTAE), Kenya

Abstract

Agriculture and its related economic activities form the main livelihood for Kenya population. The sector faces numerous challenges that have led to food insecurity in the country. Maize production plays a significant role in the country’ economic development contributing significantly to the national overall Gross Domestic Product (GDP). Declining maize grain yield is one of the major challenges that require interventions to avert the looming food crisis. To address the challenge various Long Term Agricultural Experiments (LTAE) and studies on soil fertility maintainance options have been developed. However, such studies have explored only single factors at a time with limited application of robust statistical application. Statistical procedures could offer best set of few treatment factors that explain the maize grain yields in LTAEs in Kenya and beyond. The focus of this paper was the application of robust statistical methods in obtaining set of minimum treatment factors that could be used in the determination maize grain yield in LTAE. Specifically, the paper sought to describe the trend in maize grain yield over the experimental period, characterize the input factors for maize grain yield and to determine the most significant treatment factors for maize grain yield and total microbial population count (bacteria, fungi, actinomycetes, rhizobia). The primary data was summarized from LTAE in National Agricultural Research Laboratories (NARL), 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 isolated (Farm Yard Manure (FYM) and Nitrogen and Phosphorus (NP)) at their low factor levels as the most significant treatment factor in maximizing the maize grain yield and total microbial population count. It was possible to select a minimum set of treatment factors in LTAE that are critical in predicting the maize grain yield.