Response Surface Methodology for Optimization of Multiple Responses of Watermelon using Organic Manure

Abstract

Response Surface Methodology (RSM) is a critical technique in developing new processes, optimizing their performance and improving the design. Field experiment was conducted at horticultural research and teaching farm of Chuka University to evaluate the responses of watermelon to organic manure. The study investigated the use of Central Composite Design (CCD) in formulation of optimal use of organic manure in order to obtain maximum growth and yield of watermelon. The main objective of this study was to optimize the multiple responses of watermelon to organic manure using CCD and RSM. The study was guided by the following specific objectives; to establish the effect of organic manure on growth and yield of watermelon using CCD, determine a three- factor second-order model that best fits the data and find optimal settings on the control variables (poultry manure, cow manure and goat manure) that produce maximum response values on watermelon crop. The parameters assessed to achieve the objective of the study were vine length, number of branches/plant and fruit weight of watermelon. A statistical model of the second-order that best fits the data was used to achieve the objectives. The predicted values were found to be in good agreement with the experimental values which define the propriety of the models and the achievement of CCD in the optimization of multiple responses of watermelon. The results of the study showed that high rate of goat and poultry manure had significance influence on growth and yield of watermelon (fruit weight of 93.73 tonnes per hectare, 9 branches per watermelon plant and vine length of 225.4 cm) at 5% significance level. Based on the finding of this study, it was recommended that farmers in the study area apply 17.64 tons/ha of poultry manure, 11.2 tons/ha of cow manure and 18.1 tons/ha of goat manure for growth and yield of watermelon. Furthermore, in order to create much awareness of RSM on Agricultural settings the study recommends joint development by statisticians and Agriculturalists to reasonably model practical Agricultural research problems using CCD and RSM. Finally, further research may be commissioned with CCD, Box–Behnken and Doehlert design approach to plan the experiments for growth and yield of watermelon with an overall objective of optimizing the responses (such as number of fruits/plant and number of leaves per plant) of watermelon to organic manure (poultry manure, goat manure, rabbit manure and donkey manure). It is anticipated that the findings of the current study will provide necessary information useful to the policy makers, Agriculturalist and stakeholders to enhance growth and yield of watermelon in Kenya.