Optimization of Groundnuts (Archis hypogeal) Yield through Response Surface Methodology

Kiprotich, Dennis and Muriithi, Dennis K. and Njogu, Martin K. (2024) Optimization of Groundnuts (Archis hypogeal) Yield through Response Surface Methodology. Asian Journal of Probability and Statistics, 26 (10). pp. 95-107. ISSN 2582-0230

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Abstract

Groundnut production faces several constraints, including poor soil fertility, small land sizes, and inappropriate agricultural techniques. The study aimed to optimize groundnut (Archis hypogeal) yield using response surface methodology (RSM). It explored the use of CCD and RSM to determine the optimal application of rabbit, poultry, and sheep manure for maximum yield, a method not previously applied in groundnut production. The study was conducted at the Chuka University Teaching and Training Farm, Kairani. The experimental design was developed using Central Composite Design (CCD), with 20 experimental runs derived from 23 full factorial designs with six axial points and six center points. Data was collected on the weight of the groundnuts yield harvested in each experimental plot measured by use of a weighing scale. Response Surface Methodology techniques was adopted for data analysis in R-statistical software and R studio programing language. The study findings indicated that organic manures had a significant effect (P < 0.05) on the yield of groundnuts crop. The study revealed that application of 13.6097 t ha-1, 10.582 t ha-1 and 11.0814 t ha-1 of poultry, rabbit and sheep manure respectively are the optimum levels that would lead to maximum weight of groundnuts in the study area. The finding of this study could have an economic benefit to farmers in the study area which aligns with broader national goals of poverty reduction, rural development, and economic growth. This study recommended that farmers should adopt organic farming practices to reduce reliance on chemical fertilizers, improve soil health, and contribute to environmental sustainability.

Item Type: Article
Subjects: Open Library Press > Mathematical Science
Depositing User: Unnamed user with email support@openlibrarypress.com
Date Deposited: 14 Oct 2024 09:34
Last Modified: 19 Apr 2025 13:00
URI: http://data.ms4sub.com/id/eprint/2033

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