Development of an Oil Extraction Machine for Jatropha curcas Seeds

Salawu, A. T. and Isiaka, M. and Suleiman, M. L. (2015) Development of an Oil Extraction Machine for Jatropha curcas Seeds. Journal of Scientific Research and Reports, 6 (4). pp. 313-328. ISSN 23200227

[thumbnail of Salawu642014JSRR15148.pdf] Text
Salawu642014JSRR15148.pdf - Published Version

Download (566kB)

Abstract

Aim: This study aimed to solve one of the problems which Jatropha curcas seeds (JCS) oil extraction industry is facing in the Northern part of Nigeria; the lack of efficient small scale oil extraction machines. A small scale JCS oil extraction machine was therefore designed, developed, and evaluated for performance.
Study Design: The study was conducted using 3 × 3 × 3 Factorial Experimental Design. The results obtained were analysed using ANOVA while Least Significant Difference (LSD) test was used to separate the means.
Place and Duration of Study: Department of Agricultural Engineering, Ahmadu Bello University, Zaria, Nigeria between January 2011 and April 2013.
Methodology: Base on design calculations, locally sourced materials with indigenous technology were used for the development of the machine. In evaluating the developed prototype machine, the effect of speed, feed-rate, and moisture content on throughput, extraction rate, and extraction efficiency were determined.
Results: The throughput, extraction rate and extraction efficiency of the machine were in the range of 27.86 to 54.96 kg/hr, 4.45 to 9.42 L/hr, and 27.86 to 65.17%, respectively. The best throughput, extraction rate and extraction efficiency of the machine were obtained at 40 rpm with a feed-rate of 48 kg/hr and moisture content of 7.0% on dry basis (db). The average throughput, extraction rate and extraction efficiency of the machine were 32.67 kg/hr, 7.76 L/hr, and 62.22%, respectively.
Conclusion: The seed-machine factors suggest that the machine should be operated at a speed of 40 rpm, feed-rate of 48 kg/hr and moisture content of 7.0% db to enhance its best performance.

Item Type: Article
Subjects: OA STM Library > Multidisciplinary
Depositing User: Unnamed user with email support@oastmlibrary.com
Date Deposited: 15 Jul 2023 07:07
Last Modified: 13 Sep 2024 07:35
URI: http://geographical.openscholararchive.com/id/eprint/1014

Actions (login required)

View Item
View Item