Neural network-based electronic nose for cocoa beans quality assessment

Authors

  • Vincent O Olunloyo University of Lagos
  • Timothy A Ibidapo University of Lagos
  • Rotimi Rufus Dinrifo Lagos State Polytechnic, University of Lagos

Keywords:

cocoa, quality, electronic nose, neural networks, smell, food

Abstract

In this study, a prototype electronic nose was developed for monitoring the quality of cocoa beans.  The system comprises an array of metal-oxide semiconductor sensors and an artificial neural network pattern recognition unit.  The results obtained from assessment experiments on cocoa beans show good agreement with those obtained from the traditional ‘cut test', recording up to 95% accuracy.  This investigation demonstrates that the electronic nose technique holds promise as a successful technique in evaluating the quality of cocoa beans for industrial processing.

Author Biography

Rotimi Rufus Dinrifo, Lagos State Polytechnic, University of Lagos

Rufus Rotimi DINRIFO

R.R Dinrifo B.Tech, M.Sc, PhD; MNIAE, MNSE, MCOAN, Regd Engineer (COREN)

Agricultural /Process Machinery Engineer / Process Automation / Systems Engineer, Food Quality Analyst, Systems Analyst / Computer Programmer,

Published

2012-01-20

Issue

Section

VII-Information Systems