Electrical conductivity prediction system of honey using hyperspectral imaging

Irfan Sriyono Putro, Adhi Harmoko Saputro, Cuk Imawan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This work aims to develop a prediction system based on hyperspectral imaging to measure electrical conductivity value of honey. The reference of electrical conductivity was measured using a conductivity meter (HI 98311, Hanna Instrument, Rhode Island, USA) as an aqueous solution (20 g dry matter in 100 ml distilled water). The data processing consist of image correction, feature extraction, and feature selection, while as the prediction model was built using Partial Least Square Regression (PLSR), Artificial Neural Network (ANN), and Partial Least Square Artificial Neural Network (PLS-ANN). Hyperspectral images from 28 honey samples were captured using visible near-infrared (VIS-NIR) hyperspectral camera (400-1000 nm) in transmittance mode. The performance of the prediction system provided by PLSR is 0.88 (correlation coefficient) and 26.20% (RMSE). The ANN has correlation coefficient and RMSE of 0.93 and 23.12%, respectively. The best performance was the PLS-ANN model which has correlation coefficient of 0.98 and RMSE of 12.65%.

Original languageEnglish
Title of host publication2018 International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages487-491
Number of pages5
ISBN (Electronic)9781538674222
DOIs
Publication statusPublished - Nov 2018
Event2018 International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2018 - Yogyakarta, Indonesia
Duration: 21 Nov 201822 Nov 2018

Publication series

Name2018 International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2018

Conference

Conference2018 International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2018
CountryIndonesia
CityYogyakarta
Period21/11/1822/11/18

Keywords

  • Artificial neural network
  • Electrical conductivity
  • Honey
  • Hyperspectral
  • Partial least square regression

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