Prediction of soluble solid contents mapping on Averrhoa carambola using hyperspectral imaging

Maisyarah Yuniar Rangkuti, Adhi Harmoko Saputro, Cuk Imawan

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

1 Citation (Scopus)

Abstract

Hyperspectral imaging system has been developed to determine the quality of fruits based on the profile mapping of soluble solid content (SSC) in Averrhoa carambola with combining spectral and spatial analysis. The number of samples used is 278 samples. The proposed system consists of a Specim FX-10 Hyperspectral Camera with spectral range 400-1000 nm, workbench slider, two 150 Watt halogen lamps tungsten and a personal computer supported with the software for control the motor speed and hypercube data acquisition. A push-broom technique is applied to acquire hyperspectral images from all sample in the region of 400-1000 nm. The region of interest (ROI) of each sample is obtained at 30×30 pixels. In this research, all of the samples were analyzed using partial least squares (PLS) and principal component analysis (PCA) to obtain prediction models for SSC mapping on star fruit. The best model is then used to create the distribution mapping of the soluble solids content on the star fruit. The performance of the prediction model was evaluated by observing the correlation coefficient, and root means square error. The prediction model of PLS result provided for correlation coefficient value, and root mean square errors value were 0.98, 0.43 and 0.98, 0.48 for prediction model of PCA, respectively. This research showed that hyperspectral imaging system might be useful to predict and to map soluble solid content of star fruit and suitable in an industrial sorting fruit system.

Original languageEnglish
Title of host publicationProceedings - 2017 International Conference on Sustainable Information Engineering and Technology, SIET 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages414-419
Number of pages6
ISBN (Electronic)9781538621820
DOIs
Publication statusPublished - 27 Feb 2018
Event2017 International Conference on Sustainable Information Engineering and Technology, SIET 2017 - Batu City, Indonesia
Duration: 24 Nov 201725 Nov 2017

Publication series

NameProceedings - 2017 International Conference on Sustainable Information Engineering and Technology, SIET 2017
Volume2018-January

Conference

Conference2017 International Conference on Sustainable Information Engineering and Technology, SIET 2017
CountryIndonesia
CityBatu City
Period24/11/1725/11/17

Keywords

  • Averrhoa carambola
  • hyperspectral imaging
  • image processing
  • partial least squares

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