Njume, Akeme Cyril
Unknown Affiliation

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

Performance Comparison of Two Portable Near-infrared Devices for Rapid Authentication of Aceh Aromatic Rice ‘Sigupai’ Widodo, Slamet; Masyitah, Masyitah; Purwanto, Yohanes Aris; Njume, Akeme Cyril
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 13 No. 3 (2024): September 2024
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v13i3.851-862

Abstract

Sigupai rice, Indonesia local aromatic rice varieties grown in South-West region of Aceh, is highly valued for its fragrance and quality, making it susceptible to adulteration. This study compares the performance of two portable Near-infrared (NIR) devices, SCiO and NeoSpectra, for rapid authentication of Sigupai rice. We evaluated 86 samples for qualitative analysis (i.e. authentic vs adulterated rice) and 44 samples for quantitative analysis (i.e. the level of adulteration). For the qualitative analysis using partial least squares-discriminant analysis (PLS-DA), the best estimation model could differentiate authentic and adulterated samples with an accuracy, sensitivity, specificity, and false positive rates of 89.29%, 92.86%, 85.71% and 14.29% for the NeoSpectra and 97.44%, 100%, 94.87%, and 5.13% for the SCiO, respectively at the validation stage. For quantitative analysis using partial least squares-regression (PLS-R), the best estimation model could estimate the level of adulteration with a coefficient of determination (R²), RMSEP, RPD, and consistency values of 0.92, 1.50%, 5.93 and 100.69% for the NeoSpectra and 0.96, 1.31%, 6.83 and 104.78% for the SCiO. Both portable NIR devices could be used as a rapid analysis tool for the authenticity of Sigupai rice with high accuracy. However, in this study the SCiO device showed a better performance. Keywords: Portable NIR device, Authentication, Aromatic rice, Rapid analysis, Sigupai variety.