PERTANIKA JOURNAL OF TROPICAL AGRICULTURAL SCIENCE

 

e-ISSN 2231-8542
ISSN 1511-3701

Home / Regular Issue / JTAS Vol. 31 (2) Mar. 2023 / JST-3531-2022

 

Visible-Near-Infrared Spectroscopy and Chemometrics for Authentication Detection of Organic Soybean Flour

Rudiati Evi Masithoh, Muhammad Fahri Reza Pahlawan, Devi Alicia Surya Saputri and Farid Rakhmat Abadi

Pertanika Journal of Tropical Agricultural Science, Volume 31, Issue 2, March 2023

DOI: https://doi.org/10.47836/pjst.31.2.03

Keywords: Authentication, PCA, PCA-LDA, PLS-DA, PLSR, soybean flour, Vis-NIR

Published on: 20 March 2023

Organic and non-organic soybean flours, although visually indifferent, have a significant difference in price and nutrition content. Therefore, the accurate authentication detection of organic soybean flour is necessary. Visible-near-infrared (Vis-NIR) spectroscopy coupled with chemometric methods is a non-destructive technique applied to detect authentic or adulterated organic soybean flour. The spectra of organic, adulterated organic, and non-organic soybean flours were captured using a Vis-NIR spectrometer at 350–1000 nm. The spectra were analyzed using partial least squares (PLS), principal component analysis (PCA), and the combination of these two with discriminant analysis (DA). The results showed that PCA using PC1 and PC2 could differentiate organic and non-organic soybean flours, whereas PC1 and PC4 can detect pure and adulterated organic soybean flours. The PCA–linear DA models showed 98.5% accuracy (Acc) for predicting pure organic and adulterated soybean flours and 100% Acc for predicting organic and non-organic flours. Moreover, PLS regression models resulted in a high R² of >95% for predicting organic and non-organic flours and pure and adulterated soybean flours. In addition, the PLS-DA models can differentiate organic from non-organic soybean flour and distinguish pure and adulterated soybean flours with 100% Acc and reliability.

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