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ARS Home » Plains Area » Manhattan, Kansas » Center for Grain and Animal Health Research » Stored Product Insect and Engineering Research » Research » Publications at this Location » Publication #370570
Research Project: Impacting Quality through Preservation, Enhancement, and Measurement of Grain and Plant Traits

Location: Stored Product Insect and Engineering Research

Title: Rapid differentiation of commercially-available soy sauces using near-infrared spectroscopy

Author
item ROSALES, JERIC - University Of The Philippines Los Banos
item YAPTENCO, KEVIN - University Of The Philippines Los Banos
item AGUILA, MAE JOANNE - University Of The Philippines Los Banos
item Armstrong, Paul

Submitted to: Philippine Journal of Agricultural and Biosystems Engineering
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/4/2019
Publication Date: 12/15/2019
Citation: Rosales, J.H., Yaptenco, K.F., Aguila, M.B., Armstrong, P.R. 2019. Rapid differentiation of commercially-available soy sauces using near-infrared spectroscopy. Philippine Journal of Agricultural and Biosystems Engineering. 15(2):3-12.

Interpretive Summary: Near-infrared (NIR) spectroscopy was used to differentiate between four leading brands of soy sauce available in the Philippines. These local brands included Datu Puti (DP), Marca Piña (MP), and Silver Swan (SS). A naturally-brewed imported brand, Kikkoman (KK), was also used for comparison. This work was done to develop a rapid method to determine authenticity and quality consistency of the different brands commonly available. NIR spectroscopy was used by shining light through a small sample of the soy sauce and measuring light absorbance on the other side. The absorbance spectra collected were then used to build mathematical models that would discriminate between the different types of soy sauce. Results show that 100% of the DP, KK and MP types were identified correctly but the SS soy sauce was confused as being either DP or MP soy sauce. Misclassification of the SS brand may indicate some variance in manufacturing process.

Technical Abstract: Near-infrared (NIR) spectroscopy was used to differentiate between four leading brands of soy sauce in the Philippines; the local brands included Datu Puti (DP), Marca Piña (MP), and Silver Swan (SS). A naturally-brewed imported brand, Kikkoman (KK), was used for comparison. Spectral data of soy sauce samples were acquired in absorbance mode from 900 nm to 1700 nm. First– (1D) and second– (2D) derivative transforms of preprocessed spectral data were analysed by a combination of principal component analysis (PCA) – linear discriminant analysis (LDA), and by partial least squares regression (PLSR). Spectral data with no derivative (ND) transformation was analysed for comparison. Preprocessing methods included mean scatter correction (MSC), Savitzky-Golay (SG) smoothing, and standard normal variate (SNV); these were used in different combinations to determine the best treatment. PCA-LDA results showed that the MSC-SG-ND treatment gave the best result overall with 97.6% of samples classified correctly, and 96.9% of variability explained by two principal components. For PLSR, data preprocessed using SNV-SG-2D transformation gave the best results after cross-validation, with a 9-factor model with root mean square error (RMSE) and coefficient of determination (R2) of 0.114 and 0.989, respectively. Using an independent set of soy sauce samples, the PLSR model was able to correctly identify 100% of DP, KK and MP; however, all SS samples were misclassified as DP or MP. This underscores the need for extensive sampling to build up a spectral library of soy sauce from different brands and sources; this will enable rapid testing of products for authenticity, quality and safety.