Application of Fourier Transform Infrared Spectroscopy and Multivariate Analysis Methods for the Non-Destructive Evaluation of Phenolics Compounds in Moringa Powder

This study performed non-destructive measurements of phenolic compounds in moringa powder using Fourier Transform Infrared (FT-IR) spectroscopy within a spectral range of 3500–700 cm−1. Three major phenolic compounds, namely, kaempferol, benzoic acid, and rutin, were measured in five different varie...

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Published in:Agriculture (Basel) 2022-01, Vol.12 (1), p.10
Main Authors: Joshi, Rahul, Sathasivam, Ramaraj, Park, Sang Un, Lee, Hongseok, Kim, Moon S., Baek, Insuck, Cho, Byoung-Kwan
Format: Article
Language:English
Subjects:
Benzoic acid
Chromatography
Conjugation
Correlation coefficient
Correlation coefficients
Fourier analysis
Fourier transform infrared spectroscopy
Fourier transforms
High performance liquid chromatography
Hydrocarbons
Infrared analysis
Infrared spectroscopy
Kaempferol
Least squares method
Linear analysis
Liquid chromatography
moringa powder
Multivariate analysis
Noise
nondestructive measurement
Nondestructive testing
Performance prediction
Phenolic compounds
phenolics compounds
Phenols
Polyphenols
Powder
Prediction models
Radiation
Regression analysis
Regression models
Rutin
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Summary:This study performed non-destructive measurements of phenolic compounds in moringa powder using Fourier Transform Infrared (FT-IR) spectroscopy within a spectral range of 3500–700 cm−1. Three major phenolic compounds, namely, kaempferol, benzoic acid, and rutin, were measured in five different varieties of moringa powder, which was approved with respect to the high-performance liquid chromatography (HPLC) method. The prediction performance of three different regression methods, i.e., partial least squares regression (PLSR), principal component regression (PCR), and net analyte signal (NAS)-based methodology, called hybrid linear analysis (HLA/GO), were compared to achieve the best prediction model. The obtained results for the PLS regression method resulted in better performance for the prediction analysis of phenolic compounds in moringa powder. The PLSR model attained a correlation coefficient (Rp2) value of 0.997 and root mean square error of prediction (RMSEP) of 0.035 mg/g, respectively, which is comparatively higher than the other two regression models. Based on the results, it can be concluded that FT-IR spectroscopy in conjugation with a suitable regression analysis method could be an effective analytical tool for the non-destructive prediction of phenolic compounds in moringa powder.
ISSN:2077-0472
2077-0472
DOI:10.3390/agriculture12010010