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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Environmental Microbial & Food Safety Laboratory » Research » Publications at this Location » Publication #392550

Research Project: Advancement of Sensing Technologies for Food Safety and Security Applications

Location: Environmental Microbial & Food Safety Laboratory

Title: Comparative determination of phenolic compounds in Ara-bidopsis Thaliana leaf powder under distinct stress conditions using Fourier-Transform Infrared (FT-IR) and Near-Infrared (FT-NIR) Spectroscopy

item JOSHI, RAHUL - Chungnam National University
item SATHASIVAM, RAMARAJ - Chungnam National University
item KUMAR, PRAVEEN - Chungnam National University
item PATEL, AJAY - Chungnam National University
item NGUYEN, BAO - Chungnam National University
item FAQEERZAADA, MOHAMMAD - Chungnam National University
item PARK, SANGUN - Chungnam National University
item LEE, SUNGHYUN - Chungnam National University
item Kim, Moon
item BAEK, INSUCK - Orise Fellow
item CHO, BYOUNG-KWAN - Chungnam National University

Submitted to: Plants
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/19/2022
Publication Date: 3/22/2022
Citation: Joshi, R., Sathasivam, R., Kumar, P., Patel, A.K., Nguyen, B.V., Faqeerzaada, M.A., Park, S., Lee, S., Kim, M.S., Baek, I., Cho, B. 2022. Comparative determination of phenolic compounds in Ara-bidopsis Thaliana leaf powder under distinct stress conditions using Fourier-Transform Infrared (FT-IR) and Near-Infrared (FT-NIR) Spectroscopy. Plants. 11(7):836.

Interpretive Summary: A variety of plants cultivated worldwide are valued for their bioactive chemical compounds and processed into powder form for food and medicinal use. Specific compounds of interest, such as phenolic compounds, can be measured in plant powders very precisely and efficiently via established laboratory methods such as high-performance liquid chromatography, gas chromatography, or gas chromatography with mass spectrometry. However, these time-consuming and sample-destructive techniques require expertise to perform and are poorly suited for rapid compound detection in real-time processing applications. Alternative methods are needed. This study compares Fourier Transform infrared spectroscopy (FT-IR) and Fourier Transform near-infrared spectroscopy (FT-NIR) for non-destructive, quantitative evaluation of phenolic compounds in powdered Arabidposis thaliana prepared from the leaves of plants grown in growth chamber conditions simulating drought stress, which is known to influence phenolics content. The results showed that although both methods used with multivariate data analysis techniques could predict phenolics content with high accuracy, but FT-NIR performed better and thus appears to be more suitable for food processors to use for rapid analysis of leaf powders for phenolic content.

Technical Abstract: The increasing interest in plant phenolic compounds in the past few years has become necessary because of their several important physicochemical properties. Thus their identification through non-destructive methods has become crucial. This study carried out comparative non-destructive measurements of Arabidopsis thaliana leaf powder samples phenolic compounds using Fourier-transform infrared and near-infrared spectroscopic techniques under six distinct stress conditions. The prediction analysis of 600 leaf powder samples under six different stress conditions was performed using PLSR, PCR, and NAS-based HLA/GO regression analysis methods. The results obtained through FT-NIR spectroscopy yielded the highest correlation coefficient (R_p^2) value of 0.999, with a minimum error (RMSEP) value of 0.003 mg/g, based on the PLSR model using the MSC preprocessing method, which was slightly better than the correlation coefficient (R_p^2) value of 0.980 with an error (RMSEP) value of 0.055 mg/g for FT-IR spectroscopy. Additionally, beta coefficient plots present spectral differences and the identification of important spectral signatures sensitive to the phenolic compounds in measured powdered samples. Thus, the obtained results demonstrated that FT-NIR spectroscopy combined with partial least squares regression (PLSR) has a solid potential for non-destructively predicting phenolic compounds in Arabidopsis thaliana leaf powder samples.