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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 #362706

Research Project: Sensing Technologies for the Detection and Characterization of Microbial, Chemical, and Biological Contaminants in Foods

Location: Environmental Microbial & Food Safety Laboratory

Title: Detection of additives and chemical contaminants in turmeric powder using FT-IR spectroscopy

Author
item DHAKAL, SAGAR - University Of Maryland School Of Medicine
item Schmidt, Walter
item Kim, Moon
item TANG, XIUYING - China Agricultural University
item PENG, YANKUN - China Agricultural University
item Chao, Kuanglin - Kevin Chao

Submitted to: Foods
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/19/2019
Publication Date: 4/24/2019
Citation: Dhakal, S., Schmidt, W.F., Kim, M.S., Tang, X., Peng, Y., Chao, K. 2019. Detection of additives and chemical contaminants in turmeric powder using FT-IR spectroscopy. Foods. 8(5):143.

Interpretive Summary: Turmeric ranked number four among popularly sold plant products in the United States in 2016. With its strong commercial popularity, incidences of turmeric adulteration by different botanical products and chemical dyes have increased. Different analytical methods have been applied for the detection of additives and chemical contaminants in yellow turmeric and other spice powders. Although these methods could identify contaminants, and classify pure/adulterated spice powders with high accuracy, the studies did not develop quantitative models to estimate contaminant concentrations. This study used optical sensing technology to identify and quantify a chemical contaminant (Sudan Red G) and a botanical additive (white turmeric) in commercial yellow turmeric powder. A mathematical model for each yellow turmeric—Sudan Red and yellow turmeric—white turmeric sample was developed to estimate the adulterant concentrations. The result shows that the model can estimate the concentration of Sudan Red in yellow turmeric with an accuracy of 97%. Similarly, the model estimated the concentration of white turmeric with an accuracy of 92%. Both the models show high accuracy indicating the optical sensing technique combined with statistical modeling can be used for qualitative and quantitative detection of botanical additives and chemical contaminants in turmeric and for confirming product identification in regulatory food safety concerns.

Technical Abstract: Yellow turmeric (Curcuma longa) is widely used for culinary and medicinal purposes, and as a dietary supplement. Due to the commercial popularity of C. longa, economic adulteration and contamination with botanical additives and chemical substances has increased. This study used FT-IR spectroscopy for the identification and estimation of white turmeric (Curcuma zedoaria), and Sudan Red G dye mixed with yellow turmeric powder. Fifty replicates of yellow turmeric—Sudan Red mixed samples (1, 5, 10, 15, 20, 25% Sudan Red, w/w) and fifty replicates of yellow turmeric—white turmeric mixed samples (1, 10, 20, 30, 40, 50% white turmeric, w/w) were prepared. The IR spectra of the pure compounds and mixtures were analyzed. The Sudan Red peak at 748 wavenumber and the white turmeric peak at 1078 wavenumber were used as spectral fingerprints. A partial least square regression (PLSR) model was developed for each mixture type to estimate adulteration concentrations. The coefficient of determination (R) for the Sudan Red mixture model was 0.97 with root mean square error of prediction (RMSEP) = 1.3%. R and RMSEP for the white turmeric model were 0.92 and 5.5%, respectively. Our results indicate that the method developed in this study can be used to identify and quantify yellow turmeric powder adulteration.