|Chao, Kuanglin - Kevin Chao|
|DHAKAL, SAGAR - University Of Maryland School Of Medicine|
|Qin, Jianwei - Tony|
|PENG, YANKUN - China Agricultural University|
|HUANG, QING - University Of Science And Technology Of China|
Submitted to: Journal of Food Chemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/20/2020
Publication Date: 5/10/2020
Citation: Chao, K., Dhakal, S., Schmidt, W.F., Qin, J., Kim, M.S., Peng, Y., Huang, Q. 2020. Raman and IR spectroscopic modality for authentication of turmeric powder. Journal of Food Chemistry. 320:126567. https://doi.org/10.1016/j.foodchem.2020.126567.
Interpretive Summary: Food safety requires identification of contamination in an efficient amount of time while avoiding false positive and false negative results. This study used Raman imaging and infrared spectroscopy to detect a chemical contaminant (Sudan Red G) and a botanical additive (white turmeric) in commercial yellow turmeric powder. Through spectral interpretation, we show that combining Raman and infrared spectra can provide a complete diagnostic fingerprint to quantitatively detect Sudan Red and white turmeric adulteration. This approach can improve the detection accuracy and reduce analytical time. With the need for constant improvements in food fraud detection, the method presented in this study can be easily extended to other types of fraud involving other products or matrices which could greatly benefit the food industry and consumers.
Technical Abstract: Deliberate chemical contamination of food powders has become a major food safety concern worldwide. This study used Raman imaging and FT-IR spectroscopy to detect Sudan Red and white turmeric adulteration in turmeric powder. While Sudan Red Raman spectral peaks were identifiable in turmeric-Sudan Red samples, Sudan Red false positive detection was observed in binary Raman images, limiting effective quantitative detection. In addition, white turmeric Raman spectral peaks were unidentifiable in turmeric-white turmeric mixtures. However, IR spectra of turmeric-Sudan Red and turmeric-white turmeric samples provided discrete identifier peaks for both the adulterants. Partial least squares regression models were developed using IR spectra for each mixture type. The models estimated Sudan Red and white turmeric concentrations with correlation coefficients of 0.97 and 0.95, respectively. Priority should be given to developing an IR imaging system and incorporating it with Raman system to simultaneously measure of food samples for detection of adulterants.