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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 #310150
Title: Detection of starch adulteration in onion powder by FT-NIR and FT-IR spectroscopy

Author
item LOHUMI, SANTOSH - Chungnam National University
item LEE, SNAGDAE - Chungnam National University
item LEE, WANG-HEE - Chungnam National University
item Kim, Moon
item MO, CHANGYEUN - Rural Development Administration - Korea
item BAE, HANHONG - Yeungnam University
item CHO, BYOUNG-KWAN - Chungnam National University

Submitted to: Journal of Agricultural and Food Chemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/1/2014
Publication Date: 9/24/2014
Citation: Lohumi, S., Lee, S., Lee, W., Kim, M.S., Mo, C., Bae, H., Cho, B. 2014. Detection of starch adulteration in onion powder by FT-NIR and FT-IR spectroscopy. Journal of Agricultural and Food Chemistry. 62:9246-9251.

Interpretive Summary: Spectroscopic technologies have been used to assess quality attributes of various agricultural products, including the intentional adulteration of foods or food ingredients . In this study, adulteration of onion powder with cornstarch was identified by Fourier transform near-infrared (FT-NIR) and Fourier transform infrared (FT-IR) spectroscopy. The reflectance spectra of 180 pure and adulterated samples of onion powder were analyzed to develop models to predict the presence of cornstarch. The FT-NIR data were of greater predictive value (98% accuracy) than the FT-IR data (90% accuracy). These fourier transform spectroscopy methods can be applied to rapidly detect adulteration in other spices. This investigation provides insightful information to food technologists and agricultural engineers who are developing nondestructive technologies for authentication of food materials.

Technical Abstract: Adulteration of onion powder with cornstarch was identified by Fourier transform near-infrared (FT-NIR) and Fourier transform infrared (FT-IR) spectroscopy. The reflectance spectra of 180 pure and adulterated samples (1–35 wt% starch) were collected and preprocessed to generate calibration and prediction sets. A multivariate calibration model of partial least-squares regression (PLSR) was executed on the pretreated spectra to predict the presence of starch. The PLSR model predicted adulteration with an R2 of 0.98 and a standard error of prediction (SEP) of 1.18% for the FT-NIR data, and an R2 of 0.90 and SEP of 3.12% for the FT-IR data. Thus the FT-NIR data were of greater predictive value than the FT-IR data. Principal component analysis on the preprocessed data identified the onion powder in terms of added starch. The first three principal component loadings and beta coefficients of the PLSR model revealed starch-related absorption. These methods can be applied to rapidly detect adulteration in other spices.