Rapid Detection of Paprika Adulteration by FT-NIR Spectroscopy
Rapid Detection of Paprika Adulteration by FT-NIR Spectroscopy
Introduction
There is a long history of spice adulteration, which dates back thousands of years. The main incentive behind the adulteration is economic: either reduction of cost or increase in perceived value. Most adulterants are harmless, such as adulteration with products from non-authentic geographic origins. However, some adulterants are deadly. Paprika, as an example, can be adulterated with tomato skins and brick dust, but it can also be adulterated with lead oxide and carcinogenic chemical dyes, such as Sudan I dye. In 1994, Hungarian ground paprika was found to be contaminated with lead oxide, which can easily dissolve in the hydrochloric acid present in our stomach, making it toxic upon ingestion. Several people died in that incident and dozens more were taken ill. In 2005, Sudan I dye was found in Worcestershire sauce contaminated by adulterated chili powder. Sudan I dye is known to be a rodent carcinogen and has been banned as a food additive.
Incidents such as these put the adulteration of food, including spice adulteration, at the top of the list when it comes to food safety concerns. Traditional analytical methods are comparatively expensive and time-consuming. On the other hand, although near-infrared (NIR) spectroscopy is not as sensitive as some other analytical methods, in the case of economic adulteration the concentrations of adulterants are often quite high, and it has the advantages of no sample preparation, high speed, and ease of use. To increase the sensitivity of the NIR method, a patent-pending algorithm has been developed specifically for screening at concentrations as low as 0.01%. In this study, the Advanced-ID algorithm with an FT-NIR spectrometer will be evaluated for paprika adulterated with tomato skin, red brick dust, and Sudan I dye.
Experimental
Materials
Four paprika samples were purchased from local supermarkets: McCormick Paprika, McCormick Gourmet Hot Hungarian Paprika, Morton & Bassett Paprika and Spice Chain Pride of Szeged Hungarian Style Paprika. Sudan I (dye content ≥ 95% ) was purchased from Sigma Aldrich (St. Louis, MO). Red brick was obtained from Home Depot and ground into fine powder in the lab. Tomato was purchased from a local supermarket and its skin was peeled, dried and ground into fine powder. Sudan I dye, red brick dust and ground tomato were added into a paprika sample manufactured by Spice Chain in various concentrations as listed in Table 1.
Sample Measurement
FT-NIR spectra were collected using two QuasIR 3000 spectrometers (Galaxy Scientific, Nashua, NH, USA). Samples were stored in 25 x 95 mm glass vials and then
placed on top of the 23 mm sample window of the integrating sphere. Each sample was measured twice on each instrument, with 4 cm-1 resolution and 200 scans. Samples were shaken between measurements.
Data Processing
Spectral Sage software was used for data collection and the CLS-based Advanced-ID algorithm and software were used for the analysis .
Result and Discussion
For a sample comprising n components, its spectrum S can be modeled as the sum of the spectra of n components K1...Kn, assuming the Beer-Lambert law is obeyed.
where K is the matrix of reference spectra of the sample components, c1...cn are unknown coefficients and R is a residual, or error. The least squares solution to this equation for the coefficients can be found by standard matrix algebra, and is otherwise known as Classical Least Squares (CLS), or K-matrix regression.
If each spectrum contains m data points, then we can write this in matrix notation as :
where S and R are m x 1 matrices, K is an m x n matrix of reference spectra, and c is an n x 1 matrix of coefficients. Often, all of the components represented in K are known to be present and the objective of the regression is to find the coefficients c that can then be used to calculate their relative concentrations. In certain cases, however, one of the components may be an unknown that needs to be identified, or a suspected component whose presence in the mixture needs to be confirmed. If we designate this component as a target component and the spectrum of this component as T (the target spectrum), then for convenience we can rewrite the equation as:
Table 1: Adulterated Paprika Sample Information
Sample Adulterant ID | Adulterant % |
Tomato skin Mix 1 | 10.86 |
Tomato skin Mix 2 | 5.54 |
Tomato skin Mix 3 | 1.23 |
Tomato skin Mix 4 | 0.52 |
Tomato skin Mix 5 | 0.11 |
Brick Dust Mix 1 | 14.12 |
Brick Dust Mix 2 | 4.77 |
Brick Dust Mix 3 | 1.04 |
Brick Dust Mix 4 | 0.68 |
Brick Dust Mix 5 | 0.1 |
Sudan I Mix 1 | 10.32 |
Sudan I Mix 2 | 4.58 |
Sudan I Mix 3 | 0.88 |
Sudan I Mix 4 | 0.62 |
Sudan I Mix 5 | 0.11 |
OUR PORTFOLIO
Explore our new recently completed projects. deserve
