Authentic Spices: Method for Identifying the Country of Origin

A spike recovery test was then carried out to check the accuracy of the elemental method for spice sample analysis. Four random spice samples were spiked with all elements at 20 and 60 ppb and measured using ICP-MS and ICP-OES. The quantitative results for the spice samples showed that the concentrations of aluminum, potassium, calcium, magnesium, sodium, iron, phosphorus, sulfur, silicon, zinc, and manganese were relatively high in all four spice samples. The spike results for these elements were therefore invalid as the spike levels were too low (20 times lower) relative to the levels present in the unspiked samples. The recoveries for all remaining elements were within ±20 percent.

Elemental Fingerprinting

All spices were analyzed, and the multi-element data batch file (55 spice samples, nine replicates) was imported into MPP chemometric software for statistical analysis. Principal component analysis (PCA), an unsupervised technique, was used to find the direction of the greatest variance in the elemental data and display the samples based on these differences and similarities. As shown in Figure 1, the spice samples were separated fairly well based on country of origin and by spice.

Overall differences between the elemental composition of spices from the 13 different countries were found. As seen in the PCA (see Figure 1), spice elemental profiles were found to discriminate country of origin and explain 47.22 percent and 11.69 percent of the variance in PCA components 1 and 2, respectively; however, the countries were not completely separated.

We were interested to see if origin could be distinguished when examining one spice. This can be demonstrated in the PCA of rosemary, where clear separation between samples from Morocco and Tunisia is shown (see Figure 2). In addition to discriminating between countries, we saw in Figure 1 that elemental profiles could also distinguish some spices. We further investigated whether spices originating from one country could be separated. The PCA in Figure 3 shows the elemental composition of multiple spices within Egypt and Turkey. Clear separation was seen between four spices from Turkey, and possible spice discrimination was seen in samples from Egypt.

Initial Findings and Future Aspirations

ICP-MS can be used for the quantitative analysis of the widest range of elements in spice samples, producing large data sets for statistical analysis. ICP-OES can also be applied for elemental fingerprinting studies using data for all but the lowest concentration elements.

Exploratory data analysis using PCA showed that the elemental composition of spices is influenced by the country of origin, allowing discrimination between 13 countries. Four different spices from the same country were also separated using the methodology, as was the same spice from two different countries.

More samples are needed to strengthen and test the fingerprinting model to authenticate spices. However, because of current tracking issues, obtaining spices of known origin is challenging. Once established, the method could form a valuable part of a food manufacturing and distribution facilities’ food fraud program—potentially with economic- and health-related benefits for the consumer.

Dr. Nelson, an assistant adjunct professor for viticulture and enology at University of California Davis, is a market development spectroscopy scientist at Agilent Technologies. Reach her at [email protected]. Tanabe is a graduate student of agricultural and environmental chemistry in the Department of Viticulture and Enology at UCD. Gilleland and Whitecotton are application engineers at Agilent Technologies. And Hasty and Anderson work for CEM Corp.

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