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Volume 13
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10.3390/foods13233783
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Food Authentication Goes Green: Method Optimization for Origin Discrimination of Apples Using Apple Juice and ICP-MS

by
Marie-Sophie Müller
1,
Marie Oest
1,
Sandra Scheffler
1,
Anna Lena Horns
2,
Nele Paasch
2,
René Bachmann
2 and
Markus Fischer
1,*
1
Hamburg School of Food Science, Institute of Food Chemistry, University of Hamburg, Grindelallee 117, 20146 Hamburg, Germany
2
Landeslabor Schleswig-Holstein, Max-Eyth-Straße 5, 22437 Neumünster, Germany
*
Author to whom correspondence should be addressed.
Foods 2024, 13(23), 3783; https://doi.org/10.3390/foods13233783
Submission received: 17 October 2024 / Revised: 18 November 2024 / Accepted: 20 November 2024 / Published: 25 November 2024
(This article belongs to the Section Food Analytical Methods)
Versions Notes

Abstract

Apples are among the most important fruits worldwide and the most consumed fruit in Germany. Due to higher energy and personnel costs, domestic apples are more expensive and thus offer an incentive for mixing with foreign goods. Moreover, imported apples have a higher carbon footprint, which is an obstacle regarding sales in times of climate change. Not only the transport of the goods but also the analysis influences the carbon footprint. Inductively coupled plasma mass spectrometry (ICP-MS) is a powerful tool for origin discrimination. In this study, 85 apple juice samples were analyzed, whereby sample preparation for ICP-MS was optimized by eliminating the freeze-drying step and thereby reducing CO2 emissions. The CO2 emission was lowered by around 97%. The optimized method was applied to 272 apple juice samples from seven countries to create models for origin determination. The differentiation of European and non-European apples provided an accuracy of 90.9% ± 2.4%. German samples can be differentiated from other countries with an accuracy of 83.2% ± 1.4%. The regional differentiation of German samples (north vs. south) achieved an accuracy of 92.3% ± 5.4%. The results show that the optimized ICP-MS method, in which freeze-drying is not required is well suited for determining the origin of apples from apple juice.
Keywords: apples; apple juice; element profiling; food authentication; inductively coupled plasma mass spectrometry; chemometrics apples; apple juice; element profiling; food authentication; inductively coupled plasma mass spectrometry; chemometrics

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MDPI and ACS Style

Müller, M.-S.; Oest, M.; Scheffler, S.; Horns, A.L.; Paasch, N.; Bachmann, R.; Fischer, M. Food Authentication Goes Green: Method Optimization for Origin Discrimination of Apples Using Apple Juice and ICP-MS. Foods 2024, 13, 3783. https://doi.org/10.3390/foods13233783

AMA Style

Müller M-S, Oest M, Scheffler S, Horns AL, Paasch N, Bachmann R, Fischer M. Food Authentication Goes Green: Method Optimization for Origin Discrimination of Apples Using Apple Juice and ICP-MS. Foods. 2024; 13(23):3783. https://doi.org/10.3390/foods13233783

Chicago/Turabian Style

Müller, Marie-Sophie, Marie Oest, Sandra Scheffler, Anna Lena Horns, Nele Paasch, René Bachmann, and Markus Fischer. 2024. "Food Authentication Goes Green: Method Optimization for Origin Discrimination of Apples Using Apple Juice and ICP-MS" Foods 13, no. 23: 3783. https://doi.org/10.3390/foods13233783

APA Style

Müller, M. -S., Oest, M., Scheffler, S., Horns, A. L., Paasch, N., Bachmann, R., & Fischer, M. (2024). Food Authentication Goes Green: Method Optimization for Origin Discrimination of Apples Using Apple Juice and ICP-MS. Foods, 13(23), 3783. https://doi.org/10.3390/foods13233783

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