Estimation of the Uncertainties Related to the Measurement of the Size and Quantities of Individual Silver Nanoparticles in Confectionery

Abstract

E174 (silver) is a food additive that may contain silver nanoparticles (AgNP). Validated methods are needed to size and quantify these particles in a regulatory context. However, no validations have yet been performed with food additives or real samples containing food additives requiring a sample preparation step prior to analysis. A single-particle inductively coupled plasma mass spectrometry (spICP-MS) method was developed and validated for sizing and quantifying the fraction of AgNP in E174 and in products containing E174, and associated uncertainties related to sample preparation, analysis and data interpretation were unraveled. The expanded measurement uncertainty for AgNP sizing was calculated to be 16% in E174-containing food products and increased up to 23% in E174 itself. The E174 food additives showed a large silver background concentration combined with a relatively low number of nanoparticles, making data interpretation more challenging than in the products. The standard uncertainties related to sample preparation, analysis, and challenging data interpretation were respectively 4.7%, 6.5%, and 6.0% for triplicate performances. For a single replicate sample, the uncertainty related to sample preparation increased to 6.8%. The expanded measurement uncertainty related to the concentration determination was 25–45% in these complex samples, without a clear distinction between additives and products. Overall, the validation parameters obtained for spICP-MS seem to be fit for the purpose of characterizing AgNP in E174 or E174-containing products.

Physicochemical characterization of nanoparticles in food additives in the context of risk identification

“…To determine the uncertainties associated with the analysis of Ag nanoparticles by spICP-MS, validation studies have been performed on the material NM-300K and on Ag-005 and Ag-009 (pristine materials), Ag-P-003 and Ag-P-004 (E 174 containing products) and a partial revalidation of NM-300K due to a slightly adapted analytical methodology. This is reported in detail by Waegeneers et al (Waegeneers et al, 2019).…”

“…The sample preparation of the food additives in their pristine state and in food products is described in detail by (De Vos et al, 2020;Verleysen et al, in preparation, 2020;Waegeneers et al, 2019). Dispersion protocols including pH optimization based on zeta potential, probe sonication and centrifugation were described in detail in SOPs.…”

Particle size analysis of pristine food-grade titanium dioxide and E 171 in confectionery products: Interlaboratory testing of a single-particle inductively coupled plasma mass spectrometry screening method and confirmation with transmission electron microscopy

“…The heterogeneous content of silver among candies and a non-optimised sample dispersion protocol were identified as the main sources. Moreover, the authors of that study concluded that the non-optimised dispersion protocol did not have an impact on the particles' size distribution, but on the particle concentration ( Waegeneers, De Vos, Verleysen, Ruttens, & Mast, 2019 ). Other possible reasons for a broader distribution of results are discussed in the following paragraphs.…”

Physicochemical Characterization of the Pristine E171 Food Additive by Standardized and Validated Methods

“…No attempt was made to estimate the recovery for the particle number concentration. Repeatability standard deviation (s r ), between-day standard deviation (s d ), and the uncertainty on the bias (u ∆ ) were estimated as explained in [75]. To determine the measurement uncertainty under routine measurement conditions (three replicates analyzed on a single day), the repeatability and between-day variations were divided by respectively the number of replicates and the number of measurement days.…”

“…Optimal de-agglomeration, quantitative information of the particle shape, and calculation of the transport efficiency are critical factors to measure the constituent particle size of E171 materials by spICP-MS accurately. Furthermore, quantitative information on the fraction of particles that is smaller than the spICP-MS quantification limit may improve the reliability of the size distribution as well [75]. Corrections for particle shape and missing particle fractions require a priori input of quantitative EM analysis.…”