No abstract

No abstract

A collaborative trial was conducted to determine the performance characteristics of an analytical method for the quantification of inorganic arsenic (iAs) in food. The method is based on (i) solubilisation of the protein matrix with concentrated hydrochloric acid to denature proteins and allow the release of all arsenic species into solution, and (ii) subsequent extraction of the inorganic arsenic present in the acid medium using chloroform followed by back-extraction to acidic medium. The final detection and quantification is done by flow injection hydride generation atomic absorption spectrometry (FI-HG-AAS). The seven test items used in this exercise were reference materials covering a broad range of matrices: mussels, cabbage, seaweed (hijiki), fish protein, rice, wheat, mushrooms, with concentrations ranging from 0.074 to 7.55mgkg(-1). The relative standard deviation for repeatability (RSDr) ranged from 4.1 to 10.3%, while the relative standard deviation for reproducibility (RSDR) ranged from 6.1 to 22.8%.

This review provides an overview of the information currently available about the presence of semicarbazide (SEM) in food. Likely sources of SEM in food matrices are summarised and discussed. Detailed information is given about the analytical methods used to determine SEM; features and drawbacks associated with them are carefully evaluated. Performance criteria characterising the analytical methods discussed are also given.

Two of the core tasks of the European Union Reference Laboratory for Heavy Metals in Feed and Food (EU-RL-HM) are to provide advice to the Directorate General for Health and Consumers (DG SANCO) on scientific matters and to organise proficiency tests among appointed National Reference Laboratories. This article presents the results of the 12th proficiency test organised by the EU-RL-HM (IMEP-112) that focused on the determination of total and inorganic arsenic in wheat, vegetable food and algae. The test items used in this exercise were: wheat sampled in a field with a high concentration of arsenic in the soil, spinach (SRM 1570a from NIST) and an algae candidate reference material. Participation in this exercise was open to laboratories from all around the world to be able to judge the state of the art of the determination of total and, more in particular, inorganic arsenic in several food commodities. Seventy-four laboratories from 31 countries registered to the exercise; 30 of them were European National Reference Laboratories. The assigned values for IMEP-112 were provided by a group of seven laboratories expert in the field of arsenic speciation analysis in food. Laboratory results were rated with z and ζ scores (zeta scores) in accordance with ISO 13528. Around 85 % of the participants performed satisfactorily for inorganic arsenic in vegetable food and 60 % did for inorganic arsenic in wheat, but only 20 % of the laboratories taking part in the exercise were able to report satisfactory results in the algae test material.

The Institute for Reference Materials and Measurements (IRMM) of the Joint Research Centre (JRC), a Directorate General of the European Commission, operates the International Measurement Evaluation Program (IMEP). IMEP organises inter-laboratory comparisons in support of European Union policies. This paper presents the results of two proficiency tests (PTs): IMEP-116 and IMEP-39, organised for the determination of total Cd, Pb, As, Hg and inorganic As (iAs) in mushrooms. Participation in IMEP-116 was restricted to National Reference Laboratories (NRLs) officially appointed by national authorities in European Union member states. IMEP-39 was open to all other laboratories wishing to participate. Thirty-seven participants from 25 countries reported results in IMEP-116, and 62 laboratories from 36 countries reported for the IMEP-39 study. Both PTs were organised in support to Regulation (EC) No. 1881/2006, which sets the maximum levels for certain contaminants in food. The test item used in both PTs was a blend of mushrooms of the variety shiitake (Lentinula edodes). Five laboratories, with demonstrated measurement capability in the field, provided results to establish the assigned values (X ref). The standard uncertainties associated to the assigned values (u ref) were calculated by combining the uncertainty of the characterisation (u char) with a contribution for homogeneity (u bb) and for stability (u st), whilst u char was calculated following ISO 13528. Laboratory results were rated with z- and zeta (ζ)-scores in accordance with ISO 13528. The standard deviation for proficiency assessment, σ p, ranged from 10% to 20% depending on the analyte. The percentage of satisfactory z-scores ranged from 81% (iAs) to 97% (total Cd) in IMEP-116 and from 64% (iAs) to 84% (total Hg) in IMEP-39.

Highlights ED-XRF, an attractive technique for screening purposes in honey control. ED-XRF allows verification of botanical/geographical origin of Spanish PDO honeys. Multivariate analysis of elemental profiles, fundamental to classify honey samples.

Financial gain is a main driver for committing food fraud and replacement of ingredients with cheaper alternatives is an easy way to do it. Coconut sugar is becoming popular as an alternative to beetroot or cane sugar due to its high mineral content and lower glycaemic index. As its market price is about twice as high as that of conventional sugar, coconut sugar may become target to fraudulent manipulation. The present work explores the feasibility of using energy-dispersive X-ray fluorescence as a screening tool to verify its authenticity. Mass fractions of P, Cl, S, K, Ca, Fe, Cu, Br, Rb, and Sr determined in eleven coconut, ten cane, and one beetroot sugar samples, purchased in Belgian, Spanish, Polish, and Italian supermarkets were used for discriminating the different sugars. On average, the mass fractions of all the mentioned elements were higher in coconut than in cane and beetroot sugars. Multivariate analysis of the elemental fingerprint by Soft Independent Modelling of Class Analogies was used for authentication purposes. Models constructed were characterised by zero false positives; three coconut sugars (27%) could not be classified as such, neither as cane sugars.