New Validated Method for the Determination of Six Opium Alkaloids in Poppy Seed-Containing Bakery Products by High-Performance Liquid Chromatography-Tandem Mass Spectrometry after Magnetic Solid-Phase Extraction

Bakery products containing poppy seeds are increasingly being commercialized. These seeds may be contaminated with latex from the Papaver somniferum L. plant rich in opium alkaloids (OAs). Therefore, health authorities demand the development of analytical methods to control them. In this study, an efficient and simple method was developed and validated for the first time to analyze six OAs in bakery products by high-performance liquid chromatography-tandem mass spectrometry. For this purpose, a solid-liquid extraction was optimized, and then a magnetic material [magnetite surface-modified with Fe(III) terephthalate, denoted as Fe₃O₄@TPA-Fe] was used for a fast magnetic solid-phase extraction. The method has been validated with adequate recoveries (70-110%) and relative standard deviations (<20%) and without matrix effects. Nine bakery samples (five breadsticks and four sliced bread) were analyzed; breadsticks showed low amounts of OAs, but two sliced bread showed higher amounts of OAs than the new amount (1.5 mg/kg) set by the Commission Regulation (EU) 2021/2142.

Mesostructured Silica-Coated Magnetic Nanoparticles to Extract Six Opium Alkaloids in Poppy Seeds Prior to Ultra-High-Performance Liquid Chromatography-Tandem Mass Spectrometry Analysis

In recent years, health authorities have become increasingly concerned about preventing consumer exposure to opium alkaloids present in Papaver somniferum L. poppy seeds. In this study, a simple, rapid and efficient method has been optimised to determine all main opioids in poppy seeds (morphine, codeine, thebaine, papaverine, noscapine and oripavine) by UHPLC-QqQ-MS/MS. For this purpose, solid-liquid extraction (SLE) of samples was optimised and six magnetic adsorbent materials with a core of Fe3O4 coated with amorphous and mesostructured silica, both functionalised with octadecyl-silane or octyl-silane were characterised and evaluated for magnetic solid-phase extraction (MSPE). The material with the best results was non-functionalised mesostructured silica and, with it, the MSPE procedure was optimised. This method was validated and used to quantify six opioids in 14 edible seed samples (eleven poppy seeds and three seed mixes). Considerable amounts were found (1.5-249.0 mg/kg morphine, <0.2 µg/kg-45.8 mg/kg codeine, <2.4 µg/kg-136.2 mg/kg thebaine, <0.2 µg/kg-27.1 mg/kg papaverine, <0.2 µg/kg-108.7 mg/kg noscapine and <240 µg/kg-33.4 mg/kg oripavine), exceeding maximum limits established in some EU countries and the reference level of morphine in the EU. Furthermore, in some commercial samples for human consumption, inadequate labelling was found because significant amounts of alkaloids were detected even though Papaver rhoeas L. seeds were declared on the product label.

Applications of surface functionalized Fe3O4 NPs-based detection methods in food safety

Food safety has always been an issue of great concern to people. The development of rapid, sensitive and specific detection technology of food pollutants is one of the hot issues in food science field. The rapid development of functionalized Fe₃O₄ nanoparticles (NPs) provides unprecedented opportunities and technical support for the innovation of food safety detection. The surface functionalized Fe₃O₄ NPs, which combine superparamagnetic with nanoscale feature, have become an excellent tool for food quality and safety detection. This review highlights the mechanism, principles, and applications of surface functionalized Fe₃O₄ NPs-based detection technique in the agrifood industry. Then the relevant characteristics, functional roles and general mechanisms of nanomaterial-based detection of various endogenous components and exogenous pollutants in foods are discussed in detail. Ultimately, this review is expected to promote the optimization of functionalized Fe₃O₄ NPs and provide direction for the diversity of signal recognition and the sustainability of detection methods.