CVD grown carbon nanofibers: an efficient DSPE sorbent for cleanup of multi-class pesticide residue in high fat and low water commodities by QuEChERS using GC-ECD

Simple and rapid ionic liquid-based one-, two-, three-phase transition microextraction for efficient extraction of trace organic pollutants and elimination of lipid co-extractives from fatty food matrices

Extraction of trace contaminants from fatty food matrices is challenging in food analysis. Herein, a new ionic liquid-based one-, two-, three-phase transition microextraction (IL-OTTPTME) was proposed to efficiently extract trace targets while simultaneously eliminating lipid co-extractives. The method performance was illustrated through the determination of chrysoidine in fatty soybean products using high-performance liquid chromatography-ultraviolet/visible detection. The strong interactions and infinite contact between IL and chrysoidine in the one-phase system ensured ultra-high extraction efficiency (∼100 %). Density functional theoretical calculations confirmed the presence of strong hydrogen bonding and π-π interactions. The formation of the three-phase system during extraction could completely eliminate lipid co-extractives. The IL-OTTPTME integrated extraction, enrichment and cleanup steps into one step, making it rapid and extremely easy to operate. The method had a wide linear range of 0.5-5000 μg/kg and low limit of detection (0.15 μg/kg). It also had satisfactory relative recoveries (95.1 %-104.0 %) and low RSDs (≤5.0 %, n = 5).

A Novel and Highly Efficient Microextraction Method for the Determination of Aflatoxin Precursor Averantin in Fatty Grain Samples

Averantin (AVN) is an important aflatoxin biosynthetic precursor and has been listed in the screening range of mycotoxins. Herein, a novel ionic liquid-based one-, two-, and three-phase transition microextraction (IL-OTTPTME) method was combined with high-performance liquid chromatography for the extraction and determination of AVN in fatty grain samples. The formation of a homogeneous solution and three-phase system during the IL-OTTPTME process allowed both efficient extraction and coextracted lipid cleanup. Density functional theory calculations and distribution coefficient determination results demonstrated that AVN extraction by IL mainly occurred through hydrogen-bond and π-π interactions. Under optimized conditions, the LOD and LOQ of the proposed method were 0.5 and 1.5 ng/g, respectively. Finally, the method was used to determine AVN in several grains with different fat contents, achieving satisfactory relative recoveries (86.0-107.8%) and RSDs (1.2-6.2%, n = 3).

A fast multi-residue analysis of twenty-four classes of pesticide in sesame (Sesamum indicum L.) and their migration into processed products

Sesame is widely used as a nutritional supplement or condiment because of its nutritious properties and palatable flavor. However, the extensive use of pesticides in sesame fields has paradoxically decreased the nutritional vantage. The current study used QuEChERS with a low-temperature freezing method to develop a multi-residue analytical approach to detect target analytes (pesticides) in sesame seed, sesame oil, sesame paste, and sesame meal. The migration ability of target pesticides during oil processing was investigated using HPLC-MS/MS and GC-MS: 35% of pesticides decreased, with processing factors (PFs) lower than 0.98, whereas 65% migrated from the seed to the oil during processing. The migration success of methoxyfenozide was the highest, while clothianidin and pymetrozine demonstrated a significantly lower rate of transfer. The results provide insight into the types of pesticides that should be used in farming practices of sesame to decrease the impact on human health.

Carbon nanomaterials for the detection of pesticide residues in food: A review

In agricultural fields, pesticides are widely used, but their residual presence in the environment poses a threat to humans, animals, insects, and ecosystems. The overuse of pesticides for pest control, enhancement of crop yield, etc. leaves behind a significant residual amount in the environment. Various robust, reliable, and reusable methods using a wide class of composites have been developed for the monitoring and controlling of pesticides. Researchers have discovered that carbon nanomaterials have a wide range of characteristics such as high porosity, conductivity and easy electron transfer that can be successfully used to detect pesticide residues from food. This review emphasizes the role of carbon nanomaterials in the field of pesticide residue analysis in different food matrices. The carbon nanomaterials including carbon nanotubes, carbon dots, carbon nanofibers, graphene/graphene oxides, and activated carbon fibres are discussed in the review. In addition, the review examines future prospects in this research area to help improve detection techniques for pesticides analysis.

Determination and dietary intake risk assessment of 35 pesticide residues in cowpea (Vigna unguiculata [L.] Walp) from Hainan province, China

The presence of pesticide residues in cowpea raises serious health concerns. In this study, a novel, sensitive, high-performance method was developed to simultaneously analyze the residues of 35 pesticides in cowpea samples from growing areas in the Hainan province of China, from November 2018 to June 2021. The method employs modified QuEChERS sample pretreatment coupled with gas chromatography-tandem mass spectrometry. The limits of quantification of the 35 pesticides in the cowpea matrix ranged from 1.0 to 8.0 μg/kg. Twenty-seven of the 35 pesticides were detected, twelve of which are banned for use on legumes in China. Residues for ten pesticides in 17.1% of the samples exceeded their MRLs, with the highest exceedance of 380% observed in difenoconazole. Moreover, 80.8% of the samples contained one or more pesticide residues, with the most frequently detected pesticide being chlorfenapyr with a detection rate of 46.3%. In addition, the pesticide triazophos was detected through different years and regions. Notably, the chronic dietary exposure risk (%ADI) of the detected pesticides, evaluated from the national estimated acceptable daily intake, was lower than 100% in Chinese people of different age groups.

Evaluating green silver nanoparticles as prospective biopesticides: An environmental standpoint

The current method of agriculture entails the usage of excessive amounts of pesticides and fertilizers. The blatant use of conventional pesticides and fertilizers over several decades has led to their bioaccumulation with adverse effects on soil biodiversity and the development of resistance by pests. With the decline in clinically useful antibiotics and increase in multi drug resistant microbes, it is imperative to develop new and effective antimicrobial therapies. Growing awareness and demand for efficacious biorational pesticides are on the rise. Silver nanoparticles are widely known antimicrobials and have been in use for several purposes for a long time. This work reviews the implications of applying silver nanoparticles in agriculture and their possible consequences. The physiological and biochemical changes in plants due to the uptake of silver nanoparticles as a consequence of its morphology, capping biomolecules and method of application are comprehensively discussed in this review article. Studies on tolerance levels or stress due to silver nanoparticles by variation in concentration/doses on diverse flora and fauna are also analyzed here. Further, phytotoxicity and genotoxicity due to the metal as well as its transformation in soil, water and sludge are taken into account. We also gauge the potential of biogenic silver nanoparticles-viable antimicrobial agents for enhanced applications in agriculture as biopesticides.

Iron nanoparticles decorated hierarchical carbon fiber forest for the magnetic solid-phase extraction of multi-pesticide residues from water samples

This study describes a versatile, robust and fast sample pre-concentration novel method based on chemical vapour deposition grown iron nanoparticles dispersed hierarchical carbon fiber forest (Fe-ACF/CNF) for the determination of multi-pesticide residue in water samples. This method was developed by the implementation of Fe-ACF/CNF to magnetic solid-phase extraction method (MSPE) for the adsorption of twenty-nine pesticides of various classes using gas chromatography equipped with an electron capture detector. Fe-ACF/CNF was grown via tip growth mechanism and Fe-nanoparticles are moved to the tip of CNF. The presence of Fe-nanoparticles is responsible for the magnetic property of proposed adsorbents. The Fe-ACF/CNF is competent enough to extract twenty-nine pesticides of different physico-chemical characteristics from water samples. All the predominant parameters including the amount of sorbent desorption time, temperature, sonication effect, regeneration, and reusability of Fe-ACF/CNF were thoroughly investigated. Acceptable linearity was obtained in the range of 20-500 μg/L with a correlation coefficient value ≥ 0.990 for all pesticides. The accuracy of the developed method was evaluated and the obtained recovery of the spiked samples was within 70-120% (standard deviation ≤ 15%) and reusability up to the 4th cycle. The limit of detection and quantification values was in the range of 1.44-5.15 and 4.76-17.0 μg/L, respectively. The obtained results are also cross verified with real water samples from the Gomti river (Lucknow, India) and shown the excellent extraction efficiency of Fe-ACF/CNF.

[Progress of sample preparation and analytical methods of dried fruit foods]

坚果、果脯等干果类食品含有丰富的营养成分,深受国内外广大消费者的喜爱。但这些食品在果实生产、加工、储运时会使用农药或产生霉变等,造成干果中农药、重金属、霉菌毒素或添加剂等有害成分残留,甚至超过国家限量要求,带来严重的食品安全问题。因此,加强干果类食品的质量监督具有重要的经济和社会意义。但干果类食品基质复杂,有害物质种类多,结构和性质差异大,含量低,其分析检测需要快速高效的样品前处理技术和准确灵敏的分析检测方法。该文主要综述了近十年来干果类食品中有害物质的样品前处理及分析检测方法研究进展。其中样品前处理方法主要包括各种场辅助萃取法、相分离法和衍生化萃取方法等。场辅助萃取法主要是借助超声波和微波场等外场(协同)作用加快干果中有害物质的溶出速度,提高其萃取效率。相分离法,包括固相(微)萃取、分散固相萃取和液相(微)萃取法等,具有溶剂消耗少、分离富集效率高的优势,是干果样品分析中较常使用的前处理方法。该文还重点介绍了干果中各类有害成分分析检测技术,主要包括色谱、原子光谱、无机质谱、电化学分析等常规实验室方法,以及一些适用于现场分析的快速检测技术,并以此为基础,展望了干果类食品中有害物质分析检测技术的发展趋势。

Phosphonium-based deep eutectic solvent coupled with vortex-assisted liquid-liquid microextraction for the determination of benzoylurea insecticides in olive oil

In this study, a novel method using a phosphonium-based deep eutectic solvent coupled with vortex-assisted liquid-liquid microextraction was investigated for the enrichment and separation of five benzoylurea insecticides in olive oil. The experimental factors affecting the extraction efficiency, including the extractant type, deep eutectic solvent volume, extraction time, and extraction mode, were optimized. Under optimal conditions, good linearity was observed for all target analytes, with correlation coefficients (r) ranging from 0.9971 to 0.9998; the limits of detection were in the range of 1.5 to 7.5 μg/L, and the recoveries of analytes using the proposed method ranged between 66.9 and 111.0%. The simple, rapid, and effective method was successfully applied for detecting target analytes in olive oil sample.