| Literature DB >> 34486835 |
Lihui Zhou1, Xiaohua Xiao1, Gongke Li1.
Abstract
Dried fruit foods, including nuts and preserved fruits, are favored by consumers and are rich in protein, lipids, minerals, vitamins, and other nutrients. However, these food products can be contaminated by pesticide residues, heavy metals, mycotoxins, and additives during growth, processing, storage, and transportation. The presence of such pollutants in excess of a certain limit will lead to food safety problems. Therefore, it is of great economic and social significance to strengthen the quality supervision of dried fruit foods. However, these foods have a complex matrix and low concentrations of various harmful substances, which necessitates efficient and appropriate sample preparation methods as well as rapid, accurate detection methods. In the present article, the sample preparation and analytical methods for harmful substances in dried fruit foods since 2010 are reviewed. The sample preparation methods are classified as field-assisted extraction, phase separation, and derivatization and extraction methods. The field-assisted extraction method is based on the action of an external field (synergistic) such as ultrasonic or microwave fields to increase the dissolution rate of hazardous substances in dried fruits and improve the extraction efficiency. Phase separation methods such as solid-phase extraction, dispersive solid-phase extraction and solid-phase microextraction are commonly used as sample preparation methods for dried fruit samples, because of the advantages of low solvent consumption and wide analysis range. Moreover, this paper discusses the progress of various analytical methods for these hazardous substances in dried fruits, including conventional laboratory methods such as chromatography, atomic spectroscopy, inorganic mass spectrometry, and electrochemical analysis, as well as rapid detection techniques suitable for field analysis. Laboratory testing has the advantages of high accuracy, high sensitivity, and low detection limits. However, it has the disadvantages of complicated preparation, long analysis time, and difficult operation. Rapid detection technology speeds up the analytical speed, has operational simplicity, and saves analysis time. The complexity of the food matrix, which easily interferes with the sample matrix, low selectivity, and difficulty in accurate quantification, it is necessary to minimize cases of incorrect or erroneous detection. Therefore, rapid detection of harmful substances in dried fruit foods is possible by optimizing the sample pretreatment methods and detection technologies, and by seeking new (especially, on-site) detection technologies. Prospects on the development of selective and non-destructive sample preparation methods and automated, high-throughput, rapid detection methods in dried fruit food analysis are presented. The development of new, green rapid sample pretreatment methods and technical products that integrate separation, enrichment, and detection as well as the construction of accurate and sensitive rapid detection methods are expected to become the development trend in the analysis of harmful substances in dried fruit foods.Entities:
Keywords: analytical methods; dried fruit foods; food safety; hazardous substances; review; sample preparation
Mesh:
Substances:
Year: 2021 PMID: 34486835 PMCID: PMC9404242 DOI: 10.3724/SP.J.1123.2021.06030
Source DB: PubMed Journal: Se Pu ISSN: 1000-8713
干果类食品中有害物质的种类、名称、限量标准和分析检测方法
| Hazardous | Category | Analytes | Maximum | Maximum | Sample preparation | Analytical | Ref. | ||
|---|---|---|---|---|---|---|---|---|---|
| Pesticide | insecticide | pyrethroids, organic phosphines | 0.01- | 6 | - | UAE, MAE, | GC, GC-MS, | [ | |
| residue | bactericide | dithiocarbamates, triazoles | 0.01- | 60 | - | SPE, DSPE, | HPLC-MS/MS, | ||
| herbicide | paraquat, aquacide, | 0.01- | 0.3 | - | QuEChERS | HPLC | |||
| plant growth | gibberellin, forchlorfenuron, | 0.2- | 10 | - | |||||
| Heavy metal | heavy metal | Pb, Hg, Cd, Cr, As | - | - | Microwave- | AAS, AFS, ICP- | [ | ||
| Fungimycin | fungimycin | aflatoxin | 5.0- | 50* | - | SPE, SPME, DSPE, | HPLC, HPLC-MS, | [ | |
| Food | sweetening | aspartame, saccharin sodium, | - | 0.025- | 6.0 | UAE, SPE, | IC, HPLC, HPLC- | [ | |
| preservative | nitrite | - | 0.5- | 1.0 | DLLME | GC, HPLC, UV-Vis, | [ | ||
| decolorant | sulfur dioxide, sulfur | - | 0.05- | 0.35 | ELISA, SERS, | ||||
| colorant | sudan red, rose red B, acid | - | 0.1- | 10 | CE, ICP-MS, | [ | |||
| Allergen | allergenic | Cora 1, Cora 8, Arah 1 | - | - | UAE | ELISA, PCR, | [ | ||
UAE: ultrasound assisted extraction; MAE: microwave assisted extraction; DSPE: dispersive solid phase extraction; LLME: liquid-liquid microextraction; DLLME: dispersive liquid-liquid microextraction; AAS: atomic absorption spectroscopy; AFS: atomic fluorescence spectrometry; ICP-OES: inductively coupled plasma-optical emission spectrometry; ICP-MS: inductively coupled plasma mass spectrometry; ELISA: enzyme linked immunosorbent assay; FL: fluorescence; ECL: electrochemiluminescence; IC: ion chromatography; UV-Vis: ultraviolet and visible spectrophotometry; SERS: surface-enhanced Raman scattering; SWSV: square wave stripping voltammeter; CE: capillary electrophoresis; PCR: polymerase chain reaction; -: no data. * The unit is μg/kg.
干果类食品样品前处理方法及其优缺点
| Sample preparation | Advantages | Disadvantages | Ref. |
|---|---|---|---|
| UAE, MAE | high extraction efficiency, fast speed, | filtration, operation trouble | [ |
| low cost, low solvent consumption | |||
| SPE | low solvent consumption, no separation | long extraction time, poor batch repeatability | [ |
| SPME | combination of extraction and concentration, | fragile fiber, peeling of coating, memory effect | [ |
| DSPE | simple and fast operation, low cost, | cumbersome process, matrix effects, | [ |
| LLME | high extraction efficiency, | centrifugal separation, poor recovery | [ |
| Derivatization | improvements in the detectability of | cumbersome operation, effects on chromatographic | [ |
干果中有害物质实验室检测方法
| Analytical method | Analytes | Samples | LOD/(μg/kg) | Recovery/% | Ref. | |
|---|---|---|---|---|---|---|
| SPME-LC/MS | patulin | dried fruit | 0.0235* | 92.5- | 94.5 | [ |
| QuEChERS-UPLC-MS/MS | pesticide residue | nut | 0.01-10 | 51.0- | 126.0 | [ |
| HPLC | food additives | preserved fruit | 100-250 | 90.2- | 106.3 | [ |
| QuEChERS-GC-MS/MS | multi-residue pesticide | dried fruits | - | 70- | 120 | [ |
| QuEChERS-LC-ESI-MS | acrylamide | dried fruits | 2.0 | 61- | 82 | [ |
| DSPE-CE | synthetic food colorants | preserved fruit | 3.50-5.50 | 94.3- | 102 | [ |
| IC | sulfites | dried fruits | 143* | 81- | 105 | [ |
| AFS | mercury | nuts | 0.08 | 100- | 101 | [ |
| ICP-MS | heavy metal | dried strawberry | 2.60-427.60 | 79- | 104.9 | [ |
* The unit is ng/mL.
图1基于协同效应和酶促可编程3D DNA纳米花的电化学发光生物传感器原理图[
图2具有不同生物分子的BB-MZI对的芯片示意图[