利用 MS1 和 MS2 级超高效液相色谱-QTOF 同时分析作物中的 504 种农药多残留。

IF 4.7 2区 农林科学 Q1 FOOD SCIENCE & TECHNOLOGY Foods Pub Date : 2024-10-31 DOI:10.3390/foods13213503
Mun-Ju Jeong, Su-Min Kim, Ye-Jin Lee, Yoon-Hee Lee, Hye-Ran Eun, Miok Eom, Gui-Hyun Jang, JuHee Lee, Hyeong-Wook Jo, Joon-Kwan Moon, Yongho Shin
{"title":"利用 MS1 和 MS2 级超高效液相色谱-QTOF 同时分析作物中的 504 种农药多残留。","authors":"Mun-Ju Jeong, Su-Min Kim, Ye-Jin Lee, Yoon-Hee Lee, Hye-Ran Eun, Miok Eom, Gui-Hyun Jang, JuHee Lee, Hyeong-Wook Jo, Joon-Kwan Moon, Yongho Shin","doi":"10.3390/foods13213503","DOIUrl":null,"url":null,"abstract":"<p><p>A robust analytical method was developed for the simultaneous detection of 504 pesticide multiresidues in various crops using ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF). The method integrates both MS<sup>1</sup> and MS<sup>2</sup> levels through sequential window acquisition of all theoretical mass spectra (SWATH) analysis, allowing for accurate mass measurements and the construction of a spectral library to enhance pesticide residue identification. An evaluation of the method was carried out according to international standards, including the FAO guidelines and SANTE/11312/2021. Validation across five representative crops-potato, cabbage, mandarin, brown rice, and soybean-demonstrated exceptional sensitivity, with over 80% of the analytes detected at trace levels (≤2.5 μg/kg). Moreover, an impressive 96.8% to 98.8% of the compounds demonstrated LOQs of ≤10 μg/kg. Most compounds exhibited excellent linearity (<i>r</i><sup>2</sup> ≥ 0.980) and satisfactory recovery rates at spiking levels of 0.01 and 0.1 mg/kg. Among 42 crop samples analyzed, pesticides were detected in 1 cabbage, 3 mandarin, and 6 rice samples, with a mass accuracy within ±5 ppm and a Fit score ≥ 70.8, confirming the method's practical applicability and reliability. The detected residues ranged from 12.3 to 339.3 μg/kg, all below the established maximum residue limits (MRLs). This comprehensive approach offers an efficient, reliable, and scalable solution for pesticide multiresidue monitoring, supporting food safety programs and regulatory compliance.</p>","PeriodicalId":12386,"journal":{"name":"Foods","volume":"13 21","pages":""},"PeriodicalIF":4.7000,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11545108/pdf/","citationCount":"0","resultStr":"{\"title\":\"Simultaneous Analysis of 504 Pesticide Multiresidues in Crops Using UHPLC-QTOF at MS<sup>1</sup> and MS<sup>2</sup> Levels.\",\"authors\":\"Mun-Ju Jeong, Su-Min Kim, Ye-Jin Lee, Yoon-Hee Lee, Hye-Ran Eun, Miok Eom, Gui-Hyun Jang, JuHee Lee, Hyeong-Wook Jo, Joon-Kwan Moon, Yongho Shin\",\"doi\":\"10.3390/foods13213503\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>A robust analytical method was developed for the simultaneous detection of 504 pesticide multiresidues in various crops using ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF). The method integrates both MS<sup>1</sup> and MS<sup>2</sup> levels through sequential window acquisition of all theoretical mass spectra (SWATH) analysis, allowing for accurate mass measurements and the construction of a spectral library to enhance pesticide residue identification. An evaluation of the method was carried out according to international standards, including the FAO guidelines and SANTE/11312/2021. Validation across five representative crops-potato, cabbage, mandarin, brown rice, and soybean-demonstrated exceptional sensitivity, with over 80% of the analytes detected at trace levels (≤2.5 μg/kg). Moreover, an impressive 96.8% to 98.8% of the compounds demonstrated LOQs of ≤10 μg/kg. Most compounds exhibited excellent linearity (<i>r</i><sup>2</sup> ≥ 0.980) and satisfactory recovery rates at spiking levels of 0.01 and 0.1 mg/kg. Among 42 crop samples analyzed, pesticides were detected in 1 cabbage, 3 mandarin, and 6 rice samples, with a mass accuracy within ±5 ppm and a Fit score ≥ 70.8, confirming the method's practical applicability and reliability. The detected residues ranged from 12.3 to 339.3 μg/kg, all below the established maximum residue limits (MRLs). This comprehensive approach offers an efficient, reliable, and scalable solution for pesticide multiresidue monitoring, supporting food safety programs and regulatory compliance.</p>\",\"PeriodicalId\":12386,\"journal\":{\"name\":\"Foods\",\"volume\":\"13 21\",\"pages\":\"\"},\"PeriodicalIF\":4.7000,\"publicationDate\":\"2024-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11545108/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Foods\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://doi.org/10.3390/foods13213503\",\"RegionNum\":2,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"FOOD SCIENCE & TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Foods","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.3390/foods13213503","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

利用超高效液相色谱-四极杆飞行时间质谱(UHPLC-QTOF)技术,开发了一种稳健的分析方法,用于同时检测多种作物中的 504 种农药多残留。该方法通过对所有理论质谱的顺序窗口获取(SWATH)分析,整合了 MS1 和 MS2 水平,从而实现了精确的质量测量,并构建了光谱库,提高了农药残留的鉴定能力。根据国际标准(包括粮农组织准则和 SANTE/11312/2021)对该方法进行了评估。五种代表性作物--土豆、卷心菜、柑橘、糙米和大豆--的验证结果表明,该方法灵敏度极高,超过 80% 的分析物在痕量水平(≤2.5 μg/kg)即可被检测到。此外,96.8%-98.8%的化合物的最低检测限为≤10 μg/kg。在 0.01 和 0.1 mg/kg 的加标水平下,大多数化合物都表现出良好的线性关系(r2 ≥ 0.980)和令人满意的回收率。在分析的 42 个农作物样品中,1 个白菜样品、3 个柑橘样品和 6 个水稻样品检测出了农药残留,质量准确度在 ±5 ppm 以内,Fit 值≥ 70.8,证实了该方法的实用性和可靠性。检测到的残留量范围为 12.3 至 339.3 μg/kg,均低于规定的最大残留限量(MRL)。这种综合方法为农药多残留监测提供了一种高效、可靠和可扩展的解决方案,为食品安全计划和监管合规提供了支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Simultaneous Analysis of 504 Pesticide Multiresidues in Crops Using UHPLC-QTOF at MS1 and MS2 Levels.

A robust analytical method was developed for the simultaneous detection of 504 pesticide multiresidues in various crops using ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF). The method integrates both MS1 and MS2 levels through sequential window acquisition of all theoretical mass spectra (SWATH) analysis, allowing for accurate mass measurements and the construction of a spectral library to enhance pesticide residue identification. An evaluation of the method was carried out according to international standards, including the FAO guidelines and SANTE/11312/2021. Validation across five representative crops-potato, cabbage, mandarin, brown rice, and soybean-demonstrated exceptional sensitivity, with over 80% of the analytes detected at trace levels (≤2.5 μg/kg). Moreover, an impressive 96.8% to 98.8% of the compounds demonstrated LOQs of ≤10 μg/kg. Most compounds exhibited excellent linearity (r2 ≥ 0.980) and satisfactory recovery rates at spiking levels of 0.01 and 0.1 mg/kg. Among 42 crop samples analyzed, pesticides were detected in 1 cabbage, 3 mandarin, and 6 rice samples, with a mass accuracy within ±5 ppm and a Fit score ≥ 70.8, confirming the method's practical applicability and reliability. The detected residues ranged from 12.3 to 339.3 μg/kg, all below the established maximum residue limits (MRLs). This comprehensive approach offers an efficient, reliable, and scalable solution for pesticide multiresidue monitoring, supporting food safety programs and regulatory compliance.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Foods
Foods Immunology and Microbiology-Microbiology
CiteScore
7.40
自引率
15.40%
发文量
3516
审稿时长
15.83 days
期刊介绍: Foods (ISSN 2304-8158) is an international, peer-reviewed scientific open access journal which provides an advanced forum for studies related to all aspects of food research. It publishes reviews, regular research papers and short communications. Our aim is to encourage scientists, researchers, and other food professionals to publish their experimental and theoretical results in as much detail as possible or share their knowledge with as much readers unlimitedly as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced. There are, in addition, unique features of this journal: Ÿ manuscripts regarding research proposals and research ideas will be particularly welcomed Ÿ electronic files or software regarding the full details of the calculation and experimental procedure, if unable to be published in a normal way, can be deposited as supplementary material Ÿ we also accept manuscripts communicating to a broader audience with regard to research projects financed with public funds
期刊最新文献
Construction of Sensory Evaluation System of Purple Sweet Potato Rice Steamed Sponge Cake Based on Fuzzy Mathematics. Optimization of Ferimzone and Tricyclazole Analysis in Rice Straw Using QuEChERS Method and Its Application in UAV-Sprayed Residue Study. Nutrition, Flavor, and Microbial Communities of Two Traditional Bacterial Douchi from Gansu, China. Diversity Analysis and Comprehensive Evaluation of 101 Soybean (Glycine max L.) Germplasms Based on Sprout Quality Characteristics. Antioxidant Potential Evaluation at Various Stages of Black Cumin Oil Production.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1