Transfer and risk assessment of perchlorate during green/black tea processing and brewing.

IF 8 Food research international (Ottawa, Ont.) Pub Date : 2025-02-01 Epub Date: 2024-12-30 DOI:10.1016/j.foodres.2024.115579
Hezhi Sun, Yabo Liang, Peipei Qi, Yan Liu, Fengjian Luo, Zongmao Chen, Li Zhou
{"title":"Transfer and risk assessment of perchlorate during green/black tea processing and brewing.","authors":"Hezhi Sun, Yabo Liang, Peipei Qi, Yan Liu, Fengjian Luo, Zongmao Chen, Li Zhou","doi":"10.1016/j.foodres.2024.115579","DOIUrl":null,"url":null,"abstract":"<p><p>Perchlorate was reported to be taken up by tea (Camellia sinensis L.) plants and mainly stored in leaves. However, the change of contents in perchlorate in fresh tea leaf-made tea and tea infusion remains unclear. Here, we revealed the transfer of perchlorate during green/black tea processing and brewing using UPLC-MS/MS and established a corresponding dietary risk assessment method. The processing factors based on the dry-weight contents of perchlorate during green and black tea processing were in the range of 0.96-1.17. The content of perchlorate was stable throughout tea processing. Perchlorate in made tea was prone to leaching into infusions with an average leaching rate of 74.1 ± 12.6 %. Moreover, risk assessment was developed based on the above processing factor, leaching rate and risk quotient (RQ) method, which contributes to estimating the impact of perchlorate in fresh tea leaves on human dietary exposure via tea drinking.</p>","PeriodicalId":94010,"journal":{"name":"Food research international (Ottawa, Ont.)","volume":"201 ","pages":"115579"},"PeriodicalIF":8.0000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Food research international (Ottawa, Ont.)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.foodres.2024.115579","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/30 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Perchlorate was reported to be taken up by tea (Camellia sinensis L.) plants and mainly stored in leaves. However, the change of contents in perchlorate in fresh tea leaf-made tea and tea infusion remains unclear. Here, we revealed the transfer of perchlorate during green/black tea processing and brewing using UPLC-MS/MS and established a corresponding dietary risk assessment method. The processing factors based on the dry-weight contents of perchlorate during green and black tea processing were in the range of 0.96-1.17. The content of perchlorate was stable throughout tea processing. Perchlorate in made tea was prone to leaching into infusions with an average leaching rate of 74.1 ± 12.6 %. Moreover, risk assessment was developed based on the above processing factor, leaching rate and risk quotient (RQ) method, which contributes to estimating the impact of perchlorate in fresh tea leaves on human dietary exposure via tea drinking.

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
绿茶/红茶加工和冲泡过程中高氯酸盐的转移和风险评估。
据报道,高氯酸盐被茶(Camellia sinensis L.)植物吸收,主要储存在叶片中。然而,高氯酸盐在鲜茶和茶泡茶中的含量变化尚不清楚。本研究利用UPLC-MS/MS分析了绿茶/红茶加工和冲泡过程中高氯酸盐的转移,并建立了相应的饮食风险评估方法。绿茶和红茶加工过程中以高氯酸盐干重含量为基准的加工因子在0.96 ~ 1.17之间。高氯酸盐的含量在整个茶叶加工过程中是稳定的。泡茶中高氯酸盐易浸出,平均浸出率为74.1±12.6%。此外,基于上述加工因子、浸出率和风险商(RQ)方法建立了风险评估,有助于评估新鲜茶叶中高氯酸盐对人类饮茶饮食暴露的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Bioactive compounds: functional foods as the cornerstone of healthy nutrition: linking academia and industry. Untargeted metabolomic approach to assess the acute metabolism and urinary excretion of olive leaf bioactive compounds in humans. Milk-derived casein glycomacropeptide improves colonic mucus function under Western-style diet feeding in a sialylation-dependent manner. Chemical composition, bioactive compounds, biological activity, and applications of ora-pro-nóbis (Pereskia spp.): A review. Machine learning-based predictive modeling of foodborne pathogens and antimicrobial resistance in food microbiomes using omics techniques: A systematic review.
×
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:604180095
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