{"title":"利用表面增强拉曼光谱检测食品中硫胺的最新进展","authors":"","doi":"10.1016/j.jfca.2024.106855","DOIUrl":null,"url":null,"abstract":"<div><div>Thiram is a broad-spectrum fungicide used to protect postharvest fruits and vegetables from pathogen infection. However, thiram has been related to major human diseases, leading to the establishment of strict MRLs. Here, we are reviewing for the first time the methods for the identification and quantification of thiram in food products based on SERS. The sensitivity and reproducibility obtained when using different preprocessing steps and metallic nanoparticles have been compared. SERS allowed the detection of thiram <em>in situ</em>, which provided a band at approximately 1377 cm<sup><img>1</sup> that could be used for thiram quantification. SERS provided higher intensity enhancements for thiram than for other fungicides, indicating that it is a suitable technique for the selective detection of thiram. The highest sensitivities were observed when using silver nanoparticles. Machine learning analysis is emerging as a suitable way to enhance SERS reproducibility in <em>in situ</em> analysis, to predict thiram concentrations in fruit and vegetable internal layers, and to simultaneously quantify thiram together with other fungicides. Overall, SERS provides unique advantages for thiram detection, rendering it a suitable method for the inexpensive and highly sensitive detection of this fungicide.</div></div>","PeriodicalId":15867,"journal":{"name":"Journal of Food Composition and Analysis","volume":null,"pages":null},"PeriodicalIF":4.0000,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Recent advances in the use of surface-enhanced Raman spectroscopy for thiram detection in food products\",\"authors\":\"\",\"doi\":\"10.1016/j.jfca.2024.106855\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Thiram is a broad-spectrum fungicide used to protect postharvest fruits and vegetables from pathogen infection. However, thiram has been related to major human diseases, leading to the establishment of strict MRLs. Here, we are reviewing for the first time the methods for the identification and quantification of thiram in food products based on SERS. The sensitivity and reproducibility obtained when using different preprocessing steps and metallic nanoparticles have been compared. SERS allowed the detection of thiram <em>in situ</em>, which provided a band at approximately 1377 cm<sup><img>1</sup> that could be used for thiram quantification. SERS provided higher intensity enhancements for thiram than for other fungicides, indicating that it is a suitable technique for the selective detection of thiram. The highest sensitivities were observed when using silver nanoparticles. Machine learning analysis is emerging as a suitable way to enhance SERS reproducibility in <em>in situ</em> analysis, to predict thiram concentrations in fruit and vegetable internal layers, and to simultaneously quantify thiram together with other fungicides. Overall, SERS provides unique advantages for thiram detection, rendering it a suitable method for the inexpensive and highly sensitive detection of this fungicide.</div></div>\",\"PeriodicalId\":15867,\"journal\":{\"name\":\"Journal of Food Composition and Analysis\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2024-10-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Food Composition and Analysis\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0889157524008895\",\"RegionNum\":2,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CHEMISTRY, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Food Composition and Analysis","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0889157524008895","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, APPLIED","Score":null,"Total":0}
Recent advances in the use of surface-enhanced Raman spectroscopy for thiram detection in food products
Thiram is a broad-spectrum fungicide used to protect postharvest fruits and vegetables from pathogen infection. However, thiram has been related to major human diseases, leading to the establishment of strict MRLs. Here, we are reviewing for the first time the methods for the identification and quantification of thiram in food products based on SERS. The sensitivity and reproducibility obtained when using different preprocessing steps and metallic nanoparticles have been compared. SERS allowed the detection of thiram in situ, which provided a band at approximately 1377 cm1 that could be used for thiram quantification. SERS provided higher intensity enhancements for thiram than for other fungicides, indicating that it is a suitable technique for the selective detection of thiram. The highest sensitivities were observed when using silver nanoparticles. Machine learning analysis is emerging as a suitable way to enhance SERS reproducibility in in situ analysis, to predict thiram concentrations in fruit and vegetable internal layers, and to simultaneously quantify thiram together with other fungicides. Overall, SERS provides unique advantages for thiram detection, rendering it a suitable method for the inexpensive and highly sensitive detection of this fungicide.
期刊介绍:
The Journal of Food Composition and Analysis publishes manuscripts on scientific aspects of data on the chemical composition of human foods, with particular emphasis on actual data on composition of foods; analytical methods; studies on the manipulation, storage, distribution and use of food composition data; and studies on the statistics, use and distribution of such data and data systems. The Journal''s basis is nutrient composition, with increasing emphasis on bioactive non-nutrient and anti-nutrient components. Papers must provide sufficient description of the food samples, analytical methods, quality control procedures and statistical treatments of the data to permit the end users of the food composition data to evaluate the appropriateness of such data in their projects.
The Journal does not publish papers on: microbiological compounds; sensory quality; aromatics/volatiles in food and wine; essential oils; organoleptic characteristics of food; physical properties; or clinical papers and pharmacology-related papers.