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SERS nanosensor of 3-aminobenzeneboronic acid labeled Ag for detecting total arsenic in black tea combined with chemometric algorithms

Barimah, Alberta Osei (författare)
Jiangsu Univ, Sch Food & Biol Engn, Key Lab Modern Agr Equipment & Technol, Minist Educ, Zhenjiang 212013, Peoples R China.
Chen, Ping (författare)
Jiangsu Univ, Sch Food & Biol Engn, Key Lab Modern Agr Equipment & Technol, Minist Educ, Zhenjiang 212013, Peoples R China.
Yin, Limei (författare)
Jiangsu Univ, Sch Food & Biol Engn, Key Lab Modern Agr Equipment & Technol, Minist Educ, Zhenjiang 212013, Peoples R China.;Jiangsu Univ, Jiangsu Educ Dept, Int Joint Res Lab Intelligent Agr & Agriprod Proc, Zhenjiang 212013, Peoples R China.
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El-Seedi, Hesham (författare)
Uppsala universitet,Farmakognosi,Institutionen för farmaceutisk biovetenskap,Jiangsu Univ, Int Res Ctr Food Nutr & Safety, Zhenjiang 212013, Peoples R China.
Zou, Xiaobo (författare)
Jiangsu Univ, Sch Food & Biol Engn, Key Lab Modern Agr Equipment & Technol, Minist Educ, Zhenjiang 212013, Peoples R China.;Jiangsu Univ, Jiangsu Educ Dept, Int Joint Res Lab Intelligent Agr & Agriprod Proc, Zhenjiang 212013, Peoples R China.
Guo, Zhiming (författare)
Jiangsu Univ, Sch Food & Biol Engn, Key Lab Modern Agr Equipment & Technol, Minist Educ, Zhenjiang 212013, Peoples R China.;Jiangsu Univ, Jiangsu Educ Dept, Int Joint Res Lab Intelligent Agr & Agriprod Proc, Zhenjiang 212013, Peoples R China.
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Jiangsu Univ, Sch Food & Biol Engn, Key Lab Modern Agr Equipment & Technol, Minist Educ, Zhenjiang 212013, Peoples R China Jiangsu Univ, Sch Food & Biol Engn, Key Lab Modern Agr Equipment & Technol, Minist Educ, Zhenjiang 212013, Peoples R China.;Jiangsu Univ, Jiangsu Educ Dept, Int Joint Res Lab Intelligent Agr & Agriprod Proc, Zhenjiang 212013, Peoples R China. (creator_code:org_t)
Elsevier, 2022
2022
Engelska.
Ingår i: Journal of Food Composition and Analysis. - : Elsevier. - 0889-1575 .- 1096-0481. ; 110
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • Detrimental health effects caused by the intake of food contaminated with heavy metals have drawn concerns on effective monitoring using rapid and benign methods. This work presented a novel surface-enhanced Raman scattering (SERS)-based 3-Aminobenzeneboronic acid (ABBA) labeled silver (Ag) nanosensor combined with chemometric algorithms to detect and predict total arsenic (TAs) in acid digested spiked black tea leaves. The sensor recognizes TAs through the partial detachment of ABBA and the chemical formation of As-O-Ag linkage between the TAs and the Ag nanoparticles, which caused a SERS-on signal enhancement effect. SERS combined with competitive adaptive reweighted sampling partial least squares algorithm predicted the TAs with higher correlation coefficient (R-p) results (R-p = 0.9750) and a detection limit of 0.0273 mu g/g. Good recoveries of 83.84-109.53% and the excellent agreement with the inductively coupled plasma-mass spectrometry method (R-2 = 0.999) revealed this developed rapid method could be deployed for fast-tracking of As in food samples.

Ämnesord

NATURVETENSKAP  -- Kemi -- Analytisk kemi (hsv//swe)
NATURAL SCIENCES  -- Chemical Sciences -- Analytical Chemistry (hsv//eng)

Nyckelord

Labeled sensor
Chemometrics
Arsenic
SERS
CARS-PLS
Food safety

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Av författaren/redakt...
Barimah, Alberta ...
Chen, Ping
Yin, Limei
El-Seedi, Hesham
Zou, Xiaobo
Guo, Zhiming
Om ämnet
NATURVETENSKAP
NATURVETENSKAP
och Kemi
och Analytisk kemi
Artiklar i publikationen
Journal of Food ...
Av lärosätet
Uppsala universitet

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