Development of an Immunosensor Based on Surface Plasmon Resonance for Simultaneous Residue Analysis of Three Pesticides —Boscalid, Clothianidin, and Nitenpyram— in Vegetables

A simultaneous immunosensor based on surface plasmon resonance (SPR) was developed for determination of 3 pesticides —boscalid, clothianidin and nitenpyram— instead of the direct competitive enzyme-linked immunosorbent assays (dcELISAs) widely used as individual determination methods. Carboxy groups...

Full description

Saved in:
Bibliographic Details
Published inAnalytical Sciences Vol. 34; no. 5; pp. 533 - 539
Main Authors HIRAKAWA, Yuki, YAMASAKI, Tomomi, HARADA, Ayako, IWASA, Seiji, NARITA, Hiroshi, MIYAKE, Shiro
Format Journal Article
LanguageEnglish
Published Singapore The Japan Society for Analytical Chemistry 2018
Springer Nature Singapore
Japan Science and Technology Agency
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:A simultaneous immunosensor based on surface plasmon resonance (SPR) was developed for determination of 3 pesticides —boscalid, clothianidin and nitenpyram— instead of the direct competitive enzyme-linked immunosorbent assays (dcELISAs) widely used as individual determination methods. Carboxy groups that introduced compounds to their pesticides were designed, and conjugates of them and bovine serum albumin were immobilized onto separate channels of the same sensor chip. When a mixture of 3 monoclonal antibodies reacted to each pesticide, and 3 pesticides were injected into the SPR immunosensor, each channel showed specific reactivity at 15 – 93 ng mL−1 for boscalid, 6.7 – 27 ng mL−1 for clothianidin, and 7.3 – 62 ng mL−1 for nitenpyram. Recovery tests using vegetables spiked with a mixture of 3 pesticides showed good results: 75 – 90%, 88 – 104%, and 72 – 105%, respectively, with a high correlation to results of the dcELISAs. The SPR immunosensor would be useful for the determination of pesticide residues in vegetables.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0910-6340
1348-2246
DOI:10.2116/analsci.17P487