Chrome Extension
WeChat Mini Program
Use on ChatGLM

Trace analysis of 28 antibiotics in plant tissues (root, stem, leaf and seed) by optimized QuEChERS pretreatment with UHPLC-MS/MS detection

Journal of Chromatography B(2020)

Cited 9|Views21
No score
Abstract
Phytoremediation has proven to be an effective in-situ treatment technique for antibiotic contamination. Due to the immature methods of extracting multi-antibiotics in different plant tissues, the antibiotic absorption and transportation mechanism in the phytoremediation process has yet to be resolved. Therefore, an improved Quick, Easy, Cheap, Effective, Rugged and Safe (QuEChERS) pretreatment with ultra-high-performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) detection method for 28 antibiotics in different plant tissues (root, stem, leaf and seed) was developed in this study. The optimized method showed satisfactory performance with recoveries for most antibiotics ranging from 70% to 130% (except sulfadoxine with 138 +/- 8.84% in root, sulfameter with 68.9 +/- 1.87% and sulfadoxine with 141 +/- 10.0% in seed). The limits of detection (LODs) of the target compounds in root, stem, leaf and seed were 0.04 +/- 0.02 2.50 +/- 1.14 ng/g, 0.05 +/- 0.02 1.78 +/- 0.42 ng/g, 0.06 +/- 0.01 2.50 +/- 0.14 ng/g and 0.13 +/- 0.10 3.64 +/- 0.74 ng/g, respectively. This developed method was successfully applied to the determination of antibiotics in different tissues of hydroponic wetland plants exposed to antibiotics-spiked water for one-month. Sixteen of 28 spiked antibiotics were detected in plant tissue samples. Overall, of these 16 antibiotics, all were detected in root samples (from < LOQ to 1478 +/- 353 ng/g), eleven in stem samples (from < LOQ to 425 +/- 47.0 ng/g), and nine in leaf samples (from < LOQ to 429 +/- 84.5 ng/g). This developed analytical method provided a robust tool for the simultaneous screening and determination of antibiotics in different plant tissues.
More
Translated text
Key words
Antibiotic,Plant tissues,QuEChERS,UHPLC-MS/MS
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined