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Research Article

Study on residue and dissipation of flurochloridone by LC-MS/MS in potato and soil under open-field conditions in the China’s Qinghai Plateau

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Pages 4942-4952 | Received 25 Nov 2020, Accepted 01 Apr 2021, Published online: 26 May 2021
 

ABSTRACT

In this research, the dissipation dynamics and residue distribution of flurochloridone in potato were assessed using a modified QuEChERS method combined with LC-MS/MS. At 0.01–1 mg kg−1 flurochloridone application, the recoveries ranged from 81.3% to 90.9% in potato leaf, root, tuber and soil, with the relative standard deviation of 1.6%-3.5%. The limits of quantification and detection for flurochloridone were 0.01 and 0.001 mg kg−1 in the four matrices. The dissipation dynamic and terminal residue analyses of flurochloridone 25% emulsifiable concentrate in potato was conducted in three different areas of Qinghai plateau (Haidong, Haixi and Haibei). The half-lives of flurochloridone in the three districts were 25.7, 27.7 and 19.3 days in soil as well as 8.1, 10.2 and 7.0 days in leaf, respectively. The terminal residues of flurochloridone were <0.001, 0.005–0.013, <0.001 and 0.007–0.023 mg kg−1 in potato leaf, root, tuber and soil, respectively, which did not exceed the European maximum residue limit recommendation (0.1 mg kg−1). Our findings can provide a basic framework for the appropriate use of flurochloridone in potato in the Qinghai plateau.

Acknowledgment

The authors Wei Li, Hongyu Chen, and Shuo shen have acknowledged that the above manuscript shows content similarity to the following published paper.

Disclosure of potential conflicts of interest

No potential conflict of interest was reported by the author(s).

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Additional information

Funding

This work was supported by Applied Basic Research of Qinghai Science & Technology Department (2018-ZJ-716), National Natural Science Foundation of China (31860512) and Qinghai Academy of Agriculture and Forestry Innovation Fund (2017-NKY-08).

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