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Residue dynamics and risk assessment of Luna Experience® (fluopyram + tebuconazole) and chlorpyrifos on French beans (Phaseolus vulgaris L.)
- Katna, Sapna, Dubey, Jatiender Kumar, Patyal, Surender Kumar, Devi, Nisha, Chauhan, Avinash, Sharma, Ajay
- Environmental science and pollution research international 2018 v.25 no.27 pp. 27594-27605
- Phaseolus vulgaris, chlorpyrifos, dry beans, foliar application, green beans, half life, harvest date, maximum residue limits, pods, seeds, soil, tebuconazole
- The persistence of chlorpyrifos, fluopyram, and tebuconazole was estimated in green pods, matured seeds, and soil of French beans using dispersive QuEChERS. Three foliar applications each of chlorpyrifos and a combination fungicide fluopyram + tebuconazole (Luna experience, 400 SC) were applied at 600 and 125 + 125 as a standard dose and 1200 and 250 + 250 g a.i. ha⁻¹ as a double dose, respectively, were applied at an interval of 10 days and treated pods were picked up at regular intervals. Dried mature seeds and soil were also monitored at harvest. The initial deposits of chlorpyrifos on bean pods were 3.083 and 6.017 mg kg⁻¹ with a half-life of 1.86 and 2.29 days, at respective doses. Foliar application of a combi product Luna experience yielded 3.396 and 5.772 mg kg⁻¹ residues of fluopyram and 3.613 and 5.887 mg kg⁻¹ of tebuconazole in green pods at standard and double dose with almost same half-lives of 3.4 and 3.8–3.9 days. Residues declined below the limit of quantitation (LOQ) of 0.05 mg kg⁻¹ in green beans after 15 and 25 days after the application of double dose of chlorpyrifos and Luna experience, respectively. However, the residues in dry bean seeds and soil reached below the LOQ of 0.05 mg kg⁻¹ at the time of harvest. A pre-harvest interval of 5, 10, and 7 days has been proposed for chlorpyrifos, fluopyram, and tebuconazole, respectively, in beans. HQ < 1 and TMDI < MPI in all test chemicals. Hence, it was concluded that a waiting period of 5 days for chlorpyrifos and 7–10 days in Luna experience will be safer to consumers. This data generated will be useful for regulatory agency for fixing MRLs.