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Article Dans Une Revue Chemosphere Année : 2015

Nature and decomposition degree of cover crops influence pesticide sorption: Quantification and modelling

Résumé

This study quantifies and models the influence of the type and the degree of decomposition of cover crops (CC) on three pesticides sorption: epoxiconazole (EPX), S-metolachlor (SMOC) and glyphosate (GLY). Residues of four cover crop species were incubated for 0, 6, 28 or 56 d in controlled conditions. For each incubation time, adsorption of pesticides on CC residues was measured in batch experiments. Additionally, the biochemical and elemental composition (Van Soest fractionation, C:N, 13C NMR spectroscopy) of CC was characterized. Mineralization of CC residues was monitored at all incubation times using CO2 trapping. Results showed that the adsorption of pesticides differed significantly according to (i) the type of molecule, (ii) the type of CC, (iii) the degree of CC decomposition and the interaction CC × decomposition time. EPX and GLY were the most (Kd ranging from 188 to 267 L kg−1) and the least (Kd ranging from 18 to 28 L kg−1) sorbed pesticides respectively. With increasing decomposition of the CC residue, sorption increased by 1.6- to 4.7-fold according to the type of pesticide and cover crop. It was significantly correlated with the net cumulative mineralization (ρ > 0.7) and other indicators of biochemical composition such as C:N ratio (ρ < −0.7), the Van Soest neutral detergent soluble fraction (ρ > 0.5) and the alkyl/O-alkyl C ratio determined by NMR. An innovative model based on net cumulative mineralization of CC residues is proposed to describe the pesticide sorption and appears to be a promising approach to account for the effects of decaying plant residues on the environmental fate of pesticides.
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Dates et versions

hal-01192519 , version 1 (02-09-2015)

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Anna Cassigneul, Lionel Alletto, Pierre Benoit, Valerie Bergheaud, Veronique Etievant, et al.. Nature and decomposition degree of cover crops influence pesticide sorption: Quantification and modelling. Chemosphere, 2015, 119, pp.1007-1014. ⟨10.1016/j.chemosphere.2014.08.082⟩. ⟨hal-01192519⟩
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