INRA, Institut National de la Recherche Agronomique, UMR 1091 EGC, 78850 Thiverval-Grignon, France.
Chemosphere. 2013 Jun;91(11):1447-55. doi: 10.1016/j.chemosphere.2012.12.005. Epub 2013 Feb 22.
Assessing pesticide fate in conservation agricultural systems requires a detailed understanding of their interaction with decomposing surface crop residues (mulch). Adsorption and desorption behavior of glyphosate, s-metolachlor and epoxiconazole was investigated on maize mulch residues decomposed under laboratory and field conditions. Our conceptual approach included characterization of chemical composition and hydrophobicity of mulch residues in order to generate parameters to predict sorption behavior. Adsorption of s-metolachlor and epoxiconazole greatly increased with mulch decomposition, whereas glyphosate adsorption was less affected but its desorption was increased. Mulch characteristics including aromaticity, hydrophobicity and polarity indices were strongly correlated to Koc of the non-ionic pesticides. A predictive model based on compositional data (CoDa) analysis revealed that the sorption capacity of decomposing mulch can be predicted from descriptors such as aromatic and alkyl C corresponding respectively to lignin and NDF biochemical fractions. The decomposition degree of mulch residues should be taken into account while predicting the fate of pesticides.
评估保护性农业系统中农药的命运需要详细了解它们与分解的地表作物残体(覆盖物)的相互作用。本研究在实验室和田间条件下,研究了草甘膦、甲草胺和乙氧氟草醚在玉米残体上的吸附和解吸行为。我们的概念方法包括对覆盖物残体的化学成分和疏水性进行特征描述,以便生成预测吸附行为的参数。甲草胺和乙氧氟草醚的吸附随着覆盖物的分解而大大增加,而草甘膦的吸附受影响较小,但解吸增加。覆盖物的特征,包括芳香度、疏水性和极性指数,与非离子农药的 Koc 强烈相关。基于组成数据(CoDa)分析的预测模型表明,从木质素和 NDF 生化组分分别对应的芳香族 C 和烷基 C 等描述符可以预测分解覆盖物的吸附能力。在预测农药命运时,应考虑覆盖物残体的分解程度。