ABSTRACT

Knowledge about herbicide-soil interactions is essential for the safe use of these products. The objective of this study was to evaluate the potential of multivariate discriminant analysis to predict the picloram sorption and desorption capacity of soils and to determine soil groups based on the risk of environmental contamination. Physicochemical properties of 17 soils were subjected to principal component analysis (PCA). Thereafter, the soils were grouped by cluster analysis (CA). Discriminant analysis (DA) was used to determine the efficiency of the clusters. The CA generated three groups of soils, and the coefficients of sorption (Kfs) and desorption (Kfd) were 2.85 and 4.29 for G1, 0.93 and 11.71 for G2, and for G3, 0.36 and 30.76 mg^1−1/n L^1/n kg⁻¹, respectively. The similarity of soil physicochemical properties in each group resulted in similar picloram sorption and desorption coefficients. Clay, organic matter, pH, and sum of bases showed the greatest influence on the sorption and desorption of picloram. Grouping soils by PCA and CA based on soil physicochemical properties is an alternative approach to determine the risk of environmental contamination by picloram in agricultural areas.

摘要

有关除草剂与土壤相互作用的知识对于安全使用这些产品至关重要。本研究的目的是评估多变量判别分析预测土壤的毒草胺吸附和解吸能力以及根据环境污染风险确定土壤类别的潜力。对 17 种土壤的理化性质进行了主成分分析 (PCA)。此后，通过聚类分析 (CA) 对土壤进行分组。判别分析 (DA) 用于确定聚类的效率。CA 生成了三组土壤，G1 的吸附系数 (Kfs) 和解吸系数 (Kfd) 分别为 2.85 和 4.29，G2 的吸附系数为 0.93 和 11.71，G3 的吸附系数为 0.36 和 30.76 mg 1−1/n ^L 1 ^{/ n}千克^-1， 分别。各组土壤理化性质的相似性导致了相似的毒草胺吸附和解吸系数。粘土、有机物、pH 和碱的总和对毒草胺的吸附和解吸影响最大。根据土壤物理化学性质，通过 PCA 和 CA 对土壤进行分组是确定农业地区毒菌仑环境污染风险的另一种方法。