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Four humic substances were extracted from a peat (HA1) and a volcanic soil (HA2), an oxidized coal (HA3), and a lignite (HA4). The four humic materials presented distinct differences in their chemical and physical−chemical characteristics as assessed by chemical methods, 13C-NMR spectroscopy, and high-performance size exclusion chromatography. The interactions between these well-characterized and purified humic substances and the widely used glyphosate [N-(phosphonomethyl)glycine] herbicide were studied by means of adsorption isotherms. Adsorption of glyphosate was found to be surprisingly high and followed the order HA1 > HA2 > HA3 ≥ HA4. Humic extracts from soil adsorbed glyphosate even more than clay minerals, thereby indicating that the interactions with humic substances, in either a solid or dissolved form, are far more important than previously believed. Adsorption is explained by the multiple hydrogen bondings which can occur among the various acidic and oxygen-containing groups of both molecules. However, the order of adsorption did not simply follow the order of acidity but rather that of increasing aliphaticity and molecular size of humic substances. In fact, the least adsorbing humic materials from nonsoil sources showed a high content of aromatic structures and small molecular dimensions. These results reveal that the extent of glyphosate adsorption on humic substances varies considerably with their macromolecular structure and dimension and that is favored by a high degree of stereochemical flexibility combined with a large molecular size. Keywords: Adsorption; glyphosate; humic substances

Traditional methods for studying tree roots are destructive and labor intensive, but available nondestructive techniques are applicable only to small scale studies or are strongly limited by soil conditions and root size. Soil electrical resistivity measured by geoelectrical methods has the potential to detect belowground plant structures, but quantitative relationships of these measurements with root traits have not been assessed. We tested the ability of two-dimensional (2-D) DC resistivity tomography to detect the spatial variability of roots and to quantify their biomass in a tree stand. A high-resolution resistivity tomogram was generated along a 11.75 m transect under an Alnus glutinosa (L.) Gaertn. stand based on an alpha-Wenner configuration with 48 electrodes spaced 0.25 m apart. Data were processed by a 2-D finite-element inversion algorithm, and corrected for soil temperature. Data acquisition, inversion and imaging were completed in the field within 60 min. Root dry mass per unit soil volume (root mass density, RMD) was measured destructively on soil samples collected to a depth of 1.05 m. Soil sand, silt, clay and organic matter contents, electrical conductivity, water content and pH were measured on a subset of samples. The spatial pattern of soil resistivity closely matched the spatial distribution of RMD. Multiple linear regression showed that only RMD and soil water content were related to soil resistivity along the transect. Regression analysis of RMD against soil resistivity revealed a highly significant logistic relationship (n = 97), which was confirmed on a separate dataset (n = 67), showing that soil resistivity was quantitatively related to belowground tree root biomass. This relationship provides a basis for developing quick nondestructive methods for detecting root distribution and quantifying root biomass, as well as for optimizing sampling strategies for studying root-driven phenomena.

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