In this study the transfer characteristics of mercury (Hg) from a wide range of Chinese soils to corn grain (cultivar Zhengdan 958) were investigated. Prediction models were developed for determining the Hg bioconcentration factor (BCF) of Zhengdan 958 from soil, including the soil properties, such as pH, organic matter (OM) concentration, cation exchange capacity (CEC), total nitrogen concentration (TN), total phosphorus concentration (TP), total potassium concentration (TK), and total Hg concentration (THg), using multiple stepwise regression analysis. These prediction models were applied to other non-model corn cultivars using a cross-species extrapolation approach. The results indicated that the soil pH was the most important factor associated with the transfer of Hg from soil to corn grain. Hg bioaccumulation in corn grain increased with the decreasing pH. No significant differences were found between two prediction models derived from different rates of Hg applied to the soil as HgCl₂. The prediction models established in this study can be applied to other non-model corn cultivars and are useful for predicting Hg bioconcentration in corn grain and assessing the ecological risk of Hg in different soils.

The key activity to build semantic web is to build ontologies. But today, the theory and methodology of ontology construction is still far from ready. This paper proposed a theoretical framework for massive knowledge management - the knowledge domain framework (KDF), and introduces an integrated development environment (IDE) named large-scale ontology development environment (LODE), which implements the proposed theoretical framework. We also compared LODE with other popular ontology development environments in this paper. The practice of using LODE on management and development of agriculture ontologies shows that knowledge domain framework can handle the development activities of large scale ontologies. Application studies based on the principle of knowledge domain framework and LODE was described briefly.