A predictive model for arsenic accumulation in rice grains based on bioavailable arsenic and soil characteristics

Arsenic (As) is a well-known human carcinogen, and rice consumption is the main way Chinese people are exposed to As. In this study, 14 kinds of paddy soils were collected from the main rice-producing areas in China. The results showed that rice roots and leaves accumulated more As than stems and grains in the following sequence: Asroot Asleaf > Asstem > Asgrain. The accumulation of As by rice grains mainly depends on the total As and bioavailable As (0.43 mol/L HNO3 extractable As), which explained 32.2% and 22.2% of the variation in the grain As, respectively. In addition, soil pH, organic matter (OM) and clay contents were the major factors affecting grain As, explaining 13.1%, 7.9% and 5.3% of the variation, respectively. An effective prediction model was established via multiple linear regression as Asgrain = 0.024 BAs - 0.225 pH + 0.013 OM + 0.648 EC - 0.320 TN - 0.088 TP - 0.002 AS + 2.157 (R2 = 0.68, P < 0.01). Through the verification of the samples from both pot experiments and paddy fields, the model successfully provided accurate predictions for rice grain As.

Automated summary

The study found that arsenic accumulation was higher in rice roots and leaves, and factors affecting grain arsenic content included total arsenic, soil pH, organic matter, and clay content. An effective prediction model was established using multiple linear regression, successfully predicting rice grain arsenic content.