Selenium Content Characteristics of Surface Soil and Rice Seed in Fujian Province and Prediction of Selenium-Enriched Production Areas

The traditional classification of selenium-enriched land is based solely on soil selenium content, which may lead to omissions and misjudgments. Accurate prediction of selenium content in rice grains can provide a more precise basis for delineating selenium-enriched production areas. This study utilized large-scale soil and rice grain sample data from Fujian Province to establish a selenium content prediction model for rice grains through machine learning. The grid search method was employed to enhance the accuracy of the model's predictions, aiming to provide data support for the regionalization of selenium-enriched soil in the study area. The results indicated that the average selenium content in the surface soil of Fujian Province was 0.34mg/kg, showing strong spatial variability. The proportions of soil in the sufficient selenium and selenium-enriched states were 62.83% and 27.05%, respectively, with no selenium poisoning observed. Soil selenium content has a strong inheritance from parent material, with higher selenium content in soils developed from high-selenium rocks such as coal-bearing strata and siliceous rocks. The selenium-enriched rate of rice grains in the sampling area was 44.09%, while the selenium-enriched rate of the corresponding root zone soil was only 10.54%. Soil pH, iron oxide content, organic matter content, phosphorus content, rainfall, and temperature were important factors influencing the selenium bioaccumulation coefficient in rice grains. By comparing the prediction results of the random forest model with those of the traditional multiple linear regression model (MLR), the root mean square error (RMSE) of the random forest model was 0.018, lower than that of MLR model (0.096), and the correlation coefficient (R) was 0.957, higher than that of the MLR model (0.653). The performance of the random forest model was significantly superior to that of MLR model. Based on the optimized random forest model, the selenium-enriched production areas in Fujian Province were classified into priority development areas and potential development areas. The priority development areas for selenium-enriched rice in this province are mainly located in the northwest of Ningde City, the west of Sanming City, and the central and southern parts of Zhangzhou City, while the potential development areas are mainly in the central and southern parts of Nanping City and the central part of Sanming City.