Determining and mapping the spatial mismatch between soil and rice cadmium (Cd) pollution based on a decision tree...

Area of Science:

• Environmental Science
• Soil Science
• Agricultural Science

Background:

• Environmental complexity creates spatial variations in heavy metal soil and rice contamination.
• These spatial differences critically impact rice safety and regional management strategies.
• Scientifically identifying these spatial disparities is an urgent research need.

Purpose of the Study:

• To explore the spatial mismatch between soil and rice grain cadmium (Cd) pollution.
• To reveal the causal factors and recognition rules governing this spatial relationship.
• To provide references for accurate spatial identification and targeted prevention of heavy metal pollution.

Main Methods:

• Utilized interpolation methods to investigate the spatial mismatch of Cd pollution.
• Employed a decision tree model to extract recognition rules for Cd spatial relationships.
• Mapped the spatial distribution and identified key environmental factors.

Main Results:

• A significant spatial mismatch in Cd pollution between soil and rice grains was observed.
• Key findings include: 68.88% slight soil/safe rice, 13.39% slight soil/serious rice, 11.63% safe soil/serious rice.
• Identified 11 recognition rules with an average accuracy of 75.90%, highlighting Soil Organic Matter (SOM), distance from residential areas (Dis-residence), soil pH, and Leaf Area Index (LAI) as main factors.

Conclusions:

• The study successfully revealed the spatial mismatch of heavy metal pollution in soil and rice.
• The identified environmental factors provide crucial insights into Cd accumulation in rice.
• Results offer decision-making references for precise spatial identification and targeted prevention of heavy metal pollution issues.