Surface modeling of soil antibiotics.

Area of Science:

• Environmental Science
• Soil Science
• Analytical Chemistry

Background:

• Intensive vegetable cultivation often leads to persistent veterinary antibiotic residues in soils.
• Spatial heterogeneity of these residues poses challenges for accurate interpolation and risk assessment.
• Understanding residue distribution is crucial for managing environmental and health risks.

Purpose of the Study:

• To develop and evaluate an effective interpolator for predicting the spatial distribution of soil antibiotic residues.
• To assess the impact of incorporating vegetable types into interpolation models.
• To compare the performance of High Accuracy Surface Modeling (HASM) with traditional methods.

Main Methods:

• Collected 100 surface soil samples from an intensive vegetable cultivation area in East China.
• Analyzed fluoroquinolones (FQs) including ciprofloxacin (CFX), enrofloxacin (EFX), and norfloxacin (NFX).
• Developed and applied High Accuracy Surface Modeling (HASM) combined with vegetable type data, comparing it with Kriging with External Drift (KED), Stratified Kriging (StK), Ordinary Kriging (OK), and Inverse Distance Weighting (IDW).

Main Results:

• Vegetable type significantly improved interpolator performance.
• HASM demonstrated lower Mean Absolute Errors (MAE) and Root Mean Square Errors (RMSE) for total FQs and individual antibiotics compared to KED, StK, OK, and IDW.
• HASM produced more detailed and accurate spatial distribution maps of soil antibiotics.

Conclusions:

• HASM, when integrated with vegetable type information, is a superior method for interpolating soil antibiotic residues.
• This approach enhances the accuracy of spatial predictions, aiding in risk assessment and management strategies.
• Incorporating auxiliary information like crop type is vital for improving geostatistical modeling in environmental studies.