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September 10, 2025AgricultureOpen Access

Application of Raman Spectroscopy-Driven Multi-Model Ensemble Modeling in Soil Nutrient Prediction

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Authors

XZXiuquan ZhangJWJuanling WangZLZhiwei Li

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Overview

This approach combines advanced preprocessing and regression models to improve soil nutrient predictions, suggesting new methods for soil management.

Key Points

  • Raw_SNV preprocessing with ElasticNet and BayesianRidge models showed optimal prediction performance for soil nutrients.
  • Significant Test R2 values of up to 0.825 for organic matter, highlighting the effectiveness of the modeling system.
  • The study utilized five-fold cross-validation for reliable performance assessment across various nutrient indicators.
  • Findings indicate that Raman spectroscopy can enhance soil nutrient diagnostics, supporting precision agriculture initiatives.

Cite This Study

Zhang et al. (2025) studied this question.

synapsesocial.com/papers/68c198b59b7b07f3a061a263https://doi.org/10.3390/agriculture15171901
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