Assessing the robustness of VIS-NIR spectroscopy-based soil organic carbon prediction against four wet chemistry methods
A visible and near-infrared (VIS-NIR) spectroscopy-based machine learning model can rapidly predict soil organic carbon (SOC) while minimizing environmental impacts once established. Nevertheless, model reliability has mostly been evaluated statistically, with limited explanation from a soil science...
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| Main Authors: | Cho-Yin Wu, Po-Hui Wu, Zeng-Yei Hseu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Carbon Management |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/17583004.2025.2511337 |
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