The fusion of machine olfactory data and UV–Vis-NIR-MIR spectra enabled accurate prediction of key soil nutrients

The fusion of machine olfactory data and UV–Vis-NIR-MIR spectra enabled accurate prediction of key soil nutrients

Conventional approaches for evaluating soil nutrients typically involved lengthy and resource-intensive analytical procedures, rendering them inadequate for large-scale and high-throughput testing. To address these limitations, this study proposed an innovative solution based on sensor data fusion t...

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Bibliographic Details
Main Authors: Shuyan Liu, Lili Fu, Xiaomeng Xia, Jiamu Wang, Yvhang Cao, Xinming Jiang, Honglei Jia, Zengming Feng, Dongyan Huang
Format: Article
Language:English
Published: Elsevier 2025-01-01
Series:Geoderma
Subjects:
Soil nutrient content
Multi-source data
Fusion strategy
Machine learning
Online Access:http://www.sciencedirect.com/science/article/pii/S0016706124003902
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http://www.sciencedirect.com/science/article/pii/S0016706124003902

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