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...
Saved in:
| 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: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0016706124003902 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Improving the Accuracy of Soil Classification by Using Vis–NIR, MIR, and Their Spectra Fusion
by: Shuo Li, et al.
Published: (2025-04-01) -
Spectroscopic analysis (UV-VIS-NIR) for predictive modeling of macro and micronutrients in grapevine leaves
by: J.I. Manzano, et al.
Published: (2025-03-01) -
Feature Variable Selection Based on VIS-NIR Spectra and Soil Moisture Content Prediction Model Construction
by: Nan Zhou, et al.
Published: (2024-01-01) -
Modeling UV/Vis Absorption Spectra of Food Colorants in Solution: Anthocyanins and Curcumin as Case Studies
by: Sara Gómez, et al.
Published: (2024-09-01) -
Prediction of technological properties of wheat flour by combination of UV-VIS-NIR spectroscopy and multivariate analysis methods
by: R. A. Platova, et al.
Published: (2024-04-01)