ArticleScientific reports2024
Prediction of soil organic carbon and total nitrogen affected by mine using Vis-NIR spectroscopy coupled with machine learning algorithms in calcareous soils.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Latent Conditional Diffusion-Based Data Augmentation for Small-Sample Hyperspectral Prediction of Forest Soil Organic Carbon.Sensors (Basel, Switzerland) · 2026Article
- In Situ Rapid Detection of Soil Nitrate Nitrogen via Dielectric Spectroscopy Using a Dual-Band Frequency-Splitting Coupled Sensor.ACS sensors · 2026Article
- Soil total nitrogen prediction based on multi-temporal synthetic Sentinel-2 images under different land use types.Scientific reports · 2025Article
- Prediction of Soil Properties Using Vis-NIR Spectroscopy Combined with Machine Learning: A Review.Sensors (Basel, Switzerland) · 2025Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The utilization of visible-near infrared (Vis-NIR) spectroscopy presents a nondestructive, fast, reliable and cost-effective approach to predicting total nitrogen (TN) and organic carbon (OC) levels. This study employed a combination of Vis-NIR spectroscopy, partial least-squares regression (PLSR), and support vector machine (SVM) models to investigate the effects of mining on TN and OC stocks in both the topsoil (0-10 cm) and subsoil (10-40 cm). 105 soil samples were collected from agricultural areas near an iron mine, polluted, moderately-polluted, and non-polluted sites. Results indicated that soils at the non-polluted site had the highest of soil OC stocks (7.5 kg m
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Registered trials
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