Nitrate Nitrogen Quantification via Ultraviolet Absorbance: A Case Study in Agricultural and Horticultural Regions in Central China
Bibliographic record
Abstract
Soil nitrate nitrogen (NO3−-N) is a key indicator of agricultural non-point source pollution. The ultraviolet (UV) dual-wavelength method is widely used for NO3−-N detection, but interference from complex soil organic matter affects its accuracy. This study investigated how organic matter influences NO3−-N detection by optimizing UV dual-wavelength combinations. Density functional theory (DFT) calculations showed slight spectral broadening of fulvic and humic acids in the presence of NO3−-N under UV spectrum. Standard solutions and soil samples were used to compare the detection performance of different wavelength pairs. The findings indicated that the dual-wavelength combination of 235 nm/275 nm is optimal rather than 220 nm/275 nm for measuring soil samples at NO3−-N concentrations exceeding 5 mg·L−1. The 235/275 nm method gave an average calibration coefficient of 1.57. Compared to the national standard and flow analysis methods, the average relative errors were 19.7% and 22.3% (p < 0.001), respectively, indicating its suitability for practical soil applications. These results demonstrate the method’s potential for rapid and accurate NO3−-N detection in real soil samples, supporting its application in environmental monitoring and agricultural management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".