Impact of Sample Preservation Methods on the Extraction of Inorganic Nitrogen by Potassium Chloride
Bibliographic record
Abstract
ABSTRACT Accurate measurement of soil mineral nitrogen (N) is essential for making precise N recommendations for grain maize (Zea mays L.) production. Analysis of soil inorganic N is complicated by the fact that these forms of N change rapidly during the sample-processing period. Studies were conducted to evaluate the effects of soil-preservation methods on the changes in inorganic N concentration of soil samples. In 1999 and 2000, soil samples at 0 to 20 cm depth were collected from eight locations representing different soil types. Six preservation methods were evaluated, including an immediate extraction in the laboratory for NH4-N and NO3-N determination, and extraction of samples stored under different preservation methods: frozen at −15°C for 2 months, air dried in a greenhouse for 24 h, oven dried at 20°C for 24 h, oven dried at 40°C for 24 h, and air dried at room temperature at 22°C for 24 h. All preservation methods caused a significant increase in NH4-N and, to a smaller degree, NO3-N concentrations, except freezing, which did not increase NH4-N in 1999. Compared with analysis of fresh samples, soil total inorganic N (NH4-N + NO3-N) was increased, on average, by 10.0 μ g g− 1 in 1999 and 1.4 μ g g− 1 in 2000 for the frozen treatment. Air-drying at room temperature produced the smallest increase, 4.0 μ g g− 1 in 1999 and 2.4 μ g g− 1 in 2000, followed by oven drying at 20°C (4.6 μ g g− 1in 1999 and 3.9 μ g g− 1 in 2000) and oven drying at 40°C (4.3 μg g− 1 in 1999 and 7.1 μ g g− 1 in 2000). Air-drying in the greenhouse produced the greatest increase, 6.0 μ g g− 1 in 1999 and 6.5 μ g g− 1 in 2000. Results of this study indicate that air-drying at room temperature (22°C) for 24 h with subsequent storage in sealed polyethylene containers is a reasonable and relatively reliable method in preserving soil samples for inorganic N, especially for NO3-N in low-mineral N-content soils.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".