Effect of soil temperature and moisture on soil test P with different extractants
Bibliographic record
Abstract
Song, C., Zhang, X., Liu, X. and Chen, Y. 2012. Effect of soil temperature and moisture on soil test P with different extractants. Can. J. Soil Sci. 92: 537–542. Temperature and moisture are important factors affecting adsorption, transformation and the availability of soil phosphorus (P) to plants. The different temperatures and moisture contents at which soil is sampled might affect the results of soil test P (STP). In order to evaluate the effect of the temperature and moisture, as well as the fertilization level, on the results of soil test P, an incubation study involving three soil temperatures (5, 10, and 20°C), and three soil moisture contents (50, 70, 90% of field water-holding capacity) was conducted with Chinese Mollisols collected from four fertilization treatments in a long-term experiment in northeast China. Four soil P test methods, Mehlich 3, Morgan, Olsen and Bray 1 were used to determine STP after a 42-d incubation. The effect of temperature and moisture on STP varied among soil P tests. Averaged across the four fertilization treatments, the temperature had significant impact on STP, while the responses varied among soil P test methods. Mehlich 3, Morgan and Bray 1 STP decreased and Olsen STP increased with increase in temperature. Effect of soil moisture was only significant for Mehlich 3 P and Olsen P. Soil temperature had greater impact on STP than soil moisture content. The responses of the Olsen method to temperature differed from the other three methods tested. The interaction between soil temperature and soil moisture on soil test P was only significant for Mehlich 3 P. Fertilization level does not affect the STP in as a clear pattern as the temperature and moisture varied for all four methods. Consistent soil sampling conditions, especially the soil temperature, appear to be the first step to achieve a reliable STP for any soil P test.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".