2,4-Dichlorophenoxy Acetic Acid Mineralization in Amended Soil
Bibliographic record
Abstract
The application of municipal biosolid or liquid hog manure to agricultural soils under laboratory conditions at 20 degrees C influenced the fate of the herbicide 2,4-D [2,4-(dichlorophenoxy)acetic acid] in soil. When 2,4-D was added to soil at agronomic rates immediately after the addition of manure or biosolids to a coarse-textured soil, the percentage of 2,4-D mineralized at 100 days was about 47% for both treatments, compared to only 31% for control soils without amendments. The enhanced 2,4-D mineralization as a result of amendment addition was due to an increased heterotrophic microbial activity, with the greatest increases in soil respiration occurring for soils amended with biosolids. When additions of 2,4-D were delayed for one, two, or four weeks after the amendments were applied, the additions of amendments generally reduced 2,4-D mineralization in soil, particularly for manure, indicating that the effect of amendments on enhancing soil microbial activities diminished over time. In contrast, the mineralization of 2,4-D in control soils was less dependent on when 2,4-D was applied in relation to pre-incubations of soil for zero, one, two, or four weeks. The effect of manure on decreasing 2,4-D mineralization in specific soils was as large as the effect of soil texture on differences in 2,4-D mineralization across soils. Because manure was not found to impact 2,4-D sorption by soil, it is possible that 2,4-D mineralization decreased because 2,4-D transformation products were strongly sorbed onto organic carbon constituents in manure-amended soils and were therefore less accessible to microorganisms. Alternatively, microorganisms were less likely to metabolize the herbicide because they preferentially consumed the type of organic carbon in manure that is a weak sorbent for 2,4-D.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".