Oxygen measurements in the root zone facilitated by TDR
Bibliographic record
Abstract
Deleterious soil structural conditions, as from compaction, can reduce plant growth and yields by reducing aeration and oxygen in the rooting environment. Using a double-membrane oxygen cathode in each of four corn plots, we measured soil oxygen concentrations in duplicate at depths of 5, 10, 20 and 30 cm during the growing season. In addition, temperature, water content and bulk density determinations allowed the monitoring of O2 concentration trends under no-till and conventional-till corn management. Carbon dioxide flux from the soil surface was measured weekly. Temporal patterns of O2 levels fluctuated in response to rainfall at all depths but much less so at 30-cm depth. At 30 cm the O2 concentration remained inadequate for optimum plant growth (<0.01 kg m−3) for over 2 mo after planting under no-till with poorly timed trafficking. Under conventional till and appropriately timed trafficking adequate aeration occurred more than a month earlier than under no-till. The CO2 output was generally lower by 10 to 30% in no-till than that in conventional till, indicating measurably lower levels of biological activity. The relative magnitudes of mid-season O2 concentrations and CO2 flux densities showed the same pattern as the crop yields for all tillage treatments. More analyses of seasonal O2 consumption patterns are required to determine if lack of O2 is a causal factor for the reduced crop yield. Key words: TDR, aeration, oxygen measurement, carbon dioxide, tillage, root zone
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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) | 0.000 | 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) | 0.001 | 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".