Control of Micronutrients Availability in Soil and Concentration in Rice Grain through Field Water Management
Bibliographic record
Abstract
A pot experiment was conducted under different water managements, namely control (continuous flooding condition), 2,3,4WAH (water was drained at two to four weeks after heading), and FCap (the soil moisture was kept at field capacity level, to maintain aerobic soil condition). We examined the influence of the establishment of aerobic soil condition at different timing of rice post-heading stage. The results showed that water managements changed soil redox potential and pH that were known to be responsible of micronutrients availability in soil. Transition from flooding condition to aerobic condition during rice post-anthesis stage, reduced pH toward its initial value as well as Fe availability in soil. Although soil was re-oxidized in 2,3,4WAH treatments, which reduced Fe availability in soil from the level of control treatment, concentration of Fe in grain did not differ between control and drained treatments. Correlation analyses exhibited that the reduction of Fe availability in soil under aerobic condition in 2,3,4WAH and FCap enhanced Zn and Cu availabilities in soil and increased concentration of Zn, Cu and Mn in grain. The results point up toward that, enhancement of micronutrient availability in soil during post-heading stage are strongly associated with its grain micronutrient concentration. Establishment of aerobic condition from two weeks after heading increased the grain Zn, Cu and Mn concentration by 11, 20 and 35 percent respectively over the values in flooding condition, without negative effects on yield parameters. Unlike control and 2,3,4WAH treatments, FCap that kept aerobic soil condition performed high concentration of grain micronutrients but its low yield.
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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) | 0.000 | 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 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".