Yield Responses of Upland Rice Varieties to Low N Conditions in Central Kenya
Bibliographic record
Abstract
Growth, yield, and yield components of five upland rice varieties (MWUR 1, MWUR 4, NERICA 1, NERICA 4, and IRAT109) were evaluated under four different soil N conditions (0, 26, 52, and 78 kg N/ha) to identify the factors contributing to their adaptability to low soil-fertility. The results showed that MWUR 1, MWUR 4, and NERICA 4 had greater adaptability to low N conditions. Specifically, MWUR 1 showed the highest adaptability to low soil fertility. The greater low soil-fertility adaptability of these varieties was attributed to their ability to maintain dry matter production. Furthermore, their greater dry matter production under low N conditions could be attributed to the increased root length, which allowed improved soil nutrient absorption. Our findings suggest that rice grain yield was mainly restricted by sink size, particularly panicle number per plant under low N conditions. The higher grain yield of MWUR 1 under low N conditions could be attributed to greater tillering ability. Thus, MWUR 1 could be a good candidate for cultivation under nutrient-poor soil conditions.
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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".