Effect of Rates and Sources of Nitrogen on the O×G Hybrid (Elaeis oleifera × Elaeis guineensis) of Oil Palm at the Adult Stage
Bibliographic record
Abstract
Although N is one of the two nutrients most required by oil palms and is determinant for crop growth and yield, more than half of the N applied can be lost to the environment, increasing production costs, decreasing its use efficiency, and causing air pollution through volatilization and greenhouse gas emissions. In addition, fertilization can account for up to 46% of total costs in E. guineensis cultivars and 39% in O×G interspecific hybrid cultivars in Colombia; therefore, selecting the right source and rate is considered crucial for agribusiness. In this regard, the objective of this study was to evaluate the effect rates and sources of nitrogen on the O×G interspecific hybrid of oil palm during the adult stage in terms of soil variables, nutrition, growth, FFB yield, N use efficiency, and N losses due to volatilization. Analysis of the results after five years of evaluation indicated that the use of PMCRU and PMCU did not promote significant effects on soil chemistry; however, it did have effects on nutrition, growth, FFBY, N use efficiency, and N losses due to volatilization in O×G hybrid oil palm in the productive stage according to the Tukey test at 5%. PMCRU allowed the biological optimum to be achieved with a rate of 134 kg ha-1 of N, while PMCU required the maximum rate of N evaluated (192 kg ha-1 of N). In addition, PMCRU was more efficient. In turn, the use of PMCRU can reduce N volatilization by between 92.3 and 88.9% for rates of 96 and 192 kg ha-1 of N, respectively. The use of PMCRU is a feasible alternative for the nutrition of the interspecific hybrid O×G during the adult stage in the Eastern Zone of Colombia, allowing higher yields to be achieved with lower rates of N and reducing N losses due to volatilization.
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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".