Performance of Corn Hybrids as a Function of Nitrogen Doses and Trichoderma Harzianum
Bibliographic record
Abstract
This study aimed to assess the performance of commercial corn hybrids with the application of Trichoderma harzianum under varying nitrogen levels. The experiment was conducted at the State University of Goiás, Campus Sul, during the 2022/23 harvest. The experimental design employed a factorial scheme 9 x 3, involving nine commercial hybrids and three nitrogen doses, randomized in blocks with three replications. Three nitrogen doses were applied: control (160 kg ha-1 of nitrogen), low nitrogen (80 kg ha-1 of nitrogen), and low nitrogen (80 kg ha-1 + Trichoderma harzianum). The evaluation encompassed ear height, plant height, relative chlorophyll index, stem diameter, number of rows, number of lines, and dry grain mass. The hybrids 2M77, 2M80, P3898, and P4285 exhibited superior efficiency with 80 kg ha-1 of nitrogen, while DKB390 and P3898 demonstrated the highest responsiveness to the recommended dose of 160 kg ha-1 of nitrogen. The inoculation of Trichoderma harzianum, combined with 80 kg ha-1 of nitrogen, resulted in increased grain mass, in the hybrids 30A91PW, DKB390, GNZ7280, P4285, and RK3014, with variable benefits across different characteristics. However, it is advisable to limit the use of Trichoderma harzianum to these specific commercial cultivars.
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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".