Inoculation of Wheat With Azospirillum spp.: A Comparison Between Foliar and In-furrow Applications
Bibliographic record
Abstract
The present work aimed to evaluate the agronomic performance of wheat grown under no-tillage system and submitted to different doses and methods of inoculation with Azospirillum spp. Eight treatments were tested: 1) control; 2) half N dose; 3) full dose of N; 4) half N dose + standarded inoculation by seeds (200 mL ha-1); 5) half N dose + in-furrow inoculation (200 mL ha-1); 6) half N dose + in furrow inoculation (300 mL ha-1); 7) half N dose + inoculation by foliar spraying (200 m ha-1) and 8) half N dose + inoculation by foliar spraying (300 mL ha-1). The following parameters were evaluated: number of tillers per plant, number of grains per spike, shoot dry biomass, weight of thousand seed mass, hectoliter weight, nitrogen content in grains, nitrogen content in shoot dry matter as well as crop yield. Our results showed that the supply of the half dose of mineral N associated to foliar inoculation with Azospirillum at the dose of 300 mL ha-1 provided positive results on wheat yield, confirming the bacterial ability to fix N. However, only the full mineral N fertilization stood out as the best N fertilization management.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".