Microbiolization of Seeds and Aerial Application With Yeasts for Disease Control in Wheat
Bibliographic record
Abstract
Wheat productivity is compromised by the number of diseases that affect it. The diseases control is basically effected by the use of fungicides, however, biological control has become important due especially to the demand for foods free of chemical compounds. The objective of this work was to evaluate the efficiency of yeasts in reducing diseases through the treatment of wheat seeds and the spraying of plants in the field. The tests were carried out in the field and laboratory, with the yeasts Candida albicans, Cryptococcus laurentii, Pichia guilliermondii, Rhodotorula glutinis, Zygoascus hellenicus and Saccharomyces cerevisiae compared with fungicide (carbendazim) and control with water. In the laboratory, seed health, germination, germination speed index, cold test and accelerated aging were analyzed. In the field, seed treatment and aerial application were carried out when the flag leaf was emitted and the occurrence of diseases, chlorophyll content, production components, productivity and production quality was evaluated. For the variables of production and quality of the wheat in field, the yeast Z. hellenicus was efficient for productivity resembling the fungicide. For the severity of diseases in field, parameters related to germination and seed health, yeasts were not efficient.
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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".