Technological Quality of Dual-purpose Wheat Submitted to Successive Defoliations
Bibliographic record
Abstract
Defoliation may interfere in the sink-source relationship and influence grain production and the respective technological quality of wheat flour, particularly in cultivars with potential as forage and in subsequent grain production. This study aimed to determine the effects of plant cutting heights and number of cuttings on the technological wheat flour quality of BRS Umbu and BRS Tarumã cultivars. A completely randomized design with four repetitions was used and treatments consisted of a combination of cutting heights (20 and 30 cm) and number of cuttings (no cutting, 1, 2 and 3 cuttings), resulting in the following treatments: 20/1, 20/2, 20/3 30/1, 30/2, 30/3 and controls with no cuttings. Hectoliter weight, grain crude protein, tenacity: extensibility ratio, gluten strength, falling number and wet gluten were measured. Regardless of the cutting height used, and after defoliation, the variables exhibited higher values than in non-defoliated plants, with protein content increasing by 6 and 11.3% for the BRS Tarumã and BRS Umbu cultivars, respectively. As such, it can be inferred that defoliation does not negatively affect the technological quality of wheat flour grown in a dual-purpose system.
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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 | 0.001 |
| 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".