Influência da época de plantio e corte na produtividade da cana-de-açúcar.
Bibliographic record
Abstract
Harvest planning in sugarcane attempts to optimize the crop's economic return based on the concept that sugarcane presents, along the cropping season, a period during which the maximum concentration of sucrose occurs in the stalks.This work consisted of studies that focused on the influences of edaphic-climatic factors on yield and total recoverable sugars.The hypothesis was tested that an interaction exists between the planting and harvesting seasons, as well as the hypothesis that an interaction exists between the whole-stalk and the bud seedling treatments with each planting season.Data from a research conducted at COPERSUCAR's Experimental Field -Piracicaba/SP, in a Red Eutrophic Latosol, were used.A random blocks design with strip split-plots was used, where sub-subplots were allocated within strips.Treatments were planting seasons (November, January, March, May), with harvesting seasons represented by strips (May, July, September, November), while sub-subtreatments consisted of bud and whole-stalk seedlings.The variables measured were: tons of sugarcane stalks (TSS) and tons of sugar per hectare (TSH), and total recoverable sugar (TRS).The ratoon (second cut) was evaluated in the same manner as the 1 st cut, when sugarcane was 12 months old.Three experiments were installed, each consisting of one variety: SP 70-1143, NA 56-79, and SP 71-1406.The experiments were installed and xii replicated in three cropping years: 1983/84, 1984/85, and 1985/86, with harvests in the cropping seasons from 1985 through 1988; therefore, yields for the same stage in different years, and yields for different stages in the same year were obtained.It was concluded that planting seasons affected TSS, TRS, and TSH in the 1 st cut; planting seasons interacted with seedling types in one-year-old sugarcane; harvesting seasons affected TSS, TRS, and TSH in one-year-old and ratoon sugarcane; TRS always progressed from the beginning to the end of the cropping season, with peaks in the months of September and November; late plantings delayed maturation; TSH values followed the TRS curves, and were influenced by TSS.In the first cut of variety SP 70-1143, climate influenced the planting season and seedling type results; the smallest TSS values were obtained in the May planting seasons with bud seedlings, while no differences were observed in the other planting seasons, indicating that whole-stalk seedlings can be planted in any season; in both cuts under study, the highest TRS values were obtained for the September harvesting, and the smallest values were obtained for the May planting season, indicating that peak maturity occurs in the month of September.In variety NA 56-79, the TSS values for bud and whole-stalk seedlings did not show differences, indicating that whole-stalk cane can be planted; the highest TRS and TSH values were obtained from harvests made in July.In the first cut of variety SP 71-1406, the best management consisted of bud seedlings, which were superior; the smallest TSS values were obtained for the May planting and the highest TRS value was obtained for the November harvesting; in both cuts, the TSH and TRS values indicated that harvesting should be done beginning in September.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".