Sugarcane Varieties for Animal Feeding in the Pre-Amazon Region of Brazil
Bibliographic record
Abstract
The expansion of agricultural frontiers in Brazil has resulted in the growth of ruminant production in the Pre-Amazon Region. However, this production is favored mainly in the rainy season, due to the greater supply of pasture for the animals. This fact limits the maintenance of production due to the lack of quality forage for the animals throughout the year. This work aimed to evaluate the nutritional value of the different sugarcane varieties for animal feeding during four crop cycles. In this experiment, the varieties RB 92579, RB 867515 and RB 863129 were studied for cane plant, first, second and third ratoons. The experiment was divided in four stages according to each cycle, and each cycle lasted approximately 10 to 11 months. For the productivity analysis and other parameters samples were collected at the end of each experimental cycle, when the dry matter (DM), crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), Brix, NDF/Brix and produtctivity were determined. The RB 92579 variety showed higher productivity (P < 0.05) in all the studied cycles, and remained above the national productivity average in all the cycles (±75 ton ha-1). This same variety, presented the best results for all nutricional parameters (DM, CP, NDF, ADF and FDN/Brix) when compared to the other varieties. The productivity/nutritional relation value must be taken into account when choosing a variety for animal feeding, being the RB 92579 variety the most expressive, during four cycles, wich lasted 4 years.
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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 | 0.001 | 0.001 |
| 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".