Nutrient Contents in Sugarcane Biomass in the First Regrowth Cycle
Bibliographic record
Abstract
Sugarcane extracts and accumulates high amounts of soil nutrients, because it produces large amounts of biomass. Nutrient contents for varieties widely used in the past can be found in the literature, but there is little information on current cultivars. In view of these considerations, the study aimed to determine the nutrient concentration in the shoot biomass of sugarcane varieties in the first regrowth cycle. The study was conducted at a Latossolo Amarelo in Fazenda Jequiá, located in the state of Alagoas, Brazil. The experiment was a randomized block design with five replicates, consisting of four sugarcane varieties: SP813250, RB867515, RB92579 and VAT90212. At maturity of the first regrowth sugarcane, nitrogen (N), phosphorus (P), potassium (K), Ca (calcium), Mg (magnesium), S (sulfur), zinc (Zn), iron (Fe), copper (Cu), manganese (Mn) and Boron (B) contents were determined. Varietal differences were found in nutrient contents. However, no variety showed higher concentration for all the elements. The varieties showed the following order of macronutrient concentrations: K > N > Ca > Mg > S > P. The average values were 0.47, 0.08, 0.66, 0.15, 0.13 and 0.11 dag kg-1 of N, P, K, Ca, Mg and S, respectively. Concentrations of 9.9, 98.7, 29.2, 1.9 and 4.4 mg kg-1 of Zn, Fe, Mn, Cu and B were found for the micronutrients, respectively.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".