Nutrients Use Efficiency and Uptake Characteristics of Panicum virgatum for Fodder Production
Bibliographic record
Abstract
Panicum virgatum could produce cattle feed with lower costs due to the low input requirements and its perennial nature. Dry biomass yield vs. N-P-K nutrient uptake relations as well as the N-mineralization and the N-fertilization recovery fraction for Panicum virgatum (cv. Alamo) were determined under field conditions for four N-fertilization (0, 80, 160 and 240 kg ha-1) and two irrigation levels (0 and 250 mm), οn two soils in central Greece with rather different moisture status. It was found that the dry fodder yield on the aquic soil may reach 14 t ha-1 using supplemental irrigation; while on the xeric soil a lower yield of 9-10 t ha-1 may be produced only under supplemental irrigation. Moreover, the average N, P and K concentration was 1.3%, 0.14% and 1.3% in leaves, and 0.5%, 0.85%, and 1.5% in stems, respectively, showing the very low crop requirements. Furthermore, linear biomass yield-nutrient uptake relationships were found with high R2, pointing to nutrient use efficiency of 132 and 75 kg kg-1, for N and K respectively. The base N-uptake ranged from 71-74 kg ha-1 on the aquic to 60 kg ha-1 or less on the xeric soil. Finally, it was found that N-recovery fraction was 20% on the aquic soil and lower on the xeric. Therefore, it could be conclude that Panicum virgatum seems to be a very promising crop for fodder production and its introduction in land use systems (especially οn aquic soils of similar environments) should be taken into consideration.
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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 | 0.000 |
| 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".