The quality of farm-scale alfalfa silages
Bibliographic record
Abstract
Received: 2015-11-03  |  Accepted: 2016-01-29  |  Available online: 2016-05-30 dx.doi.org/10.15414/afz.2016.19.02.54-58 The aim of the work was to determine the nutritive and fermentation quality of farm-scale alfalfa silages from West part of Slovakia, analyzed in 2014 on the Department of Animal Nutrition, Faculty of Agrobiology and Food Resources, Slovak University of Agriculture in Nitra. In alfalfa silages, we found the average dry mater content 372.66 g.kg -1 , while 30 % of samples had lower dry mater content than 350 g.kg -1 . Only 15 % of samples had higher content of crude protein than 200 g. We don't found content of ADF lower than 300 g.kg -1 of DM in any sample. In alfalfa silages was higher content of NDF than 37.5 % in 70 % of alfalfa silages. The lactic acid content was higher than 10 g of the original mater in all samples except one, ranged from 0.73 to 14.67 % on a dry matter basis. Average content of acetic acid was 29.82 g.kg -1 of DM. Undesirable butyric acid was found in 35 % of samples with average content 8.44 g.kg -1 of DM, with maximal content 108.25 g.kg -1 of DM. Keywords : alfalfa, silage, nutritive value, fermentation, quality References Baumont, R. (1996) Palatability and feeding behaviour in ruminants. A review. Annales de Zootechnie , vol. 45, no. 5, pp. 385-400. doi: http://dx.doi.org/10.1051/animres:19960501 BÃro, D. et al. (2010) Influence of bacterial-enzyme additive on fermentation process of faba bean, alfalfa and oat mixture silages. In Forage Conservation . Brno 17-19.3. 2010 . Brno: Mendel University, pp. 145-147. BÃro, D. et al. (2014) Conservation and Adjustment of Feed . Nitra: Slovak University of Agriculture (in Slovak). Daniel, J. L. P. et al. (2013) Performance of dairy cows fed high levels of acetic acid or ethanol. Journal of Dairy Science , vol. 96, no. 1, pp. 398-406.  doi: http://dx.doi.org/10.3168/jds.2012-5451 Doležal, P. et al. (2012) Feed Conservation . 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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".