The influence of harvest management and fertilizer application on seasonal yield, crude protein concentration and N offtake of grasses in northeast Saskatchewan
Bibliographic record
Abstract
The goal of pasture management is to match quantity and quality of herbage to the requirement of the grazing animal. The objective of this study was to examine the effects of harvest management and fertilizer application on annual and seasonal production, protein concentration and N-offtake by eight grass species adapted to the central Aspen Parkland. In this 3-yr splitsplit- plot experiment, grasses were either fertilized annually (50 and 13 kg ha-1 of N and P, respectively) or left unfertilized, and cut either twice annually (two-cut) in early July and late September, or three to four times annually (multi-cut), in early June, early July, early August and late September if there was sufficient herbage. The grasses used in this study were Altai wildrye [Leymus angustus (Trin.) Pilger], creeping red fescue (Festuca rubra L. var. rubra), meadow bromegrass [Bromus riparius (Rehmann)], Russian wildrye [Psathyrostachys juncea (Fisch.) Nevski], smooth bromegrass (Bromus inermis Leyss.), crested wheatgrass (Agropyron cristatum L. Gaertn.), intermediate wheatgrass [Elytrigia intermedia (Host) Nevski] and green needlegrass [Nassella viridula (Trin.) Barkworth]. Fertilizer increased yield of the two-cut treatment 15% (P < 0.05) more than the multi-cut treatment. On average, the multi-cut treatment had 32% higher protein concentration than the two-cut treatment throughout the season. Fertilizer significantly increased protein concentration only in the first harvest of the multi-cut clipped plots, probably because the application rate was low. Nitrogen offtake of the multi-cut treatment averaged 24% higher than the two-cut treatment, even though the latter yielded more. Meadow bromegrass showed the most uniform seasonal distribution of yield among the high-yielding grasses under all management systems while smooth bromegrass and crested wheatgrass were generally the poorest. Crested wheatgrass had significantly more first cut production than all other grasses. Meadow bromegrass herbage also had the lowest protein concentrations throughout the growing season among the high producing grasses. Since the protein concentrations were generally higher than required by grazing beef cattle, the meadow bromegrass herbage was the most suitable for this class of cattle. Green needlegrass also showed potential for use in pastures. Key words: Pasture, hay, protein yield, Bromus, Elytrigia, Nassella, Agropyron, Festuca, Psathyrostachys, Leymus
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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 | 0.000 | 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".