Timothy yield and nutritive value with a three-harvest system under the projected future climate in Canada
Bibliographic record
Abstract
Jing, Q., Bélanger, G., Qian, B. and Baron, V. 2014. Timothy yield and nutritive value with a three-harvest system under the projected future climate in Canada. Can. J. Plant Sci. 94: 213-222. Timothy (Phleum pratense L.) is harvested twice annually in Canada but with projected climate change, an additional harvest may be possible. Our objective was to evaluate the impact on timothy dry matter (DM) yield and key nutritive value attributes of shifting from a two- to a three-harvest system under projected future climate conditions at 10 sites across Canada. Future climate scenarios were generated with a stochastic weather generator (AAFC-WG) using two global climate models under the forcing of two Intergovernmental Panel on Climate Change emission scenarios and, then, used by the CATIMO (Canadian Timothy Model) grass model to simulate DM yield and key nutritive value attributes. Under future climate scenarios (2040-2069), the additional harvest and the resulting three-harvest system are expected to increase annual DM yield (+0.46 to +2.47 Mg DM ha-1) compared with a two-harvest system across Canada but the yield increment will on average be greater in eastern Canada (1.88 Mg DM ha-1) and Agassiz (2.02 Mg DM ha-1) than in the prairie provinces of Canada (0.84 Mg DM ha-1). The DM yield of the first harvest in a three-harvest system is expected to be less than in the two-harvest system, while that of the second harvest would be greater. Decreases in average neutral detergent fibre (NDF) concentration (-19 g kg-1 DM) and digestibility (dNDF, -5 g kg-1 NDF) are also expected with the three-harvest system under future conditions. Our results indicate that timothy will take advantage of projected climate change, through taking a third harvest, thereby increasing annual DM production.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".