Improving the nutritive value of timothy through management and breeding
Bibliographic record
Abstract
Timothy (Phleum pratense L.) is a widely grown fo rage grass species in cool and humid regions of the world including northeastern and northwestern North America, Nordic countries, Russia, and Japan. The nutritive value of timothy decreases with time, phenological development, and increasing forage yield. This review paper summarizes methods of controlling or improving the nutritive value of timothy through management practices and genetic selection, while keeping in mind the importance of forage yield. Consequently, the nutritive value of timothy is considered in relation to the accumulation of forage yield. The ecophysiological basis for the decrease in nutritive value with increasing forage yield during a growth cycle is presented with the assumption that the forage is made of two components: metabolic and structural. The decrease in the proportion of the metabolic component with increasing forage yield reduces the nutritive value of timothy. The nutritive value is also affected by the N concentration of the metabolic component, and by the digestibility of the structural component. Harvest dates, growing seasons, N fertilization, and cultivars have an indirect effect on the nutritive value of timothy through increased forage yield and the change in the proportion of the metabolic and structural components, but they also have a direct effect on each component. The results presented demonstrate the possibility of dissociating yield and nutritive value by plant breeding and, therefore, to improve the nutritive value of timothy while maintaining forage yield. Key words: Yield, cultivar, nitrogen, digestibility
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; a candidate call from one teacher head, 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".