Responses to Divergent Phenotypic Selection for Fiber Traits in Timothy
Bibliographic record
Abstract
Selection based on fiber traits may make it possible to improve forage digestibility while maintaining plant biomass. Our objectives were to evaluate the effects of divergent phenotypic selection for fiber traits on timothy ( Phleum pratense L.) digestibility, plant biomass, fiber component concentrations and their ratios, and to identify selection criteria that have effective and stable effects on timothy digestibility without affecting plant biomass. Fourteen populations derived by intercrossing plants selected for high or low values of neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL), and cellulose (CEL) concentrations, and for ADL/HEM, ADL/CEL, and ADL/(HEM+CEL) ratios were evaluated in a field experiment. Direct responses for the selected traits were significant for the NDF, CEL, ADL/HEM, ADL/CEL, and ADL/(HEM+CEL) populations. Indirect responses for in vitro true digestibility (IVTD) and in vitro NDF digestibility (IVNDFD) were greatest for the ratios involving ADL. The ADL/CEL selection resulted in the most stable responses across years for IVTD and IVNDFD. Averaged over 2 yr, the IVTD and IVNDFD of the low ADL/CEL population were 27 g kg −1 DM and 33 g kg −1 NDF greater than those of the high ADL/CEL population. Furthermore, the low ADL/CEL population maintained its HEM and CEL concentrations and its plant biomass. Phenotypic selection based on ADL/CEL could be used to improve timothy DM digestibility without reducing plant biomass.
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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 | 0.001 |
| 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) | 0.000 | 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".