194 Variation in native forage chemical composition, in vitro fermentation, and methane emissions across phenological stages.
Bibliographic record
Abstract
Abstract This study examined the effects of phenological development on forage chemical composition and in vitro ruminal fermentation of native grasses in the Mixed Prairie of Western Canada. Six grass species, including three cool-season (Pascopyrum smithii [Rydb.] A. Love, Hesperostipa comata [Trin. & Rupr.] Backworth, Koeleria macrantha [Ledeb.]) and three warm-season (Bouteloua gracilis [Kunth] Lag. Ex Griffiths, Calamovilfa longifolia [Hook.] Scribn, and Distichlis spicata [L.] E. Greene), were harvested in each of June, July, and August of 2022 and 2023. All data analyses were performed in R (R Core Team, 2024). Data were analyzed with linear mixed models, and simple linear regression models were fitted on nutrient chemical composition to predict 48-h in vitro cumulative methane production – mL g-1 dry matter disappearance (DMD). A significant grass species × harvest time interaction was observed for dry matter (DM), crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), and total digestible nutrients (TDN; P < 0.05). Crude protein decreased with advancing phenology for all species except B. gracillis, which was highest in CP in July. A linear increase in ADF (P < 0.001) over time for all species except for K. macrantha which showed a linear decrease through time, B. gracilis which decreased from June to July but increased from July to August, and for C. longifola, which had a quadratic trend that peaked in July. In July and August, NDF was higher compared to June for all species, except B. gracilis which had a higher NDF value in June that decreased through July and August. Concentrations of TDN remained constant across the months for most species, except the early-growing grass H. comata, which decreased through time and for C. longifola which followed a quadratic trend that reached its lowest point in July. K. macrantha yielded a higher in vitro total volatile fatty acid (VFA), acetate:propionate ratio, and greater individual VFA concentrations (P < 0.05) than all other grass species. P. smithii had the greatest DMD while D. stricta had the lowest (P < 0.001). D. stricta produced the greatest in vitro 48-h methane – mL g-1 DMD (P < 0.001) without significant differences across all other species. Forage CP was a significant predictor for 48-h in vitro cumulative methane production across all species except for D. stricta (P < 0.05). All linear relationships between the forage chemical compositions and 48 h cumulative methane production were positive with exception of ADF, DM, and NDF. These data highlight the need to optimize for grazing timing that accounts for temporal and chemical variation and supports the common delayed grazing in these rangelands. The predictive methane models offer necessary information to quantify carbon cycles and enteric emissions of animals grazing these rangelands.
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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".