120 Yield and nutritive value of cool- and warm-season forage forb species grown under greenhouse conditions.
Bibliographic record
Abstract
Abstract Forage systems in the southeastern United States face challenges due to seasonal fluctuations in forage availability, particularly during transitions from summer to winter and winter to summer. These gaps can negatively impact livestock nutrition and productivity. Forbs offer a potential solution due to their adaptability, nitrogen-fixing capabilities, and high nutritive value. However, their adoption remains limited due to inconsistencies in establishment, growth rates, resilience to environmental stress, and potential anti-nutritional effects associated with secondary plant metabolites (PSM). The role of forbs in livestock nutrition and sustainable agriculture is underexplored, necessitating further research to assess their agronomic potential and nutritional value under controlled conditions. This study aimed to evaluate the yield and nutritive value of commercially available and native forb species known to produce PSM. A randomized complete block design was implemented with three blocks for each season. Cool-season species were grown in 72 (3.8 L) pots, while warm-season species were planted in 36 (15.1 L) pots, each filled with a standardized soil mix. Drip irrigation was applied daily to maintain optimal moisture conditions. Biomass was harvested at 30 cm canopy height for cool-season species and at 25% flowering for warm-season species, with clippings taken 15 cm above the soil surface. Laboratory analyses were conducted to determine dry matter, crude protein (CP), detergent fiber fractions (NDF, ADF, and ADL), and secondary metabolite concentrations (e.g., tannins, flavonoids). There was variability among forb species in both yield and nutritive value in each season. Among warm-season forbs, sunn hemp exhibited the greatest yield (P < 0.05), followed by cowpea, panicled leaf tick trefoil, and lablab, whereas maximilian sunflower consistently failed to establish. Sunn hemp, cowpea, panicled leaf, sericea lespedeza, and lablab had the greatest fiber fractions (P < 0.05), with sericea lespedeza exhibiting the greatest lignin concentration. White sweet clover had the greatest NDF concentration in the cool season, while berseem clover, white sweet clover, and hairy vetch had the greatest ADF concentrations. Chicory and berseem clover exhibited the greatest lignin levels. Hairy vetch had the greatest CP concentration among cool-season species at 29%, while fenugreek had the greatest among warm-season species at 20%. In the cool season, ball clover produced the greatest yield (P < 0.05), followed by red clover, kale, and berseem clover, while white lupin and swede failed to establish. These findings suggest that certain forb species could contribute meaningfully to forage systems by enhancing nutritional value and biomass availability during critical seasonal transitions. The top-performing species identified in this study will serve as the foundation for subsequent field-based trials to evaluate their adaptability under varying environmental conditions and their effects on animal performance.
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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".