23 Effect of species on yield potential and nutritive value of cool- and warm-season forage forb species
Bibliographic record
Abstract
Abstract Forbs have significant potential to address the seasonal forage gaps that arise during the transitions from summer to winter and winter to summer, offering a practical solution to the challenges of maintaining consistent livestock nutrition year-round. Their adoption is limited by variability in growth rates, resilience to environmental stress, and the potential anti-nutritional effects of secondary metabolites (PSM) leading to their role in livestock nutrition and sustainable agriculture being underappreciated. The objective of this study was to evaluate the influence of controlled environmental conditions on the yield and nutritive value of commercially available and native forb species known to produce PSM. The experiment was a randomized complete block design, with three repetitions for each season. A total of 72 (3.8 L) pots for cool-season species, and 36 (15.1 L) pots for warm-season species were filled with a standardized soil mix. Water was administered daily via a drip irrigation system to maintain optimal growth conditions. Biomass was harvested at 30 cm canopy height for cool-season species and 25% flowering for warm-season species, clipped at 15 cm above the soil surface. Dry matter, crude protein, detergent fiber fractions, and secondary metabolite concentrations (e.g., tannins, flavonoids) were analyzed using established laboratory methods. The results revealed significant variability among forb species in yield and nutritive value. For warm-season forbs, sunn hemp exhibited the greatest yield (P < 0.05), followed by cowpea, panicled leaf tick trefoil, and lablab, while fenugreek and maximillian flower consistently failed to establish. Sunn hemp, cowpea, panicled leaf, sericea lespedeza, and lablab also had the greatest fiber fractions, with sericea lespedeza leading with the greatest lignin fraction. There were no differences among species for dry and organic matter concentrations. In the cool season, ball clover had the greatest yield (P < 0.05), followed by red clover, kale, and berseem clover. White lupin and swede consistently failed to establish. For fiber fractions, white sweet clover had the greatest NDF, berseem clover and white sweet clover and hairy vetch had the greatest ADF concentrations, while chicory and berseem clover had the greatest lignin. Top-performing species will serve as a foundation for subsequent field-based trials. Future research will focus on the integration of these species into forage systems and their effects on animal performance and metabolism.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".