Germination of Forage Seeds Through Cattle as a Natural Propagator
Bibliographic record
Abstract
Currently, sustainable practices combined with an efficient livestock can have benefits for farmers as observed in this study in which the animals themselves spread the seeds in the pasture in order to promote an addition of forage resources in the canopy. The objective of this study was to evaluate seed germination of three forage species [Avena strigosa Schreb (black oat), Calopogonium mucunoides (calopogonium) and Neonotonia wightii (perennial soybean)] following ingestion by cattle. The feces were collected from the animals at intervals of 6 hours up to 48 hours after the ingestion of the seeds. The feces were placed in beds in the field for further germination studies for the next 30, 60 and 90 days (post-planting periods). No difference (P > 0.05) was observed between the treatments species or between post-planting periods of the evaluation. For all the studied seeds, the germination was only verified in the time of up to 30 days after the placement of the feces in the field, where black oats obtained numerically the highest accumulated percentage (during 48 hours) with 10% of germinated seeds. It is concluded that the use of cattle as a disperser of forage seeds can help in the introduction of new forage in order to improve the production and the quality of the pastures. The moment of the cattle entrance in the pickets will depend on the forage species to be introduced and can vary from 6 to 12 hours after the intake of the seeds.
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) | 0.002 | 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".