In Vivo Yam (Dioscorea spp.) Vine Multiplication Technique: The Plausible Solution to Seed Yam Generation Menace
Bibliographic record
Abstract
A study was conducted to develop a vine multiplication package for generation of seed yam. The parameters assessed for the package were rooting media of the vine cuttings, yam variety and nutrient supplementation to the mother plant to generate minitubers. Nine varieties of yams were planted in 4 media types (soil, soil + sawdust, soil + carbonized rice husk and cocopeat) and 2 levels of nutrient supplementation (no supplementation and supplementation) using RCBD with 3 replications. The study was conducted over 2-year period. Boosting the nutrient status of the mother plant before excising the vines proved to enhance establishment and subsequently the yield of the vine cuttings. Incorporation of biochar in the planting media also enhanced establishment of the vine cuttings and subsequent yields. Success of the vine multiplication techniques also proved to be variety dependent. An in vivo vine multiplication package has been developed for yam seed generation.
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".