Forage growth, yield and nutritional characteristics of four varieties of napier grass (Pennisetum purpureum Schumach) in the west Usambara highlands, Tanzania
Bibliographic record
Abstract
Low pasture biomass production and dry seasons fodder scarcity are among the major challenges affecting productivity of dairy cattle in Tanzania. Field experiments were set to evaluate growth, biomass yields and nutritional contents of four napier grass (Pennisetum purpureum Schumach) varieties as feed for ruminants. Experimental napier varieties included Ouma, Kakamega 2 (KK2), Bana and local napier (LN). The study was conducted in the Western Usambara highlands (WUHs) in Tanzania between December 2016 and April 2017 (110 days). The results indicated that the varietal mean stem heights differed significantly (P<0.001); whereby LN, Ouma, KK2 and Bana had mean heights of 210.81, 185.72, 177.15 and 145.44 cm respectively. There was a significant difference (P = 0.025) in the mean total forage biomass production in which KK2, LN, Ouma and Bana yielded 16,551, 14,035, 12,868 and 8954 kg dry matter/ha respectively. The crude protein content averaged 9.92% and did not differ significantly across the varieties (P = 0.83). The mean metabolizable energy was 7.94 MJ/kg dry matter and did not differ significantly across the varieties (P = 0.11). The in vitro organic matter digestibility differed significantly (P = 0.03); 65.87, 59.22, 58.33 and 55.41% for Ouma, Bana, KK2 and LN respectively. This study demonstrates that Ouma and KK2 can be established in the WUHs for forage use due to higher biomass production. Further studies on ensiling and animal feeding would provide valuable information for optimizing forage conservation and animal performance in the WUHs and elsewhere with similar conditions.
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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) | 0.000 | 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".