Inter-row plant spacing effects on grain and fodder yields, growth performance, digestibility and manure quality of sheep
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT In Ghana, peanut (Arachis hypogaea L.) grain and fodder serve as important sources of protein for human and livestock nutrition, respectively. Experiments were conducted in four farming communities to determine the effects of planting annual peanut at four inter-row spacings of 30, 45, 65 and 75 cm on grain and fodder yields (experiment I), growth performance and manure quality (experiment II), and in situ digestibility (experiment III) of Djallonké sheep fed fodder from these plant spacings. Planting peanut at 30 cm inter-row spacing dually increased grain and fodder yields compared to planting at 60, and 75 cm. Peanut fodder from 30 cm inter-row spacing also had comparatively higher concentration of crude protein and lower concentrations of acid detergent fiber and acid detergent lignin, resulting in significant improvements in dry matter digestibility at 48 h and superior average daily weight gain of sheep. The concentration of N excreted in the manure of sheep fed the 30 cm fodder was greater than those fed peanut grown at 60, and 75 cm inter-row spacing. Planting peanut at an inter-row spacing of 30 cm therefore gave dual benefits of increasing grain and fodder yields as well as increasing the digestibility and growth performance of sheep fed peanut fodder as a supplementary diet to natural pasture for 70 days. Higher concentration of N in the manure of sheep fed 30 cm fodder could have additional benefits of improving soil fertility in smallholder farming systems where inorganic fertilizers are expensive and inaccessible to farmers.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.001 |
| 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 it