Determining Chemical Composition of Cattle Urine and Indigenous Plant Extracts
Bibliographic record
Abstract
The study was conducted to determine the specific chemical constituents of cattle urine and indigenous plant extracts. Chemical analysis revealed that the specific chemical composition i.e., chloride, sulphate, nitrite and phosphorus pentaoxide contents of fresh and fermented cattle urine were 1556, 364, 2.0, 26.8 and 4514, 252, 22.4, 7.49 mg l-1, respectively. The proximate chemical compositions of neem seed kernel extracts, mahagoni seed extracts and allamanda leaves extracts were analyzed and it was found to contain chloride (144, 55.4, 141 mg l-1), sulphate (51.1, 5.03, ˂4.0 mg l-1), nitrite (˂1.0, ˂1.0, ˂1.0 mg l-1) and phosphorus pentaoxide (413, 410, 49.5 mg l-1), respectively. Chloride and nitrite in fermented cattle urine (4514 and 22.4 mg l-1) was found extremely higher than in fresh cattle urine (1556 and 2.0 mg l-1). There was numerically higher difference in sulphate and phosphorus pentaoxide concentrations in fresh cattle urine (364, 26.8 mg l-1) compared to fermented cattle urine (252, 7.49 mg l-1).These results revealed that indigenous plant extracts of neem seed kernel, mahagoni seed and allamanda leaves contents chloride, sulphate and nitrite were extremely lower than in both fresh and fermented cattle urine but there were great difference in phosphorus pentaoxide concentration (413, 410, 49.5 mg l-1) in both fresh and fermented cattle urine (26.8, 7.49 mg l-1) composition. It was evident from this study that as the fermented cattle urine contained higher concentration of chloride and nitrite can be considered as a good means of insect pest management.
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 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 | 0.000 | 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 teacher head, 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".