Use of Quantitative and Conventional PCR to Assess Biodegradation of Bovine and Plant DNA during Cattle Mortality Composting
Bibliographic record
Abstract
Understanding mortality composting requires assessing the biodegradation efficacy of carcasses and other materials of animal and plant origin. Biosecure (plastic-wrapped) compost structures were built containing 16 cattle carcasses placed on 40 cm straw and covered with 160-cm of feedlot manure. Compost was collected from depths of 80 and 160 cm (P80, P160) and DNA degradation assessed over 147 days of static composting, and during 180 days of active composting. Residual soft tissues from carcasses were collected on day 147. At P80, copies of a 171-bp bovine mitochondrial DNA (Mt171) and 138-bp plant Rubisco gene fragment (Rub138) were reduced compared to initial copy numbers (CN) by 79% and 99% after 147 days, respectively. At P160, Mt171, and Rub138 decreased compared to initial CN by 20% and 99% by day 147, respectively. After 327 days, degradation of Mt171 increased to 91% compared to initial CN. Compared to fresh tissues, residual tissues at day 147 had a 99% reduction in genomic DNA yield. Yield of DNA was related to copies of a 760-bp bovine mitochondrial fragment (Mt760) which were > 93% reduced at both P80 and P160 after 147 day. Secondary composting improved decomposition of bovine tissues and Mt760 was not detectable after 207 days. A 99% reduction in genomic DNA of composted tissue and > 93% reduction of Mt760 suggests almost complete decomposition of carcass soft tissue after 147 days.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".