Allium cepa assay based comparative study of selected vegetables and the chromosomal aberrations due to heavy metal accumulation
Bibliographic record
Abstract
Irrigation of industrial effluents may end in the bioaccumulation of various toxic metals and consequent genetic changes in contaminated food crops. To test this hypothesis and extent of genetic modifications, Allium cepa test was performed to food crops viz. tomato (Lycopersicum esculentum) and chili (Capsicum annum) as Allium cepa test is a useful tool to assess genetic variations in plants. Prior to A. cepa test, the plants were exposed to various metal concentrations 125–1000 mg/L in the synthetic wastewater. The extracts of harvested plants were used to grow the root of A. cepa following its standard method. The root tips were fixed, stained and examined under compound microscope (almost 300–400 dividing cells) to check the extent of chromosomal variations during various stages of mitosis. The results revealed various chromosomal abnormalities including laggards, stickiness, vagrant chromosomes, binucleated cells, nuclear lesions, giant cells and c-mitosis at different level of treatment. On the whole, aberrations were increasing with the increasing doses along the positive control. In comparison, chili crop had higher level of aberrations depicting the higher chromosomal changes. Lower mitotic index (MI) with increasing level of doses was also describing the hampered cell division due to increased metal stress. The study is showing that the cell division was ceased with increasing metal stress thus increasing the rate of cell aberrations.
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 | 0.001 | 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".