Improving Small Weed Seeds Viability Assessment Using Tetrazolium Test
Bibliographic record
Abstract
Tetrazolium testing in small seeds demands difficult and longstanding procedures, such as the embryo exposure by seeds section and the seeds pre-preparation. This study aims to access the viability of small seeds using the Tetrazolium test (TZ) without seeds sectioning, resulting in quicker, cheaper and precise measurements. Non-sectioned seeds of Conyza sumatrensis, Bidens pilosa and Digitaria insularis were put in contact with the tetrazolium solution during 0, 12, 24, 48, 72, 144, 216, 288, 360, 432 and 504 h to obtain the seeds coloring percentage in each time. When possible, the seeds coloring percentages were compared to seeds viability, obtained by the literature standard tetrazolium methodology (STZ), and with seeds germination. The proposed methodology (TZM) was cheaper and less laborious than the methodologies frequently used for weed seeds viability estimation, and provided rapid and reliable seeds viability estimations for weed species with small seeds within 24 h for Digitaria insularis and Bidens pilosa, and 48 h for Conyza sumatrensis.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".