Physiological Quality of Treated and Stored Barley Seeds
Bibliographic record
Abstract
Industrial seed treatment (IST) is used in some grain crops. However, the products used often impair the quality of seeds, especially insecticides. In the case of barley seeds, investigative studies on the use of IST are scarce. The present study aimed to evaluate the influence of IST with the fungicide (Iprodione) and insecticide (Thiamethoxan) products, mixed or not, on the physiological quality of barley seeds, before and after storage for two months. A completely randomized design was used, in a 4x2 factorial scheme, with four replications. The treatments consisted of four combinations of applications carried out via IST on barley seeds, of chemical pesticides (fungicide/insecticide), alone or in mixtures, as follows: {T1 – fungicide Iprodione (Rovral); T2 – Thiamethoxan insecticide (Cruizer); T3 – mixture of fungicide/insecticide products (Iprodione + Thiamethoxan); T4 – Control)}, submitted to storage for two months, with evaluations carried out at T0 (treated and analyzed seeds) and T1 (treated seeds stored for 60 days). The following tests were carried out: water content, germination, first count, accelerated aging, seedling length, seedling dry mass. It was concluded that the germination of barley seeds treated with the fungicide Iprodione (Rovral®) and the insecticide Thiamethoxan (Cruizer®), alone and in a mixture applied via IST, maintained the physiological quality of the seeds within the standards for commercialization until 60 days of storage. The use of the insecticide Thiamethoxan (Cruizer®) via IST showed greater damage to the physiology of barley seeds during storage (60 days), applied alone or in a mixture with the fungicide Iprodione (Rovral ®).
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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".