Effects of Cultivar, Planting Period, and Fungicide Usage on Rice Blast Infection Levels and Crop Yield
Bibliographic record
Abstract
Studies were separately conducted to determine the effects of cultivar, planting date, and fungicide usage on rice blast disease, caused by Pyricularia grisea (Cooke) Sacc. [= Magnaporthe grisea (Hebert) Barr] in Kecamatan Manggala, South Sulawesi Indonesia. The four rice varieties were IR-66, Cisantana, Cigeulis, and Filipin. The results showed that IR-66 was moderately resistant to leaf and neck blast, with the lowest percentage unfilled grains per panicle. Cisantana reacted moderately resistant to leaf blast, but moderately susceptible to neck blast. Cigeulis was moderately susceptible to leaf and neck blast, while Filipin showed a highly susceptible reaction to both leaf and neck blast, and a 31% plant population death due to the blast disease. With respect to planting dates (February 4, March 22, and May 16), plants transplanted in March had the highest leaf blast severity, neck blast incidence, and the lowest yield. Seven fungicides (four are recommended for use in rice in Indonesia: flusilazol, difenoconazole, difenokonazole+propikonazole, and carbendazim (6.2%)+mancozeb (73.8%)) and three generally used ones (menefoxam (4%)+mancozeb (64%), chlorothalonyl, and metalaxyl) which were evaluated against the rice blast disease, showed the recommended fungicides for use in rice to be more effective in suppressing blast and protecting yield, compared to the other fungicides.
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".