Biological Control of Sheath Diseases of Rice Caused by Rhizoctonia oryzae and Rhizoctonia solani by Trichoderma spp.
Bibliographic record
Abstract
The objective of this study, aims to select the effective antagonistic fungi to control sheath diseases of rice. The experiments were conducted in the laboratory and green house. In the laboratory, the antagonist fungi, Trichoderma hazianum T9, T18 and T13 T. asperellum and T. koningii isolate 67 were tested on their efficiency against R. solani and R. oryzae in dual cultures. The result showed that the isolates T9, T13, T18, 67 were able to inhibit the colony of R. oryzae and R. solani. The percent of colony inhibition was highly efficient against R. oryzae isolates VHN, VHN1-3 and SMN1-7 as 88%, 63% and 63%, respectively. For R. solani, isolates VNN, SMC1-2 and SMN1-5 exhibited the percent of inhibition as 41%, 40% and 36%, respectively. In the green house test, the result revealed the 3 effective isolates, T13, T18, 67 for control R. oryzae. The best method for application of isolates T18 and T13 were foliar spray, by which disease suppression was 92% and 87%, respectively. Isolate 67 was applied by root dip method and causing disease suppression of 87%. For R. solani, the isolate T18 was applied by soil treatment and expressed disease suppression of 61%. The best method for application of isolates T13 and 67 were the combination of soil treatment, root dip and foliar spray, by which disease suppression was 60% and 50%, respectively. All 3 isolates were significant difference (P<0.05) in disease suppression compared to control. This study suggests the biological control approach for sheath diseases of rice in Lao PDR.
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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) | 0.001 | 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".