Effect of Bio-Rational Approaches on the Larval Population and Pigeonpea Pod Damage by Exelastis atomosa (Wlsm.)
Bibliographic record
Abstract
Effect of bio-rational approaches such as intercropping and application of bio-pesticide on the larval population, pod damage, grain damage and grain weight loss by plume moth (Exelastis atomosa (Wlsm.)) infesting pigeonpea (Cajanus cajan (L.) Millsp.) was studied. Pigeonpea intercropped with maize, pearl millet, sorghum, rice and black gram had significant effect on the larval population of plume moth when compared with pigeonpea sole crop infestation. The pigeonpea pod damage, grain damage and grain weight loss due to larval infestation in different pigeonpea intercrops and pigeonpea sole crop differed significantly however few exceptions were also recorded. The average larval population, pod damage, grain damage and grain weight loss in different intercrops varied from 0.25 to 0.39 larva/plant, 1.29 to 1.79%, 0.41 to 0.55% and 0.25 to 0.35%, respectively. The pigeonpea sole crop had recorded relatively higher larval population (0.39 larva/plant), pod damage (2.03%), grain damage (0.85%) and grain weight loss (0.59%) than the intercropped pigeon pea. The two sprays of NSKE 5% (first at flowering and pod formation stage and second after 20 days) were found superior in reducing larval population, pod damage, grain damage and grain weight loss. However, the plots devoid of any biopesticidal treatment had maximum larval population (0.68 larva/plant), pod damage (2.75%), grain damage (0.86%) and grain weight loss (0.60%) by E. atomosa.
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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 | 0.000 |
| 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".