SIDE EFFECTS OF USING OF SOME FOLIAR FERTILIZERS ONBIOLOGY OF COTTON LEAF WORM, SPODOPTERA LITTORALIS (BOISD.) UNDER LABORATORY CONDITIONS
Bibliographic record
Abstract
An experiment was conducted at Qaha Research Station, Qalubia governorate, during 2013 cotton season, to study the effects of four foliar fertilizers on biological aspects of cotton leaf worm, Spodoptera littoralis (Boisd.), for three successive generations. (Canada magic, Canada sal, Canada foliar and Canada amino) were sprayed on cotton leaves in field and introduced to the newly hatched larvae. The obtained results revealed that the larval stages suffered greatest mortality followed by the pre-pupal stage, the pupal stage and lastly the moths for the four compounds. The highest mean percentage mortality of overall immature stages within the three generations (98.8, 98.2, 98.0 and 96.3%) was (Canada sal, Canada amino, Canada magic and Canada foliar), respectively. Analysis of variance between the mean larval duration and Percentage pupation for the remaining larvae and pupae of the three generations, showed significant differences between treatments and control (L.S.D =2.33 & 6.3), respectively. Moreover, all larvae fed on treated leaves gave the least percentage of adults, emergence and a few malformations, also, no eggs were laid by the resulting females in the three generations. Data demonstrated that the larval and pupal weights recorded insignificant differences between treated and untreated.
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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".