Evaluation of Different Brinjal (Solanum melongena L.) Varieties for Yield Performance and Sucking Insect Pests in Bahawalpur, Pakistan
Bibliographic record
Abstract
This study investigated the relative performance of ten brinjal (Solamum melongena L.) varieties for yield in fall 2014 in Bahawalpur. The study was conducted at farm area of Islamia University of Bahawalpur. Ten brinjal varieties were evaluated for yield performance in a research trial following randomized complete block design. Significant differences existed in the yield generated by tested varieties. Significantly more yield was recorded in Shamli and Eggplant deep black followed by Advanta 306, Sandhya F1, Black boy, Black nagina and Advanta 305 in descending order. Twinkle star and Kalash F1 generated significantly less yield while the significantly least yield was recorded for Xingchangjishi than all the tested varieties. Whitefly Bemesia tabaci (Homoptera: Aleyrodidae) and jassid Amrasca biguttula biguttula (Homoptera: Cicadellidae) were the major sucking insects attacking this crop. Populations of both pest insects were recorded significantly more on Xingchangjishi while least populations of these pests were recorded on Egg plant deep black and Sandhya F1. Correlation of insect populations with yield showed inverse relationships. These results are important regarding varietal performance for yield test conducted for ten brinjal varieties. Varieties i.e.,Eggplant deep black and Shamli with significantly more yields are recommended for cultivation in this area to get more brinjal yield.
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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".