Biochemical Resistance Traits of Bitter Gourd against Fruit Fly Bactrocera cucurbitae (Coquillett) Infestation
Bibliographic record
Abstract
Host plant resistance is a key factor for management of the melon fruit fly, Bactrocera cucurbitae (Coquillett), due to difficulties associated with its chemical and biological control. Various biochemical traits including total sugars, reducing sugars, non-reducing sugars, silica, protein content, ash content, other elements and phenols, and moisture content of fruit were studied on 74 varieties/genotypes of bitter gourd (Momordica charantia L.), in relation to resistance against B. cucurbitae under field conditions. Seventy-four genotypes of bitter gourd were screened against fruit fly infestation. The correlation coefficients revealed that the larval density and bitter gourd fruit damage (%) had significant positive relationship (r = 0.99). The moisture content had significant positive effect on the fruit damage (r = 0.75) and number of larvae per fruit (0.80). Significant differences were found in tested varieties/genotypes for fruit infestation and larval density per fruit. The nitrogen, phosphorous, potassium and protein content (r = -0.87, -0.90) showed significant negative correlation with fruit fly infestation. The non-reducing, reducing, total sugars, total phenols, silica and ash content had significant impact on the fruit damage and showed significant negative correlation with fruit fly infestation. The ascorbic acid also had significant impact on the fruit damage and showed significant negative correlation with fruit fly infestation (r = -0.79), the chlorophyll ‘a’, ‘b’ and total chlorophyll content had non-significant negative effect on the fruit damage and number of larvae per fruit.
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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".