Heritability and predicted gain from selection in components of crop duration and seed yield in sesame (<i>Sesamum indicum </i>L.)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The duration of maturity in sesame is dependent on several physiological and phenological variables, which are interrelated and could be manipulated separately in breeding programme. For effective manipulation of these traits, knowledge of genetic architecture is prerequisite. Therefore, seventy diverse sesame genotypes were studied to know the heritability and predicted gain for components of crop duration, correlation among themselves and to identify superior genotypes to be utilized in future breeding programmes. Sizeable variability was revealed among genotypes for studied traits. Genotypic coefficient of variation (GCV) was high (>20%) for seed yield and capsules per plant with high heritability (>80%) and high genetic advance as pecentage of mean (>20%). Also, reproductive period and seeds per capsule expressed high heritability coupled with high genetic gain and moderate GCV. All these key components seem to be under the control of additive gene action, which is fixable. Large environmental effect for primary branches per plant was detected. Correlation of capsules per plant was significant positive and physiological maturity was significant negative with seed yield per plant, but both were correlated negatively with each other. Besides this, association of reproductive period was significant positive with physiological maturity and significant negative with vegetative duration. Simultaneous selection for capsules per plant and crop maturity duration would serve the purpose of improvement in these traits and yield in sesame. Top yielding isolated lines can be utilized for enhancing yield potential through increasing capsules per plant and earliness.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.000 | 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 it