Studies On Flowering, Fruiting And Yield Attributes Of SomeMango Cultivars
Bibliographic record
Abstract
The experiment was carried out to study on flowering, fruiting and yield attributes of some mango cultivars at the Regional Research Station, Gayeshpur, Bidhan Chandra Krishi Viswavidyalaya, Mohanpur, West Bengal, from January 2021 to June 2022. The present study was carried out on twelve important mango cultivars namely, Golapkhas, Himsagar, Mallika, Dashehari, Amrapali, Chausa, Bombai, Alphanso, Kishanbhog, Langra, Safder Pasand and Rani Pasand available at the experimental orchard of the Regional Research Station, Gayeshpur, B.C.K.V. Nadia. The experiment was laid out in randomised block design (RBD) with three replications. Outcome of the present research wok revealed that the earliest bud bursting was noticed in Golapkhas, Rani Pasand and Kishanbhog, whereas early panicle emergence with long duration was in Golapkhas and Rani Pasand. A huge variation was observed in morphology of inflorescence among the studied cultivars of mango. The variation also observed in inflorescence position (terminal, both axillary and terminal) and inflorescence colour (yellowish green, pink, green with red patches and green) among the mango cultivars. In most of the cultivars, position of inflorescence was terminal except Amrapali and Langra where it was both terminal and axillary position. Higher per centage of hermaphrodite flowers (>25%) with lesser sex ratio (<4:1) was recorded significantly in Kishanbhog and Golapkhas. The highest fruit set was noticed in Langra (32.31%) and lowest fruit set was recorded in Himsagar (14.80%). The highest fruit drop (99.58%) was observed in Kishanbhog followed by Alphanso (99.55 %) whereas lowest (99.10%) in Himsagar. Number of fruits per plant and yield per hectare were found higher in Amrapali, Chausa and Himsagar. Considering early bud emergence, early flower opening as well as early maturity of fruit, Golapkhas and Rani Pasand are best for West Bengal. On the other hand, considering late bud emergence, late flower opening and late maturity of fruit Chausa is best. Considering the number of fruits per plant and yield per plant, Amrapali, Mallika, Himsagar and Chausa may beuseful for commercial cultivation especially in Nadia region as well as West Bengal.
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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".