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Record W4400139410 · doi:10.5376/ijh.2024.14.0018

Varietal Performance on Flowering of Different Varieties of Mango (<i>Mangifera indica</i>) at Sarlahi, Nepal

2024· article· en· W4400139410 on OpenAlexvenueno aff
Kiran Thapa, Rupesh Chaudhary, Pratiksha Sharma, Sunil Kumar Chaudhary, Poojan Adhikari, Pawan Pyakurel, Arati Chapai

Bibliographic record

VenueInternational Journal of Horticulture · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Physiology and Cultivation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMangiferaHorticultureBiology

Abstract

fetched live from OpenAlex

Floral characteristics of 10 mango varieties were studied during February-June, 2023.Distinct variations were found among the studied varieties.Significant variation were observed in term of length of inflorescence, width of inflorescence, number of male flower per inflorescence, number of female flower per inflorescence, sex ratio, % male flower, % hermaphrodite flower ranging from 20.9 cm to 31.9 cm, 11.3 cm to 19.7 cm, 279 to 1,363, 59 to 230.7, 1.25 to 19.63, 50.8% to 94.1% and 5.93% to 49.24%, respectively.The result revealed in all varieties inflorescence position were found terminal and flowers were of pentamerous type.Jarda has the longest inflorescence (31.9 cm).Dasheri has the widest inflorescence (19.7 cm).Male flowers were more than hermaphrodite flowers across the varieties.Amrapali has the highest number of hermaphrodite flower (230.7).Bombay has the highest number of male flowers (1,363) and highest sex ratio (19.63).From this study, it can be inferred that Amrapali will have more fruit set as it has highest number of hermaphrodite flowers.The findings of the study will be beneficial for breeding purpose while developing new varieties of superior quality.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.876
Threshold uncertainty score0.262

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.217
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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