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Record W2039004495 · doi:10.5539/jas.v4n11p154

Evaluation of Heterosis and Combining Ability of Yield Components in Chillies

2012· article· en· W2039004495 on OpenAlexvenueno aff
Sarujpisit Payakhapaab, Danai Boonyakiat, Maneechat Nikornpun

Bibliographic record

VenueJournal of Agricultural Science · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Practices and Plant Genetics
Canadian institutionsnot available
Fundersnot available
KeywordsHeterosisHybridSoftware maintainerHorticultureYield (engineering)BiologyForensic scienceGenetics

Abstract

fetched live from OpenAlex

Nine F1 hybrids were obtained from crossing between three maintainer lines, CA1445, CA1449 and CA1450 and three restorer lines, CA683, CA1447 and CA1448. The hybrids were significantly different in yield and agronomic performance by using DMRT. The F1 hybrids CA1450 × CA1447 and CA1450 × CA1448 gave the highest yield while different statistically significant from each other in terms of yield levels differed at statistically significant level in this productivity performance when compared with their female parents, male parents and YokSiam variety but not differ statistically significant when compared with JomThong 2 and Jakkrapat varieties. The F1 hybrid CA1450 × CA1448 showed positive heterosis in terms of fruit weight per plant, the number of fruit per plant, fruit weight, fruit width, fruit length and pericarp thickness while F1 hybrid CA1450 × CA1447 expressed positive heterosis in fruit weight per plant, the number of fruits per plant, fruit weight, fruit length and pericarp thickness. The general combining ability of the female parent, CA1450, was good for five characteristics. The male parent, CA1447 was good for five characteristics.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.120
GPT teacher head0.277
Teacher spread0.157 · 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 source (direct Gemma or distilled Codex), 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

Citations16
Published2012
Admission routes1
Has abstractyes

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