MétaCan
Menu
Back to cohort
Record W2151482120 · doi:10.5539/sar.v2n3p58

Effect of Cultivar and Explants Type on Tissue Culture Regeneration of Three Nigerian Cultivars of Tomatoes

2013· article· en· W2151482120 on OpenAlexvenueno aff
Shakirat Oloruntoyin Ajenifujah‐Solebo, Isu N. A., Omotoye Olorode, Ivan Ingelbrecht

Bibliographic record

VenueSustainable Agriculture Research · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant tissue culture and regeneration
Canadian institutionsnot available
Fundersnot available
KeywordsExplant cultureHypocotylCotyledonRadicleShootBiologyCultivarBotanyHorticultureSeedlingGerminationIn vitro

Abstract

fetched live from OpenAlex

<p>In order to assess the suitable explant(s) for <em>in-vitro</em> regeneration of three local cultivars of Nigerian tomatoes, Ibadan local (IbL), Ife and JM94/46, cotyledon, hypocotyls and radicle explants were cultured in shoot regeneration medium consisting of<strong> </strong>MS containing 30 g L<sup>-1</sup> sucrose and 8 g L<sup>-1 </sup>agar with no exogenous plant growth hormones. Forty-five of each explant type was cultured on the medium in triplicate experiments and results showed varied percentage survival and shooting for the various explants. Hypocotyl explants had the highest percentage of shooting explants at 13.3% for IbL; 6.67% for Ife and 20% in JM94/46. IbL cotyledon explants had 4.44% of shooting explants with no shoots recorded in Ife and JM94/46 cotyledon explants. IbL radicle explants had 2.22% shooting explants and no shoots recorded in Ife and JM94/46. Student Neuman Keuls (SNK) statistical analysis of cultivar-media interaction showed there was no significant difference (P > 0.05) among the three cultivars in number of calli and shooting calli. There was however significant difference among the cultivars in the number of shoots recorded. SNK values for explants-media interaction showed that cotyledon and radicle explants were significantly different (P < 0.05) from hypocotyl explants in the number of shoots produced.</p>

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.397

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 head0.012
GPT teacher head0.301
Teacher spread0.289 · 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

Citations8
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueSustainable Agriculture ResearchSame topicPlant tissue culture and regenerationFrench-language works237,207