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Record W4412066975 · doi:10.33059/jj.v12i1.11461

Efektivitas Pemberian ZPT Bawang Merah (Allium Cepa L.) terhadap Subkultur Tanaman Pisang Barangan (Musa Acuminata L.) secara In Vitro

2025· article· id· W4412066975 on OpenAlexaff
Julaiha Julaiha, Samsul Kamal, Lina Rahmawati, Zuraidah Zuraidah, Eriawati Eriawati, Kurnia Rahayu Purnomo Sari

Bibliographic record

VenueJurnal Jeumpa · 2025
Typearticle
Languageid
FieldAgricultural and Biological Sciences
TopicPlant Growth and Agriculture Techniques
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsAlliumBiologyBotanyHorticulture

Abstract

fetched live from OpenAlex

Perbanyakan tanaman umumnya dilakukan secara generatif melalui biji, atau secara vegetatif melalui bagian tanaman. Namun, banyak tanaman yang sulit diperbanyak secara generatif, sehingga populasinya terus berkurang. Subkultur menjadi salah satu cara perbanyakan tanaman dalam kultur jaringan dengan pemindahan planlet yang masih sangat kecil (planlet muda) dari medium lama ke medium baru secara aseptic. Bawang merah (Allium cepa L.) salah satu zat pengatur tumbuh alternatif yang di tambahkan pada media tanam kultur jaringan pisang barangan (Musa acuminata L.) yang dapat memberikan pertumbuhan dan morfogenesis yang lebih baik bagi planlet tanaman. Tujuan penelitian untuk mengkaji pertumbuhan pisang barangan dengan pemberian larutan bawang merah dan konsentrasi yang baik pada pertumbuhan pisang barangan. Penelitian ini menggunakan pendekatan kuantitatif. Teknik analisis data yang di peroleh dari hasil penelitian ini menggunakan uji anava. Hasil uji F pada analisis sidik ragam menunjukkan bahwa pemberian larutan bawang merah pada pisang barangan berpengaruh sangat nyata terhadap jumlah akar umur 28 dan 84 hari setalah tanam (HST). Pemberian larutan bawang merah memberikan pengaruh nyata pada jumlah akar pada konsentrasi BP4 (MS + larutan bawang merah (5 ml/l).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.617
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.009
GPT teacher head0.226
Teacher spread0.218 · 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.

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
Published2025
Admission routes1
Has abstractyes

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