Optimization of Somatic Embryo Induction and Nodulation in Mangosteen (Garcinia mangostana L.) Using Carbohydrate Sources and Growth Regulators
Bibliographic record
Abstract
Mangosteen (Garcinia mangostana L.) is a horticultural plant with various beneficial properties from all parts of the plant.However, its cultivation faces several challenges, necessitating the development of efficient propagation techniques.One promising method is the induction of somatic embryos and nodulation.This study aimed to evaluate the effects of honey and sucrose in combination with the growth regulators 2,4-D and BAP on somatic embryo induction and nodulation in mangosteen, determine the optimal treatment concentration, and assess the phases of somatic embryo development and nodular bud formation.The experiment was conducted at the Biotechnology Laboratory, Faculty of Agriculture, Siliwangi University, from September 2022 to February 2023, using a completely randomized design (CRD) with six treatment combinations and four replications.The results showed that all treatments had significant effects (p < 0.05) on the percentage of embryogenic callus, the number of globular-phase somatic embryos, nodules, and nodular buds per explant.The treatment using 5% sucrose + 1 mg L⁻¹ 2,4-D + 3 mg L⁻¹ BAP produced the best results, inducing 29 globular, 4 heart-shaped, and 1 torpedo-stage somatic embryo, along with 30.21 nodules and 3.96 nodular buds per explant.These findings provide a promising protocol for efficient in vitro regeneration of mangosteen, which could support large-scale propagation and conservation efforts.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".