Medicinal Plant-Based Immunostimulants for Sustainable Shrimp Farming: From Bioactive Compounds to Reproductive Enhancement
Bibliographic record
Abstract
The expansion of intensive shrimp aquaculture, driven by global food demand, is challenged by disease outbreaks and reliance on unsustainable practices like eyestalk ablation to induce reproduction in broodstock. This review explores the potential of medicinal plant-based immunostimulants as a sustainable alternative, with a specific focus on enhancing the reproductive performance of the Pacific white shrimp, Penaeus vannamei. We detail the complex endocrine regulation of crustacean reproduction, highlighting the roles of the X-organ-sinus gland complex, mandibular organ, and key hormones like methyl farnesoate. This foundation underscores the mechanistic drawbacks of eyestalk ablation, creating a compelling need for natural interventions. The paper then synthesizes evidence on how bioactive phytochemicals, including flavonoids, alkaloids, and sterols, can stimulate growth, immunity, and gonadal maturation. A thorough analysis of two promising plants, Melastoma malabathricum (Karamunting) and Cyperus spp., is presented. M. malabathricum, rich in lanosterol, acts as a precursor for steroid hormones, significantly accelerating ovarian development, increasing oocyte size, and elevating progesterone levels in P. vannamei. Conversely, Cyperus spp. contains methyl farnesoate, a crustacean juvenoid hormone analog, which promotes vitellogenesis, spermatogenesis, and molting, leading to advanced gonadal maturation stages and improved spawning performance. By compiling the molecular and endocrine evidence, this review positions these herbal extracts as effective, natural, and welfare-friendly alternatives to synthetic hormones and invasive techniques, offering a viable strategy to enhance reproductive efficiency and sustainability in shrimp hatcheries.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".