Deteksi Keberadaan Fitoplankton Berpotensi Berbahaya Di Tambak Udang Intensif Dengan Metode eDNA Metabarcoding

Mardiati, Aina Ul (2024) Deteksi Keberadaan Fitoplankton Berpotensi Berbahaya Di Tambak Udang Intensif Dengan Metode eDNA Metabarcoding. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Tambak udang yang dikembangkan secara intensif mengaplikasikan padat tebar, pemberian pakan serta pupuk yang cukup tinggi, hal ini memungkinkan sisa pakan dan pupuk kaya nitrogen dan fosfor yang tidak termakan oleh udang akan ikut terbuang ke lingkungan dan dapat menyebabkan eutrofikasi sehingga berdampak pada kehadiran fitoplankton yang berpotensi berbahaya (harmful algae) termasuk ledakan populasi fitoplankton (blooming algae) yang mengancam keberlangsungan budidaya udang, organisme lain hingga lingkungan tambak itu sendiri. Sehingga dilakukanlah deteksi dini terkait keberadaan fitoplankton yang berpotensi berbahaya menggunakan metode yang efektif dan efisien yakni metode eDNA metabarcoding. Deteksi fitoplankton berpotensi berbahaya menggunakan eDNA metabarcoding berbasis Next Generation Sequencing dengan gen target 18S V3-V4, yang dianotasi taksonomi berdasarkan database SILVA 138 dan PR2. Hasil analisis NGS membaca sekitar 185.388 seqs DNA yang termasuk ke dalam 1.067 OTUs dari 6 sampel mewakili kolam sumber tambak, beberapa kolam tambak, aliran buangan limbah tambak dan sampel dari muara yang terkena limpasan limbah tambak udang, Tambak Bergas, Desa Lombang, Kecamatan Batang-batang, Kabupaten Sumenep, Jawa Timur. eDNA metabarcoding berhasil mendeteksi 15 genera fitoplankton yang berpotensi berbahaya (database SILVA 138), sedangkan pada tingkat spesies ditemukan 27 taksa berdasarkan database PR2. 12 taksa pada tingkat spesies ditemukan pada kolam tambak, sementara 15 spesies lainnya hanya ditemukan pada sampel muara. Pola sebaran fitoplankton yang berpotensi berbahaya menunjukkan keragaman tertinggi terdapat pada sampel muara, sementara keragaman terendah ditemukan pada sampel kolam sumber.
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The intensive cultivation of shrimp ponds often result in overcrowding, excessive feeding, and fertilizer application. As a result, excess nitrogen and phosphorus from unused feed and fertilizer may be released into the environment and contributing to eutrophication. This environmental impact can promote the growth of harmful phytoplankton, leading to harmful algal blooms. The presence of these harmful algae poses a threat to the sustainability of shrimp cultivation, other aquatic organism, and the pond ecosystem. The toxins produced by harmful algae can harm both shrimp and human tissues, while the depletion of oxygen caused by the blooms negatively affect surrounding organisms. Early detection of potentially harmful phytoplankton is essential for managing pond ecosystem and mitigating the impacts of harmful phytoplankton. An affective and efficient method for this purpose is environmental DNA (eDNA) metabarcoding. This method utilizes Next Generation Sequencing (NGS) to analyze eDNA, targeting 18S rRNA gene regions V3-V4, with taxonomic annotations based on the SILVA 138 and PR2 database. The NGS analysis yielded approximately 185.388 DNA sequences, identifying 1.067 OTUs from six samples collected from inlet, various pond locations, waste stream and estuaries affected by shrimp pond runoff. The eDNA metabarcoding successfully identified 15 potentially harmful phytoplankton genera based on SILVA 138 taxonomic annotation. At species level, 27 taxa were idenfied based on the PR2 database. Specifically, 17 taxa were found in pond samples, while 15 taxa were exclusively detected in estuarine samples. The highest diversity of potentially harmful phytoplankton was observed in estuary samples, while the lowest diversity was found in source pond samples.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	eDNA, fitoplankton, harmful, metabarcoding, tambak udang eDNA, harmful, metabarcoding, phytoplankton, shrimp pond
Subjects:	Q Science > QH Biology > QH541 Ecology Q Science > QH Biology > QH75 Nature conservation. Landscape protection. Biodiversity conservation. Endangered species and ecosystems (General). Habitat conservation. Ecosystem management. Conservation biology
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Biology > 46101-(S2) Master Thesis
Depositing User:	Aina Ul Mardiati
Date Deposited:	12 Aug 2024 08:00
Last Modified:	12 Aug 2024 08:00
URI:	http://repository.its.ac.id/id/eprint/113932

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