Development and performance evaluation of an automatic size-sorting system for catfish seeds using photodiode sensors

Irmansyah, Irmansyah; Saputra, Rifqi Eka; Zuhri, Mahfuddin; Syafutra, Heriyanto

doi:10.22441/sinergi.2026.1.018

Open access Journal SINTA 1

Development and performance evaluation of an automatic size-sorting system for catfish seeds using photodiode sensors

Sinergi · Vol. 30 No. 1 (2026) · pp. 197–208

DOI: 10.22441/sinergi.2026.1.018
ISSN: 2460-1217, 1410-2331
Published: 2026-01-16
Publisher: Universitas Mercu Buana
Language: eng
License: creativecommons.org/licenses/by-sa/4.0

Abstract

In catfish farming, uniform seed size is crucial for ensuring balanced growth and minimizing competition for feed. Generally, size sorting is performed manually through visual observation and net separation, which is labor-intensive, time-consuming, and often causes stress or injury to fish. To address these limitations, this study aimed to develop and evaluate a real-time, low-cost automatic sorting system for live catfish seeds. The proposed system utilizes photodiode sensors and an Arduino-based microcontroller to detect variations in fish body length by interrupting a laser beam. Four photodiodes were arranged at specific distances to classify fish seeds into four size categories (<7 cm, 7–8 cm, 9–10 cm, and 11–12 cm). After classification, the system automatically directed each seed into the corresponding container. The results showed that the prototype successfully classified and sorted catfish seeds with an overall accuracy of 67.5%. In contrast, tests with PVC pipes under controlled conditions achieved 100% accuracy. These findings highlight the novelty of integrating size detection and direct sorting for live fish seeds, a feature not previously reported in the literature. Beyond its current limitations, this system provides a methodological framework for sensor-based aquaculture automation, offering potential for further improvements in accuracy, robustness, and application to other aquaculture species.

Keywords

Collaboration network of the authors

28 authors · 89 co-authorship links · 3 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

IPB University
Cenderawasih University
Kwansei Gakuin University
Universitas Muhammadiyah Parepare
Universitas Yudharta Pasuruan
Affiliation unknown

Different organisations
Same organisation
Affiliation unknown
Thicker line = more joint articles · bigger circle = more articles

Show as table

Co-author	Organisation	Joint articles
Irzaman Irzaman	IPB University	3
Nazopatul Patonah Har	Affiliation unknown	3
Siti Hajar	Cenderawasih University	2
Rofiqul Umam	Kwansei Gakuin University	2
Jasman Jasman	Universitas Muhammadiyah Parepare	1
Ichsan Ristiawan	Affiliation unknown	1
Siti Aisyah	Affiliation unknown	1
Aminullah Aminullah	Universitas Yudharta Pasuruan	1
Sri Hendrastuti Hidayat	IPB University	1
Supramana Supramana	Affiliation unknown	1
Efi Toding Tondok	Affiliation unknown	1
Fitrianingrum Kurniawati	Affiliation unknown	1
Ardian Arif	Affiliation unknown	1
Rahmah Asri Nurani Hanifan	Affiliation unknown	1
Erus Rustami	Affiliation unknown	1
Siti Nikmatin	Affiliation unknown	1
Muhammad Khoirul Anam	Affiliation unknown	1
Desi Nadalia	Affiliation unknown	1
Hirotaka Takahashi	Affiliation unknown	1
Faozan Ahmad	Affiliation unknown	1
Rudi Heryanto	Affiliation unknown	1
Ganesha Antarnusa	Affiliation unknown	1
Mersi Kurniati	Affiliation unknown	1
Muhammad Firman Azima	Affiliation unknown	1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://publikasi.mercubuana.ac.id/index.php/sinergi/oai, first harvested 10 Nov 2026, last seen 10 Nov 2026.

Original metadata (oai_dc)

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	<dc:title xml:lang="en-US">Development and performance evaluation of an automatic size-sorting system for catfish seeds using photodiode sensors</dc:title>
	<dc:creator>Irmansyah, Irmansyah</dc:creator>
	<dc:creator>Saputra, Rifqi Eka</dc:creator>
	<dc:creator>Zuhri, Mahfuddin</dc:creator>
	<dc:creator>Syafutra, Heriyanto</dc:creator>
	<dc:subject xml:lang="en-US">Aquaculture</dc:subject>
	<dc:subject xml:lang="en-US">Automatic sorting</dc:subject>
	<dc:subject xml:lang="en-US">Catfish</dc:subject>
	<dc:subject xml:lang="en-US">Photodiode sensor</dc:subject>
	<dc:description xml:lang="en-US">In catfish farming, uniform seed size is crucial for ensuring balanced growth and minimizing competition for feed. Generally, size sorting is performed manually through visual observation and net separation, which is labor-intensive, time-consuming, and often causes stress or injury to fish. To address these limitations, this study aimed to develop and evaluate a real-time, low-cost automatic sorting system for live catfish seeds. The proposed system utilizes photodiode sensors and an Arduino-based microcontroller to detect variations in fish body length by interrupting a laser beam. Four photodiodes were arranged at specific distances to classify fish seeds into four size categories (&amp;lt;7 cm, 7–8 cm, 9–10 cm, and 11–12 cm). After classification, the system automatically directed each seed into the corresponding container. The results showed that the prototype successfully classified and sorted catfish seeds with an overall accuracy of 67.5%. In contrast, tests with PVC pipes under controlled conditions achieved 100% accuracy. These findings highlight the novelty of integrating size detection and direct sorting for live fish seeds, a feature not previously reported in the literature. Beyond its current limitations, this system provides a methodological framework for sensor-based aquaculture automation, offering potential for further improvements in accuracy, robustness, and application to other aquaculture species.</dc:description>
	<dc:publisher xml:lang="en-US">Universitas Mercu Buana</dc:publisher>
	<dc:date>2026-01-16</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:format>application/vnd.openxmlformats-officedocument.wordprocessingml.document</dc:format>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://publikasi.mercubuana.ac.id/index.php/sinergi/article/view/33556</dc:identifier>
	<dc:identifier>10.22441/sinergi.2026.1.018</dc:identifier>
	<dc:source xml:lang="en-US">SINERGI; Vol. 30 No. 1 (2026); 197-208</dc:source>
	<dc:source>2460-1217</dc:source>
	<dc:source>1410-2331</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://publikasi.mercubuana.ac.id/index.php/sinergi/article/view/33556/10356</dc:relation>
	<dc:relation>https://publikasi.mercubuana.ac.id/index.php/sinergi/article/view/33556/12379</dc:relation>
	<dc:relation>https://publikasi.mercubuana.ac.id/index.php/sinergi/article/view/33556/12380</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2026 SINERGI</dc:rights>
	<dc:rights xml:lang="en-US">https://creativecommons.org/licenses/by-sa/4.0</dc:rights>
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