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All Journal Bulletin of Electrical Engineering and Informatics Journal of Aquaculture and Fish Health
Fui Fui, Ching
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Agriculture, Biological Sciences & Forestry Electrical & Electronics Engineering

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The development and usability test of an automated fish counting system based on CNN and contrast limited histogram equalization Leong, Jing Mei; Ahmad Hijazi, Mohd Hanafi; Saudi, Azali; Kim On, Chin; Fui Fui, Ching; Haviluddin, Haviluddin
Bulletin of Electrical Engineering and Informatics Vol 13, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i2.5840

Abstract

The aquaculture industry has rapidly grown over the year. One pertinent aspect is the ability of the aquaculture farm management to accurately count the fish populations to provide effective feeding and the control of breeding density. The current practice of counting the fish manually increased the hatchery workers workload and led to inefficiency. The presented work proposed an intelligent, web-based fish counting system to assist hatchery workers in counting fish from images. The methodology consists of two phases. First, an intelligent fish counting engine is developed. The captured image was first enhanced using the contrast limited adaptive histogram equalization. A deep learning architecture in the form of you only look once (YOLO)v5 is used to generate a model to identify and count fish on the image. Second, a web-based application is developed to implement the developed fish counting engine. When applied to the test data, the developed engine recorded a precision of 98.7% and a recall of 65.5%. The system is also evaluated by hatchery workers in the University Malaysia Sabah fish hatchery. The results of the usability and functionality evaluations indicate that the system is acceptable, with some future work suggested based on the feedback received.
The Enhancing Growth Performance and Coloration of Koi Fish (Cyprinus rubrofuscus) through Feed Supplementation with Rumen-Fermented Carrots and Bacillus sp. Anwar, Asni; Murni, Murni; Burhanuddin, Burhanuddin; Soadiq, Syawaluddin; Khaeriyah, Andi; Agusanty, Harnita; ., Hamsah; ., Nurwahyudi; Taukhid, Imam; Fui Fui, Ching
Journal of Aquaculture and Fish Health Vol. 15 No. 1 (2026): JAFH Vol. 15 No. 1 February 2026
Publisher : Department of Aquaculture

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jafh.v15i1.72702

Abstract

Koi fish (Cyprinus rubrofuscus) is an ornamental fish with a relatively high percentage of domestic and international market demand, and its price is highly dependent on the body shape and color quality. Adding carotenoids to feed is one technique to improve the quality and brightness of koi fish colors. This research aimed to analyze the effectiveness of carrot meal fermented using rumen fluid and Bacillus sp. in feed to improve the color and growth performance of koi. This experiment was designed using a completely randomized design method, consisting of four types of treatments, each of which was repeated three times, resulting in a total of twelve test units.  The treatments tested included the use of carrot meal fermented by rumen fluid and Bacillus sp. at levels of 0% (control), 10%, 15%, and 20%.  The parameters observed were carrot meal carotenoids after fermentation, fish color performance, feed utilization efficiency, feed conversion ratio, muscle glycogen content, specific growth rate, absolute growth, and survival of koi fish. Data were analyzed using analysis of variance and further tested using Duncan. The results showed the best in treatment C, 15% rumen microbe fermented carrot meal and Bacillus sp. in feed, and produced the best color performance, TFC 89.91%, FUE 87.54%, FCR 1.99%, MGC 16.79%, SGR 22.62%, AG 34.33g, and SR 100%. This information can help koi breeders improve the color and growth performance of koi fish by using fermented carrot feed, rumen fluid, and Bacillus sp.
Co-Authors ., Nurwahyudi Agusanty, Harnita Ahmad Hijazi, Mohd Hanafi Anwar, Asni Burhanuddin Burhanuddin HAMSAH ., HAMSAH Haviluddin Haviluddin Khaeriyah, Andi Kim On, Chin Leong, Jing Mei Murni Murni Saudi, Azali Syawaluddin Soadiq, Syawaluddin Taukhid, Imam