UTILIZATION OF BITTERN FOR REDUCING THE TOTAL SUSPENDED SOLID AND TURBIDITY FROM TRADITIONAL FISH BOILED WASTEWATER

 Zulfan Ibrahimi¹, Dwi Yuli Pujiastuti², and Patmawati²

¹Study Program of Fish Processing Technology, Faculty of Fisheries and Marine, Universitas Airlangga, Surabaya, Indonesia

² Department of Marine, Faculty of Fisheries and Marine, Universitas Airlangga, Surabaya, Indonesia

*E-mail: dwiyp@fpk.unair.ac.id

Traditional fish boiled wastewater produces a bad odor caused by protein and organic matter decomposition. The organic decomposition has an impact on water quality by producing high turbidity. Bittern is residual water from salt production which is abundant with ion content of magnesium and has not been widely used as a natural coagulant. Therefore, this study was aims to determine the ability of bittern as a natural coagulant for traditional fish boiled wastewater. This research is experimental which consists of the main and supporting parameters. The dependent variables are COD, BOD, TSS, and turbidity in the wastewater treatment. The independent variables were coagulant dose (bittern) and stirring time with coagulant dose (30%, 60%, and 90%), and variations in stirring time (15 minutes, 30 minutes and 45 minutes). A factorial completely randomized design (CRD) was used as the experimental design. Data were analyzed using ANOVA (Analysis of Variance) to find out the best treatment, and the further test was carried out by DMRT (Duncan Multiple Range Test). The results showed that the effect of adding residual water from salt production (bittern) could be used as an alternative coagulant in traditional fish boiled wastewater, which significantly affected in TSS levels and turbidity (sig. <0.05). The addition of bittern can also reduce the BOD and COD values with the efficiency values of decreasing the BOD and COD values of 72.1% and 65.5%, respectively.

Keywords: bittern, fish boiled wastewater, coagulant, TSS, turbidity

UNUSUAL INLAND RECORD OF THE BULL SHARK CARCHARHINUS LEUCAS (MÜLLER & HENLE 1839) ON FORMER TIN MINE, BELITUNG ISLAND, INDONESIA

 Putri Mardhotillah^1*, Veryl Hasan², Peter Gausmann³, Maheno Sri Widodo⁴

¹Studi Programe of Aquaculture, Faculty of Fisheries and Marine, Universitas Airlangga, Surabaya, East Java 60115, Indonesia

²Department of Aquaculture, Faculty of Fisheries and Marine, Universitas Airlangga, Surabaya, East Java 60115, Indonesia

³Department of Landscape Ecology and Biogeography, Faculty of Geosciences, University of Bochum, Universitätsstraße 150, 44801 Bochum, Germany

⁴Department of Aquaculture, Faculty of Fisheries and Marine Science, Universitas Brawijaya, Malang, 65145, East Java, Indonesia

*E-mail: putritilaaa123@gmail.com

A single specimen of a juvenile bull shark Carcharhinus leucas (Müller & Henle 1839) with c. 96 cm of total length was landed and photographed on 22 July 2012 in the former tin mine, middle of oil palm plantation, Belitung Island, Indonesia. This species is currently listed as a Near Threatened (NT) species based on the IUCN Red List Status. The record indicates that a specimen of C. leucas was found more than 20 km inland. This specimen was identified as C. leucas by the characteristics of fresh specimen: greyish back and white belly, first dorsal fin high, second dorsal fin short, tip of second dorsal and caudal fins black.

Keywords: conservation, elasmobranch, environment, protection

THE WORLD'S LARGEST FRESHWATER FISH: AN OVERVIEW

Veryl Hasan¹, Josie South², Felipe P. Ottoni³

¹Department of Aquaculture, Faculty of Fisheries and Marine, Universitas Airlangga, Jl. Mulyorejo, Surabaya 60115, Indonesia.

²School of Biology, Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, UK. j.south@leeds.ac.uk.

³Laboratory of Systematics and Ecology of Aquatic Organisms, Centre of Agrarian and Environmental Sciences, Federal University of Maranhão, Chapadinha, State of Maranhão, Brazil

Giant freshwater whipray Urogymnus polylepis (Bleeker, 1852) is the largest fish in the world spread over several areas of South Asia such as India and Bangladesh, and Southeast Asia such as Myanmar, Thailand, Cambodia, Vietnam, Malaysia, and Indonesia. In Indonesia, this fish is spread in Java, Sumatra, and Borneo but it is estimated that it has become extinct in Java. Based on current records, this species is among the largest freshwater fish in the world where they can grow to over 650 pounds. The IUCN red list includes it in the Endangered (EN) category. The biggest threat to the existence of this species is the change in river function and bycatch. Conservation programs must be carried out so this species does not become extinct.

Keywords: Ecology, endangered, freshwater fish, stingray

SOIL AND HYDROLOGICAL CHARACTERISTICS OF FISHPOND WITH CARBONIZED RICE HULL

Larry A. Santos, Irene De Vera, Analyn I. Diola, Edwin N. Alferez

Pangasinan State University

Good water quality connotes clean habitat for the fishes used for human consumption which ensures food safe and environmental sustainability. This is an experimental research which explores the effects of carbonized rice hull on the water quality of fish pond water. A rice hull carbonizer was designed and constructed to produce carbonized rice hull being utilized in the study. Experiment was conducted using different amount of carbonized rice hull as substrate for fishpond water. Water quality analysis was conducted to determine the effects of the CHR on fishpond water quality. Results of water quality for both physic-chemical and microbiological analysis indicate that the water is safe as fishpond.

Keywords: Soil, fishpond, rice hull, hydrological

NOVEL LINEAGES AND RECENT CLASSIFICATION OF MARINE FUNGI

 Mark S. Calabon¹*, Resurreccion B. Sadaba¹, E.B. Gareth Jones²

¹Division of Biological Sciences, College of Arts and Sciences, University of the Philippines Visayas, Miagao, Iloilo 5023, Philippines

²Department of Botany and Microbiology, College of Science, King Saud University, P.O. Box 2455, Riyadh, 11451, Saudi Arabia

^*Corresponding author: mscalabon@up.edu.ph

Taxonomic and phylogenetic studies of lignicolous marine fungi in Thailand, Sweden, and the UK resulted in the collection of the novel genus and species, Pseudophialocephala and Parahelicomyces dictyosporus, respectively. The detailed descriptions, illustrations, taxonomic notes, and updated backbone tree of each novel taxa are provided in the present study. These novelties add to the increasing number of fungi from marine habitats and the recent classification of logged in the marine fungi website, marinefungi.org, is discussed and updated in the present work. Currently, marine fungi include 1,859 species with Ascomycota accounts for 83.86% (1,559 species), followed by Basidiomycota (158 species). In the phylum Ascomycota, Sordariomycetes is the speciose class (616 species), followed by Dothideomycetes (400 species), Eurotiomycetes (268 species), and Saccharomycetes (183 species). The most speciose order is Pleosporales (280), followed by Eurotiales (210), Saccharomycetales (182), Microascales (175) and Hypocreales (141). Other basal fungal clades include Microsporidia, Chytridiomycota, Mucoromycota, Olpidiomycota, Aphelidiomycota, Blastocladiomycota, and Mortierellomycota.

Keywords: Aquatic fungi, Aquatic mycology, Fungal numbers, Fungal systematics, Marine biology

IMAGE-BASED FISH SPECIES CLASSIFICATION USING A DEEP LEARNING APPROACH

Ezmahamrul Afreen Awalludin^{1, *}, Hazman Ariff Rusman¹, Affan Zaidi¹,

Nur Muhammad Afiq Anang¹, Muhammad Za’im Akmal Zukhairi¹

¹Faculty of Fisheries and Food Science

Universiti Malaysia Terengganu, 21030 Kuala Nerus, Terengganu, Malaysia.

^*Corresponding author: e.afreen@umt.edu.my

Traditionally, observation and conservation have been carried out manually, which is a time-consuming, sequential task that necessitates human intervention and laborious. In addition, the classification from the manual approach always suffers from the problem of the hand-crafted manual, which makes it difficult to differentiate species classes, decrease accuracy, and misclassify datasets. Thus, the main objective of this research is to propose a new approach on fish species classification using deep learning approach. The proposed method was modified with the help of a cutting-edge deep learning methodology based on the ResNet-50 architecture. ResNet-50 is one of the best neural network architectures which contributes to the network's ability to retain low error rates considerably deeper in the network. Therefore, the similar fish species with colour similarity can be classified properly using ResNet-50 model architecture especially to non-expert fish. In this study, the ResNet-50 was used as a platform for the fish classification of four sets of fish samples comprising Upeneus sulphureus, Oreochromis spp, Lutjanus malabaricus, and Nemipterus furcosus. The fish species sample was collected from the Tok Jembal, Pengkalan Maras, and Batu Rakit markets, which are located in the eastern part of Peninsula Malaysia. The datasets were setup to have a proportion of 80% training data and 20% testing data. The experiment has been run ten times in order to evaluate the performance of the classification task using the ResNet-50 model architecture. All the experiment outputs present the highest accuracy of 90%, which indicates that the Resnet-50 model architecture presents the best classification results for classifying fish species. The study's findings will help researchers, students, and the public classify fish species more effectively and with fewer time-consuming requirements.

Keywords: Fish Species Classification, Fish Image-Based, Residual Network-50 (ResNet-50), Deep learning