Proceedings International Conference on Fisheries and Aquaculture

THE EFFECTS OF PROBIOTICS ON THE GROWTH PERFORMANCES OF WHITE SHRIMP (Penaeus vannamei) REARED THROUGH BIOFLOC TECHNOLOGY

D Jatayu — 2023-12-02

The use of probiotics may give beneficial effects on shrimp culture. Biofloc technology also improves water quality and feed efficiency. This study aimed to evaluate the effects of probiotics on shrimp growth reared through biofloc technology. This study consisted of six treatments and triplicates including Control (without probiotic and biofloc), F (Biofloc), BF (Bacillus and biofloc), IF (IW and biofloc), B (Bacillus), I (IW). Biofloc technology was applied using molasses as carbon source (C/N ratio 12). The experimental animals were white shrimp (Penaeus vannamei) (3.8 ± 0.8 g), stocked into glass tanks (60 x 40 x 50 cm3) with a stocking density of 40 shrimp per tank. The shrimp were fed experimental feed four times a day for 30 days. Experimental feed for control and F treatments was composed by commercial feed (32% protein) and 1% binder, while experimental feed for BF, IF, B, and I treatments was composed by commercial feed (32% protein), probiotics (0.2%), and 1% binder. The application of probiotics into the rearing media was conducted using Bacillus and IW probiotics (5 ppm) every week for BF and IF treatments. The parameters observed included final weight, growth rate, survival, feed conversion ratio (FCR), and water quality. The highest shrimp weight was achieved in treatment B (19.0 ± 0.8 g) followed by treatment F (18.4 ± 0.5 g). The lowest FCR was shown by treatment B (1.32 ± 0.12) followed by treatment IF (1.33 ± 0.01). The highest survival was indicated in treatment B (86.67 ± 3.81%) followed by treatment F (85.00 ± 2.5%). The best water quality was found in treatment F with the optimum results in nitrate, alkalinity, and floc volume.

A STUDY ON THE LENGTH-WEIGHT RELATIONSHIPS AND CONDITION FACTOR OF BALI SARDINELLA, IN BALI STRAIT, INDONESIA

IP Sari — 2023-12-02

The Bali sardinella (Sardinella lemuru) from 'PPN Pengambengan' in Bali Strait, Indonesia, has a high commercial value and is under pressure from fishing, despite the fact that the fish growing state is poorly understood. The goal of this study is to discover numerous elements of Bali sardinella growth, such as size distribution, length-weight relationship (LWRs), condition factors, and growth patterns. A total of 817 Bali sardinella fish with lengths ranging from 105-210 mm were sampled in order to determine the length-weight relationship (LWRs) and condition factors. Local fishermen primarily caught them with purse seines (mesh size 0.75 inch). According to the findings, the Bali sardinella (both female and male) growth allometrically (b=2.8656-2.9367), showing that the fish gets slimmer as it grows longer. There was no difference in the percentage of capture numbers between males and females, nor in the condition factor (k) (p>0.05). Male and female mean k values were 0.9672±0.0396 and 0.9912±0.0670, showing that the Bali sardinella are in good condition.

DEVELOPMENT OF FARM-SCALE SALINE TILAPIA HATCHERY TO ADAPT TO THE IMPACT OF GLOBAL WARMING: A TECHNO-ECONOMIC ANALYSIS

Iding Chaidir — 2023-12-02

Tilapia (Orechromis sp) is a freshwater fish species that is widely cultivated because of its high survival ability, easy breeding, and high market demand. However, obtaining land for cultivation in freshwater areas is increasingly difficult because it competes with industrial and residential needs. On the other hand, more brackish water area is available due to the weakening of shrimp prices and rising sea levels caused by global warming. A team of The Agency for the Assessment and Application of Technology from 2008 to 2014, through a selective breeding process, produced saline-tolerant Indonesian Tilapia (officially named "Nila Salina"), which can adapt to high salinity. This variety is superior to other tilapia varieties, but it has yet to be widely cultivated because no hatcheries produce these tilapia seeds. This study aims to explain a feasibility study on the construction of a Nila Salina hatchery in Indramayu Regency, West Java, with a pond area of 3 hectares owned by a local farmer. The study began with a field survey, technical design, primary and secondary data collection, and analysis. Based on the analysis results, it is shown that a Nila Salina hatchery, starting with six packages of broodstock (1800 females and 600 males), can produce 6,040,000 seeds per year. Financial analysis shows that the economic parameters are pretty good, namely the NPV of IDR 2,414,811,000 and IRR of 26.93, indicating that the plan to develop a Nila Salina hatchery in Indramayu is feasible to implement.

COMBINING GENERATIVE MODEL AND RANDOM FOREST TO PREDICT SHRIMP DISEASE OCCURRENCE

Lukman Hakim — 2023-12-02

Penaeus vannamei is one of the most cultured species. The global production of Penaeus (Litopenaeus) vannamei reached 5.8 million tonnes in 2020, contributing to 51.7% of total shrimp production. However, despite its high production, there are still many issues in this industry. One of those is the disease. The disease threatens shrimp farming, such as slowing shrimp growth rate and even mortality. To help the farmers in mitigating the impact of disease we tried to develop a predictive model that is able to give early warning of disease occurrence. We focused on predicting acute hepatopancreatic necrosis disease (AHPND), white feces disease (WFD), infectious myonecrosis virus (IMNV), and white spot disease (WS). We used data from 1839 cultivation cycles. The cycles are managed by 383 Farms. The data covered 4 physical parameters measured twice daily (in the morning and evening). Those parameters are water temperature, dissolved oxygen, salinity, and pH. The data also cover disease tests. We conducted several processes to develop the predictive model. First, we improve the data quality using the Generative Adversarial Network model (GAN). The improved data is then used for feature engineering and model training. We used the Random Forest Model as the predictor to the data we managed to achieve an average F1 score of 0.91 for the four diseases. The model achieved an F1 score of 0.91 for AHPND, 0.89 accuracy for WFD, 0.93 accuracy for IMNV, and 0.9 accuracy for WS. Those results indicate a good possibility to predict the disease occurrence based on water quality data. Hence the method can be used as an early warning system to help the farmer in mitigating disease occurrence.

KERNEL PCA AND ENSEMBLE LEARNING FOR PREDICTING WATER CHEMISTRY AND MICROBIOLOGY PROPERTIES OF PONDS IN PENAEUS VANNAMEI CULTIVATION

Lukman Hakim — 2023-12-02

Water quality is one of the important factors that determine shrimp cultivation yields. It determines shrimp growth and survival rate. Hence water quality monitoring is one of the important activities in shrimp farming. Despite its importance, monitoring water quality during shrimp farming can be costly. This research was conducted to develop prediction models that would give farmers insight about water quality of their ponds. The prediction models used temperature, dissolved oxygen, salinity, and pH as input to predict chemical and microbiological properties of the water. The chemical properties included hardness, magnesium, calcium, and total ammonia whereas the microbiological properties included total organic matter and total plankton. The prediction model was built by combining Kernel Principal Component Analysis and machine learning algorithms (Random Forest and Gradient Boosting separately). The method was tested on the data collected from 31 ponds. The results showed that the algorithm can predict biological and chemical conditions of water (Total Organic Matter, Hardness, Calcium, Magnesium) quite well with R2 score higher than 0.8 on most parameters. Further the result also showed that the combination of Kernel PCA (configured with 2 order polynomial kernel) and Gradient Boosting had best prediction accuracy. These findings show that the method can be used as an alternative to laboratory tests. This would help the farmer in monitoring their pond’s condition in a faster and less expensive way. This also would help farmers who don’t have access to laboratory facilities in monitoring the water quality condition.

YOLO V8 FOR ESTIMATION OF SHRIMP BODY WEIGHT FROM IMAGES

Farid Inawan — 2023-12-02

Penaeus vannamei, a highly cultured species, accounted for 51.7% of the total shrimp production, reaching 5.8 million tonnes globally in 2020 (FAO, 2022). Despite its substantial production, the shrimp farming industry faces various challenges, including shrimp growth monitoring, which is a critical aspect of production. Monitoring shrimp growth not only determines the rate of growth but also affects feeding efficiency. Currently, shrimp growth rate assessment relies on traditional methods that calculate average values from sampled data, introducing potential biases and necessitating time-consuming processes, such as the drying of shrimps before scaling takes place. To address these limitations, this research proposes a novel approach integrating image processing and machine learning algorithms to estimate shrimp weight. Specifically, we combine the YOLO V8 detection algorithm with logarithmic regression. YOLO V8 detects shrimp and measures their height in images, and then, utilizing the detected shrimp objects, we predict their weight through logarithmic regression. Our proposed algorithm achieves a Mean Average Error (MAE) of 0.6 grams in shrimp weight estimation, providing a more efficient and accurate alternative for shrimp growth monitoring in the industry.

BIOCHEMICAL EFFECTS OF LIVE FISH TRANSPORTS: A Comprehensive Review

U Duran — 2023-12-02

Live fish transportation plays an important role in aquaculture and fisheries industries, enabling the movement of aquatic organisms for various purposes such as reproduction, restocking and trade. However, as the process of live fish transportation often involves prolonged confinement, changing environmental conditions and physiological stressors, it can cause various biochemical reactions in these sensitive organisms. This comprehensive review aims to explain the biochemical effects of live fish transportation, shedding light on the complex interactions between stress, physiology and overall fish health. During transportation, fish are under the influence of complex stressors, such as physical disturbances, changes in water quality parameters and handling-induced stress. The review also addresses the impact of transport-related biochemical changes on fish health and survival. Prolonged exposure to stressors can weaken the immune system and make fish more susceptible to pathogens. Furthermore, disruption of metabolic pathways and energy utilization can lead to post-transport mortality or delayed growth rates. Several strategies have been proposed to mitigate the adverse biochemical effects of live fish transportation. Pre-transport acclimation, optimization of transport conditions (e.g., water temperature, oxygen levels), and administration of stress-reducing compounds (e.g., antioxidants, corticosteroid blockers) have shown promise in alleviating stress-induced biochemical changes. In conclusion, live fish transportation is a complex process that significantly affects the biochemical environment of aquatic organisms. Understanding the intricacies of these biochemical reactions is critical to improve the welfare and survival of transported fish. Future research should focus on improving transport protocols and developing innovative interventions to minimize the negative effects of stress during transport. In this way, the sustainability of the aquaculture and fisheries industries can be supported.

FISHERFOLK AWARENESS AND ATTITUDE TOWARDS PARROTFISH AND ITS CONSERVATION IN POLLILO ISLAND, QUEZON PHILIPPINES

GM Tolentino — 2024-03-05

Polillo Island is known for its beaches and marine life. However, due to destructive anthropogenic activities, residents notice a decline in natural resources. Especially evident is the decrease in fish catch. The parrotfish benefits a fisherfolk’s livelihood by contributing to daily food sources and income of the fisherfolk. With the decline in its population, local environmental officials are regulating the fishing and consumption of this species. However, stakeholder commitment is crucial in achieving any conservation goal. Understanding fisherfolk attitudes and awareness of the resource and conservation initiatives increases the success rate of policy implementation. This study aims to determine (1) the socio-demographic characteristics of the fisherfolk; (2) their awareness of policies on (a) marine species conservation and (b) the conservation status of parrotfish; (3) their attitudes towards (a) conservation initiatives and marine protection regulations, and (b) their willingness to conserve the parrotfish species. This study also seeks (4) to analyze fisherfolk’s socio-demographic characteristics' (age, annual income, educational attainment, and fishing experience) relationship to their awareness and attitude toward parrotfish species conservation. Results were analyzed using weighted mean, Pearson R correlation, and ANOVA one-way test. To gather data, a survey was employed in three villages with a sample of 177 fisherfolk who had experienced catching parrotfish. Results show that among the socio-demographic characteristics, fisherfolk’s age and fishing experience are significantly related to their attitude toward conservation initiatives and marine protection regulations. The significance of older and experienced fisherfolk in conservation initiatives should be explored. They should be involved in encouraging new fisherfolk to conserve marine species. At the same time, conservation initiatives must be designed to benefit these experienced fisherfolk.