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Article
Computer Science, Information Systems
Ritesh Maurya et al.
Summary: Heavy metal pollution in aquatic bodies is a major health concern. Fishes are more susceptible to the harmful effects of non-biodegradable toxic metals. This study utilizes machine learning to identify heavy metal-contaminated fish using color and texture features, achieving high accuracy in classification. This technique can help mitigate the consequences of heavy metal toxicity and can be applied to large-scale fish processing.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Fisheries
Bin Yuan et al.
Summary: This study measures customer preferences and willingness to pay for various oyster trait qualities, providing marketable information for oyster breeding. The research finds that customer preferences for oyster characteristics vary widely, with the highest willingness to pay for the shell size trait. Furthermore, consumer preferences for oyster trait attributes differ between low-market-value consumers and high-market-value consumers.
Article
Chemistry, Multidisciplinary
Ari Kuswantori et al.
Summary: The future application of this study in the auto-sorting system for fish or other objects in various industries, using deep learning and machine vision technology, is highly feasible and close to implementation. Automatic fish recognition is a crucial aspect of automating the fish industry to increase productivity and address future challenges such as food demand and scarcity due to population growth, global warming, and climate change. This paper introduces a method based on the YOLOv4 recognition algorithm with a unique labeling technique, which achieves an accuracy of 98.15% when tested on videos of real fish moving on a conveyor at a speed of 505.08 m/h. This study offers a simple yet effective approach for automatically detecting, classifying, and sorting fish.
APPLIED SCIENCES-BASEL
(2023)
Review
Engineering, Marine
Hanchi Liu et al.
Summary: Automated monitoring and analysis of fish's growth status and behaviors using machine vision and deep learning techniques have become important in aquaculture management. DL-based object detection techniques have been extensively applied to classify and locate fish of interest in images.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2023)
Article
Food Science & Technology
Jiayu Li et al.
Summary: This study aims to detect protein-derived adulterants in oyster peptide powder qualitatively and quantitatively using untargeted and targeted proteomics strategies. Various peptides derived from non-oyster proteins were detected, and three signature peptides of gelatin-derived adulterants were identified and confirmed. An MRM-based quantitative method was established, which showed good linearity and recovery, contributing to the quality control of food-derived peptides in oyster peptide powder products.
Article
Fisheries
Antoine Jourdan et al.
Summary: Selective breeding programs have been initiated for the Pacific oyster Crassostrea gigas, using genomic tools to improve growth and disease resistance. The study evaluated the potential of genomic selection (GS) for growth-related and shell color traits in commercially selected populations. The results showed a high correlation between growth-related traits and low correlation with color traits. The accuracy of prediction was higher with the genomic model compared to the classical model, indicating the potential of GS in mixed-family breeding programs for C. gigas.
Review
Agricultural Engineering
Lu Zhang et al.
Summary: Feeding in aquaculture is crucial for the healthy growth of fish and the economic benefits of aquaculture. However, the current feeding methods may result in underfeeding or overfeeding, leading to growth rate issues and water pollution. This paper explores the use of machine vision in intelligent fish feeding, discussing the main factors, the process, and the technologies involved. By combining machine vision with fish feeding demand, it aims to improve efficiency and promote intelligent aquaculture. Published by Elsevier Ltd. All rights reserved.
BIOSYSTEMS ENGINEERING
(2023)
Article
Chemistry, Multidisciplinary
Xuhui Ye et al.
Summary: An automated and non-contact sorting approach based on an improved YOLOv5 algorithm is proposed for the rapid sorting of crayfish maturity and size, aiming to address the issues of high-intensity labor, low efficiency, and potential damage associated with traditional manual sorting methods. The proposed algorithm achieves an mAP of 98.8% using a dataset of 3464 images, and the processing time for an image is reduced to just 2 ms after deployment using TensorRT, significantly improving the processing speed of the model. In conclusion, this approach provides an accurate, efficient, fast, and automated solution for crayfish sorting.
APPLIED SCIENCES-BASEL
(2023)
Review
Fisheries
Daoliang Li et al.
Summary: This paper provides an overview of machine vision models applied in fish classification, discusses specific applications of various classification methods, and explores the challenges and future research directions in the field of fish classification.
ICES JOURNAL OF MARINE SCIENCE
(2022)
Article
Fisheries
Xin He et al.
Summary: This study identified 925 single nucleotide polymorphisms (SNPs) and 593 genes associated with shell shape in Crassostrea gigas. Two SNPs were found to be significantly related to shell shape differences in an independent population using SNaPshot for genotyping validation. Ten genes were identified as significantly differentially expressed in extreme shell shape groups using real-time PCR.
Article
Computer Science, Artificial Intelligence
Xiaoning Yu et al.
Summary: Non-contact methods for estimating cultured fish weight are important for aquaculture companies, but current technologies face challenges in precisely measuring fish size and estimating fish weight in dense breeding environments. This study proposes a technique for creating a dataset suitable for measuring fish size and an attention-based network for extracting fish contour features. The study addresses the issue of low-level feature loss by combining features from different levels and integrates target location information and channel dimension information. The developed methodology has been successfully applied to an aquaculture system and shows improved performance compared to existing approaches.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Fisheries
Yuxuan Deng et al.
Summary: This study proposes an approach based on Keypoints R-CNN and underwater stereo vision system to automatically identify and measure the species and length of freshwater fish. Techniques such as stochastic enhancement and attention module are utilized for model optimization, achieving improved detection results and accuracy.
Article
Fisheries
Xin He et al.
Summary: The study measured shell traits of Pacific oyster F1 individuals and identified candidate genes using GWAS, filling a research gap in oyster shell growth and shaping. Seven genes with significantly different expressions were identified in extreme phenotypic groups, six of which were associated with secondary shell shape-related traits, providing a reference for future selective breeding.
Article
Food Science & Technology
Wenzhuo Zhang et al.
Summary: This paper proposed a method for classifying citrus surface defects based on machine vision, which achieved a high accuracy rate of 99.1% on a dataset containing 2000 Tribute Citrus. The experimental results showed that the method is effective in classifying citrus surface defects compared to other methods such as SVM, AlexNet, and VGG16.
JOURNAL OF FOOD MEASUREMENT AND CHARACTERIZATION
(2021)
Proceedings Paper
Automation & Control Systems
Behzad Sadrfaridpour et al.
Summary: Oysters play a crucial role in the Chesapeake Bay ecosystem, improving water quality and leading to various restoration programs. Advancements in robotics and artificial intelligence have enabled the use of ROVs to monitor and track oysters, potentially revolutionizing aquaculture practices. This study focuses on videography of the Chesapeake Bay bottom, oyster database construction, and the use of Mask R-CNN for oyster detection and counting in videos.
2021 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2021)
(2021)
Article
Fisheries
Taryn Garlock et al.
REVIEWS IN FISHERIES SCIENCE & AQUACULTURE
(2020)
Article
Agriculture, Multidisciplinary
Lu Zhang et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2020)
Article
Automation & Control Systems
Hee-Jee Sung et al.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2020)
Review
Fisheries
Darien Danielle Mizuta et al.
REVIEWS IN AQUACULTURE
(2019)
Article
Fisheries
Ziqiang Han et al.
Review
Computer Science, Artificial Intelligence
Alberto Garcia-Garcia et al.
APPLIED SOFT COMPUTING
(2018)
Review
Agricultural Engineering
Hanmei Hong et al.
AQUACULTURAL ENGINEERING
(2014)
Article
Education, Scientific Disciplines
G. Andy Chang et al.
JOURNAL OF STATISTICS EDUCATION
(2009)
Article
Engineering, Chemical
DW Sun
JOURNAL OF FOOD ENGINEERING
(2000)
