Machine Learning In Aquaculture

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Machine Learning In Aquaculture

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Author : Mohd Azraai Mohd Razman
language : en
Publisher: Springer Nature
Release Date : 2020-01-02

Machine Learning In Aquaculture written by Mohd Azraai Mohd Razman and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-02 with Science categories.

This book highlights the fundamental association between aquaculture and engineering in classifying fish hunger behaviour by means of machine learning techniques. Understanding the underlying factors that affect fish growth is essential, since they have implications for higher productivity in fish farms. Computer vision and machine learning techniques make it possible to quantify the subjective perception of hunger behaviour and so allow food to be provided as necessary. The book analyses the conceptual framework of motion tracking, feeding schedule and prediction classifiers in order to classify the hunger state, and proposes a system comprising an automated feeder system, image-processing module, as well as machine learning classifiers. Furthermore, the system substitutes conventional, complex modelling techniques with a robust, artificial intelligence approach. The findings presented are of interest to researchers, fish farmers, and aquaculture technologist wanting to gain insights into the productivity of fish and fish behaviour.

Deep Technology For Sustainable Fisheries And Aquaculture

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Author : Amaj Rahimi-Midani
language : en
Publisher:
Release Date : 2023

Deep Technology For Sustainable Fisheries And Aquaculture written by Amaj Rahimi-Midani and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.

This book uses real-world examples from the aquaculture industry to demonstrate how deep technology is assisting farmers and vulnerable communities. Works conducted by Poseidon-AI (a deep tech company involved in the aquaculture sector) in different countries are presented as case studies to show the positive impacts of deep tech involvement in the aquaculture sector. Primary industries, such as fisheries and aquaculture, rely heavily on labor. Furthermore, the manual practices of these farming methods increase material waste and reduce yields, resulting in higher costs and lower revenues. Poikilotherms make up the majority of aquatic animals, and environmental changes have a significant impact on them. This means that, due to climate change, farming of these animals cannot continue in the same way that it has for centuries. Artificial intelligence, machine learning, image processing, sensing, and automation are approaches that can assist these farms in dealing with rapid environmental changes while also assisting farmers in growing their businesses sustainably. This book is of interest to climate change scientists, entrepreneurs, investors, civil workers, and policymakers. Furthermore, the book is a great complimentary material for graduate students of fisheries, aquaculture, ecology, soil science, water management and environmental sciences. All national and international policymakers working in implementation of UNSDGs and sustainability, will find this book a useful read. .

Harnessing Machine Learning Techniques For Large Scale Mapping Of Inland Aquaculture Waterbodies In Bangladesh

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Author : Hannah Ferriby
language : en
Publisher:
Release Date : 2021

Harnessing Machine Learning Techniques For Large Scale Mapping Of Inland Aquaculture Waterbodies In Bangladesh written by Hannah Ferriby and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Electronic dissertations categories.

Aquaculture in Bangladesh has grown dramatically in an unplanned manner in the past few decades, becoming a major contributor to the rural economy in many parts of the country. National systems for the collection of statistics have been unable to keep pace with these rapid changes, and more accurate, up to date information is needed to inform policymakers. Using Sentinel-2 Top of Atmosphere Reflectance images within Google Earth Engine and ArcGIS platforms, we proposed six strategies for improving fishpond detection as the existing techniques seem unreliable. The study area is comprised of seven districts in south-west and south-central Bangladesh. The tested strategies include: 1) identification of the best period for image collection, 2) testing the buffer size for threshold optimization, 3) determining the best combination of image reducer and water-identifying indices, 4) introduction of a convolution filter to enhance edge-detection, 5) evaluating the impact of ground-truthing data on machine learning algorithm training, and 6) identifying the best machine learning classifier. Each enhancement builds on the previous one to develop a comprehensive improvement strategy called the Enhanced Method for fishpond detection. We compared the results of each improvement strategy to the known ground-truthing fishponds as the metric of success. We compared the precision, recall, and F1 score for machine learning classifiers to determine the quality of results. Among the studied methods, the Classification and Regression Trees performed the best. Overall, the proposed strategies enhanced fishpond area detection in all districts within the study area.

Machine Learning Approaches To Identify Genes Underlying Aquaculture Production Traits In Striped Bass And Their Hybrid

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Author : Linnea Kathryn Andersen
language : en
Publisher:
Release Date : 2022

Machine Learning Approaches To Identify Genes Underlying Aquaculture Production Traits In Striped Bass And Their Hybrid written by Linnea Kathryn Andersen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.

Development Of Benthic Monitoring Approaches For Salmon Aquaculture Sites Using Machine Learning Hydroacoustic Data And Bacterial Edna

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Author : Ethan Gerald Armstrong
language : en
Publisher:
Release Date : 2019

Development Of Benthic Monitoring Approaches For Salmon Aquaculture Sites Using Machine Learning Hydroacoustic Data And Bacterial Edna written by Ethan Gerald Armstrong and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.

Intensive caged salmon production can lead to localized perturbations of the seafloor environment where organic waste (flocculent matter) accumulates and disrupts ecological processes. As the aquaculture industry expands, the development of tools to rapidly detect changes in seafloor condition is critical. Here, we examine whether applying machine learning to two types of monitoring data could improve environmental assessments at aquaculture sites in Newfoundland. First, we apply machine learning to single beam echosounder data to detect flocculent matter at aquaculture sites over larger areas than currently achieved used drop camera imaging. Then, we use machine learning to categorize sediments by levels of disturbance based on bacterial tetranucleotide frequency distributions generated from environmental DNA. While echosounder data can detect flocculent matter with moderate success in this region, bacterial tetranucleotide frequencies are highly effective classifiers of benthic disturbance; this simplified environmental DNA-based approach could be implemented within novel aquaculture benthic monitoring pipelines.

An Introduction To Sustainable Aquaculture

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Author : Daniel Peñalosa Martinell
language : en
Publisher: Taylor & Francis
Release Date : 2024-04-09

An Introduction To Sustainable Aquaculture written by Daniel Peñalosa Martinell and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-09 with Business & Economics categories.

This new textbook provides an accessible introduction to sustainable aquaculture through its relationship with three key pillars: the environment, the economy, and society. As the demand for seafood keeps increasing, aquaculture is considered one of the most promising and sustainable ways to satisfy this demand with nutritious and high-quality food. It is important to understand, therefore, the wider role and impact aquaculture has on the environment, the economy, and society. The book begins by providing a foundational introduction to aquaculture and sustainability, discussing the complex and interdependent relationship that exists between the two. The core text of the book is divided into four parts which focus on the environment, economics, social impacts, and governance and technologies. Chapters examine key issues surrounding climate change, food security, new technologies, bioeconomics and risk analysis, international cooperation, employment, and animal welfare, with the book concluding with a chapter examining the future directions and challenges for the aquaculture industry. The book draws on global case studies and each chapter is accompanied by recommended reading and chapter review questions to support student learning. This book will serve as an essential guide for students of aquaculture, fisheries management, and sustainable food, as well as practitioners and policymakers engaged in sustainable fishery development.

Feed And Feeding Practices In Aquaculture

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Author : D. Allen Davis
language : en
Publisher: Woodhead Publishing
Release Date : 2022-05-28

Feed And Feeding Practices In Aquaculture written by D. Allen Davis and has been published by Woodhead Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-28 with Technology & Engineering categories.

Feed and Feeding Practices in Aquaculture, Second Edition continues to play an important role in the successful production of fish and other seafood for human consumption. This is an excellent resource for understanding the key properties of feeds for aquaculture, advances in feed formulation and manufacturing techniques, and the practicalities of feeding systems and strategies. Many new updates have been integrated to reflect recent advances within the market, including special emphasis on up-and-coming trends and new technologies on monitoring fish feeding patterns, making this book useful for anyone working in R&D in the production of feed, as well as nutritionists, farm owners and technicians, and academics/postgraduate students with a research interest in the area. Includes new research information on using feed to enhance the sensory qualities of fish Presents the latest research in aquafeed and processing Provides the latest information on regulatory issues regarding feed and fish health

Machine Learning In Biological Sciences

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Author : Shyamasree Ghosh
language : en
Publisher: Springer Nature
Release Date : 2022-05-04

Machine Learning In Biological Sciences written by Shyamasree Ghosh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-04 with Medical categories.

This book gives an overview of applications of Machine Learning (ML) in diverse fields of biological sciences, including healthcare, animal sciences, agriculture, and plant sciences. Machine learning has major applications in process modelling, computer vision, signal processing, speech recognition, and language understanding and processing and life, and health sciences. It is increasingly used in understanding DNA patterns and in precision medicine. This book is divided into eight major sections, each containing chapters that describe the application of ML in a certain field. The book begins by giving an introduction to ML and the various ML methods. It then covers interesting and timely aspects such as applications in genetics, cell biology, the study of plant-pathogen interactions, and animal behavior. The book discusses computational methods for toxicity prediction of environmental chemicals and drugs, which forms a major domain of research in the field of biology. It is of relevance to post-graduate students and researchers interested in exploring the interdisciplinary areas of use of machine learning and deep learning in life sciences.

Deep Technology For Sustainable Fisheries And Aquaculture

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Author : Amaj Rahimi-Midani
language : en
Publisher: Springer Nature
Release Date : 2023-08-12

Deep Technology For Sustainable Fisheries And Aquaculture written by Amaj Rahimi-Midani and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-12 with Science categories.

This book uses real-world examples from the aquaculture industry to demonstrate how deep technology is assisting farmers and vulnerable communities. Works conducted by Poseidon-AI (a deep tech company involved in the aquaculture sector) in different countries are presented as case studies to show the positive impacts of deep tech involvement in the aquaculture sector. Primary industries, such as fisheries and aquaculture, rely heavily on labor. Furthermore, the manual practices of these farming methods increase material waste and reduce yields, resulting in higher costs and lower revenues. Poikilotherms make up the majority of aquatic animals, and environmental changes have a significant impact on them. This means that, due to climate change, farming of these animals cannot continue in the same way that it has for centuries. Artificial intelligence, machine learning, image processing, sensing, and automation are approaches that can assist these farms in dealing with rapid environmental changes while also assisting farmers in growing their businesses sustainably. This book is of interest to climate change scientists, entrepreneurs, investors, civil workers, and policymakers. Furthermore, the book is a great complimentary material for graduate students of fisheries, aquaculture, ecology, soil science, water management and environmental sciences. All national and international policymakers working in implementation of UNSDGs and sustainability, will find this book a useful read.

Unsupervised Deep Anomaly Detection In A Recirculating Aquaculture System

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Author : William Robinson
language : en
Publisher:
Release Date : 2020

Unsupervised Deep Anomaly Detection In A Recirculating Aquaculture System written by William Robinson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.

An unsupervised deep anomaly detection system is implemented to augment the water quality monitoring system used at a recirculating aquaculture system (RAS) facility. Its purpose is to increase the system's anomaly detection capabilities by improving its accuracy and decreasing the timeframe in which anomalies can be detected. Quick and precise detection of abnormalities leads to earlier action to reduce mortalities within the fish population, or prevent them altogether. The machine learning model introduced in this work, given the name aMSCRED or adaptive Multi-Scale Convolutional Recurrent Encoder-Decoder, is an expansion of the MSCRED model featured in previous work by Zhang et al.[1] This model is a spatio-temporal network (STN) composed of stacked CNNs and RNNs, structured in an autoencoder architecture. This configuration is capable of learning what characterizes normal behaviour within a multivariate timeseries dataset, which can thereafter be leveraged to detect abnormal behaviour, which may indicate a problem in the system. Using data obtained from the monitoring system at the RAS facility, aMSCRED is able to outperform its predecessor in terms of anomaly detection performance (measured in terms of Recall, Precision and F1 score). Recall scores of up to 97% were achieved, as well as F1 scores of up to 94%. It also outperforms its predecessor in root cause identification (RCI), achieving accurate prediction rates of ∼ 70%, compared to ∼ 50% using the model from Zhang et al. The improved results are made possible due to modifications which enable the model to adaptively select, on a per-dataset basis, different signature matrix generating strategies, model structure parameters, anomaly scoring methodologies, and root cause scoring methodologies.