Avenues and means for smart mariculture

Globally, aquaculture is one of the fast-growing production sectors using water productivity concepts. The term aquaculture refers to the practice of farming/ cultivating aquatic organisms that include finfish, shellfish and microscopic and macroscopic plants both in freshwater and saltwater in controlled conditions under human management. Farming/cultivation implies intervention in the rearing process to enhance production, breeding, nursery rearing, stocking, feeding, protection from predators, etc. It also implies individual or corporate ownership, the planning, development and operation of culture systems, sites, facilities and practices, and production and transport. The social and financial significance of aquaculture is growing consistently at >6% in recent years. India has immense potential for aquaculture development, and the sector contributed ≈70% to its total fish production in 2020

Good aquaculture practices and smart aquaculture

Globally, aquaculture stands out as one of the fastest-growing production sectors, employing water productivity concepts. Aquaculture encompasses the practice of cultivating aquatic organisms- finfish, shellfish, other invertebrates and microscopic and macroscopic plants- in controlled conditions under human management, both in freshwater and saltwater. Farming involves interventions such as breeding, nursery rearing, stocking, feeding, and protection from predators. It also includes aspects of individual or corporate ownership, planning, and development, operation of culture systems, sites, facilities, practices, production, and transport. According to the FAO (2014), aquaculture is the fastest-growing animal food sector worldwide, supplying approximately 50% of the fish consumed by humans. In 2020, global aquaculture production reached 122.6 million tons, with 54.4 million tons from inland waters and 68.1 million tons from marine and coastal aquaculture (mariculture), amounting to a total value of about USD 281.5 billion (FAO, 2022). Notably, the Asian region contributed a substantial 91.6% to this production, positioning India as the world’s second-largest aquaculture producer and the third-largest fish producer. The social and financial significance of aquaculture has consistently grown at over 6% in recent years, playing a vital role in global food production and addressing the increasing demand for protein sources, livelihoods, and income. In Afro-Asian countries, where aquaculture plays a vital role in cultural, economic, and nutritional aspects, the adoption of Good Aquaculture Practices and the embrace of Smart Aquaculture technologies become imperative for ensuring long-term food security and sustainable development. Through this lens, this article attempts to uncover the potential of Good Aquaculture Practices and Smart Aquaculture in shaping the future of aquaculture in Afro-Asian countries, striking a balance between economic growth, environmental stewardship, and societal well-being

Metodología de desarrollo de sistemas de detección y seguimiento de peces mediante tecnología láser y visión artificial con Inteligencia Artificial

Programa Oficial de Doutoramento en Tecnoloxías da Información e as Comunicacións. 5032V01[Resumen] En esta tesis se presenta una metodología de detección, seguimiento y medición de peces bajo el agua utilizando técnicas de teledetección. En la mayoría de las aplicaciones en las que se precisa la detección del pez y la medida de su tamaño, es imprescindible que se encuentren en su hábitat nadando libremente y sin ningún dispositivo eléctrico o mecánico colocado en el propio pez. De esta manera no se condiciona su comportamiento ni se somete a estrés que pudiera desencadenar situaciones no deseadas. Las técnicas de teledetección basadas en luz visible e infrarroja permiten detectar el pez sin contacto físico, sin embargo, es necesario adecuarlas para su correcto funcionamiento bajo el agua. En esta tesis se presenta esta metodología utilizando visión artificial y tres aplicaciones prácticas con dispositivos de detección basados en principios físicos diferentes. También se pretende indagar en la viabilidad de utilizar dispositivos, inicialmente diseñados para funcionar en entornos fuera del agua, que pueden ser adaptados mediante algoritmos informáticos en el seguimiento de objetos bajo el agua, y principalmente en la detección y medición de peces en su entorno acuático.[Resumo] Nesta tese preséntase unha metodoloxía de detección, seguimento e medición de peixes baixo a auga utilizando técnicas de teledetección. Na maioría das aplicacións nas que se precisa a detección do peixe e a medida do seu tamaño, é imprescindible que se atopen no seu hábitat nadando libremente e sen ningún dispositivo eléctrico ou mecánico colocado no propio peixe. Deste xeito non se condiciona o seu comportamento nin se somete a estrés que puidese desencadear situacións non deseadas. As técnicas de teledetección baseadas na luz visible e infrarvermella permiten detecar o peixe sen contacto físico, con todo, é preciso adecualas para o seu correcto funcionamento baixo a auga. Nesta tese preséntase esta metodoloxía utilizando visión artificial e tres aplicacións prácticas con dispositivos de detección baseados en principios físicos diferentes. Tamén se pretende indagar na viabilidade de utilizar dispositivos inicialmente deseñados para funcionar en contornas fora da auga, que poden ser adaptados mediante algoritmos informáticos no seguimento de obxectos baixo a auga e, principalmente, na detección e medición de peixes na súa contorna acuática.[Abstract] This PhD thesis presents a methodology to underwater fish detection, tracking and measuring, using remote sensing techniques. In most cases the applications where fish detection and size measurement is required, it is essential that they are in their hábitat, swimming freely and without any electrical or mechanical device attached to the fish itself. In this way, their behavior is not conditioned or they are subjected to stress that could cause unwanted situations. Remote sensing techniques based on visible light and infrared light allow the fish to be detected without physical contact however, it is necessary to adapt them for their correct operation under water. In this thesis, this methodology using computer vision and three practical applications with detection devices base don different physical principles are presented. In addition, this work studies the feasibility of using devices, initially designed to work in outside the water enviroments, which can be adapted by means of computer algorithms in the tracking of underwater objects, and mainly in the detection and measurement of fish in their environment

Emerging Technologies in Fisheries Science: A Transdisciplinary Report

The Pacific Coast Groundfish Fishery harvests a diverse and large grouping of fishes, but it did not become heavily fished until around WWII. This makes the groundfish fishery a comparatively young fishery. Despite its youth, it is one of the largest and most lucrative fisheries in Oregon—with a current harvest value of approximately $48 million per year, which is exceeded only by the Dungeness crab fishery. Northeastern Pacific Coast Groundfish species are also important for recreational and tribal purposes, although it is difficult to compare these to the commercial industry. With over 90 different species to consider, this commercial fishery is complex, and there are many different stakeholder groups involved, each with their own goals, values, and perspectives. Fishing regulations greatly impact local stakeholders, some of whom rely on the fishery for their livelihoods. These local stakeholders are dependent on accurate stock assessment surveys and models so that the fishing regulations are appropriate. Some stakeholders feel that regulations tend to be overly cautious to compensate for the large amount of uncertainty involved with managing a fishery and estimating a fish population. To reduce this uncertainty and the need to err so heavily on the side of caution, stock assessment surveys could include innovative technologies and novel datasets. For example, these stock assessments do not currently use automated video surveillance on their bottom trawl surveys, an emerging form of machine learning. As understood by the NSF-funded National Research Traineeship (NRT) training, there are three interwoven core concepts: 1) Big Data (BD), 2) Coupled Natural-Human (CNH) systems, and 3) Risk and Uncertainty (R&U) analysis and communication. Big Data refers to any high volume of data with high throughput. Coupled Natural-Human systems are the biological and human worlds, as well as their overlap and interaction. Risk is the potential and likelihood of an unfavorable event, and uncertainty refers to the unknowns of a likelihood, process, or analysis. This project chose to investigate these three concepts within the framework of emerging technologies and fisheries science. Emerging technologies are those dealing with BD, since this is a relatively new area of study, and this project specifically focused on computer vision within machine learning. This technology was applied to the realm of fisheries science and ultimately management, which is the study of a coupled natural-human system. Changing oceans conditions mean that Northeastern Pacific groundfish are at risk and their future is uncertain. Therefore, this project set out to determine how the influence of big data, machine learning, ecological inference, and environmental decision making overlap. The story of the life and study of these fishes in a newly Americanized sea is ready for a closer examination. It is for these reasons combined that Pacific coast groundfish fishery science provides a robust platform in which to explore the autonomous capacity of technology and data production at the intersection of environmental science and decision making. More specifically, to what extent are large, ecological datasets informing the production and application of emerging technologies in fisheries science, and how are these new technologies and sampling methods being integrated into fisheries management frameworks? A case study in which to explore this concept can be found in the testimony of a flatfish, or rather, the complex, ecologically and economically important assemblages of numerous groundfish species in the northeastern Pacific Ocean where flatfish are found

Video Analysis : Techniques for Semi-Supervised Video Object Instance Segmentation and Tracking-by-Detection in the Wild

This thesis consists of two major components. The first part is concerned with video object instance segmentation (VOS), which is the task of assigning per-pixel labels perframe of a video sequence to indicate foreground object instance membership, given the first frame ground truth mask. VOS has myriad applications, from video post-processing to action recognition, and is an active area of research. A novel end-to-end trainable, online algorithm utilizing a bilinear LSTM to learn long-term appearance models is presented. The bilinear LSTM is used to guide the learned CNN features, integrating temporal information and building more discriminative appearance features for specific objects during inference. The second part of this thesis examines computer vision's potential applications for performing automated ecological inference for endemic flat-fish populations. Specifically, it looks at the construction of a visual tracking dataset, NHFish, consisting of underwater beam trawl videos collected along the Newport Hydrographic Line of Oregon coast benthos and the application of automated methods for video analysis of the beam trawl videos

International Workshop cum Training on Fisheries and Aquaculture: African-Asian Rural Development Organization (AARDO)

The ICAR-Central Marine Fisheries Research Institute (CMFRI) stands as India’s premier marine fisheries research institution, distinguished by its robust infrastructure and a proficient workforce committed to research and development in marine fisheries, mariculture and other allied areas, including capacity building on both national and international fronts. Recognizing the pivotal role of the fisheries and aquaculture sector and the urgent need for sustainability, the African-Asian Rural Development Organization (AARDO), New Delhi, has strategically collaborated with CMFRI to provide training and skill development to persons from AARDO member countries. Sponsored by AARDO and the Ministry of Rural Development, Government of India, the capacity-building initiative was designed to benefit both India and AARDO member countries. The Workshop-cum-Training on ‘Fisheries Management and Aquaculture’ offered a significant opportunity for 11 participants from eight AARDO member countries such as Bangladesh, Ghana, Zambia, Malaysia, Namibia, Nigeria, Oman and Egypt, to undergo the comprehensive training at CMFRI. This Course Manual, released on the occasion of the Workshop-cum-Training, is a compilation of lecture notes from eminent resource persons involved in the Programme. I am confident that this manual will serve as a valuable resource, enhancing the knowledge and competence of the participants in the fields of fisheries management and aquaculture, proving beneficial in their future endeavours in their respective countries. I extend gratitude to Dr Manoj Nardeosingh, the Secretary-General, of AARDO, New Delhi; Mr Rami Mahmoud Abdel Halim Qtaishat, Assistant Secretary-General, AARDO, New Delhi and Dr Khusnood Ali, Head and Programme Coordinator, AARDO, New Delhi, for being instrumental in selecting CMFRI to organize this Programme. Special thanks to Dr. A. Gopalakrishnan, Director of CMFRI, for facilitating the successful conduct of the Programme. I would also like to express appreciation to my fellow Coordinators, Dr. T. M. Najmudeen, Dr Boby Ignatius, Dr P. Shinoj, and Dr N. Rajesh, who played pivotal roles in ensuring the smooth execution of the Programme. My heartfelt appreciation goes to all the resource persons for their efficient engagement with the trainees, providing excellent lecture notes, and contributing valuable course materials as well as arranging various handson sessions. Dr. Santhosh, B., Head, Vizhinajm RC. of CMFRI and his team; Dr George Ninan, Director, ICAR-Central Institute of Fisheries Technology, Kochi, and Dr Shine Kumar C. S., Director, NIFPHATT, Kochi, facilitated the exposure visit of the participants. I acknowledge the unwavering support from the Mariculture and other Divisions, of CMFRI, including all technical staff, research scholars, and supporting staff, who played crucial roles in organizing the Programme. Special thanks to all Heads of Divisions at CMFRI for their support. I express my gratitude to the entire Administration and Finance and Accounts staff of CMFRI for their unwavering support and cooperation throughout the Programme