Aquaculture Management Research Articles

Comparing behavioral performance and physiological responses of Sebastes schlegelii with different aggressiveness.

In fish, aggression has significant individual differences, and different personalities exhibit distinct behavioral performances and physiological stress responses. Under intensive culture conditions, Sebastes schlegelii juveniles display severe aggression and cannibalism, causing damage to fish welfare and economic loss. Herein, we investigated the alterations in behavioral performance and physiological stress indicators of Sebastes schlegelii juveniles with different aggressiveness. The results revealed that latency to the first movement, distance to center point, mobile frequency, and immobile frequency were significantly lower in high-aggressive individuals than low-aggressive individuals. In contrast, the immobile time was significantly higher in high-aggressive individuals compared to low-aggressive individuals. PCA was performed to identify the key parameters of fish behavior. From the results of PCA, position, motion state, and physical status could be used as behavioral screening indicators for individuals with different aggressiveness. The 5-HIAA/5-HT ratio was significantly lower in high-aggressive individuals than in low-aggressive individuals. Moreover, cortisol levels were positively correlated with immobile time, and the ratio of 5-HIAA/5-HT was significantly and positively correlated with the distance to the central point. These results suggested that individuals with different aggressiveness can be effectively distinguished in a short period of time according to behavioral factors such as position, motion state, and physical status. For a single measure, the distance to center point associated with brain monoaminergic activity may be a more direct factor. The results could be a non-invasive method to measure fish aggression and fish welfare, and then build on to improve fish welfare and enhance aquaculture management.

Mask_LaC R-CNN for measuring morphological features of fish

In aquaculture management, the measurement of various morphological characteristics of fish, such as body length, body width, caudal peduncle length and width, pupil diameter and iris diameter, are the main information basis for breeders to feed, use drugs, catch, grade and make breeding characters analysis. Obtaining these information quickly and accurately can provide effective guidance for management and control in the aquaculture process, and it is conducive to improve production efficiency and increase income. By combining data expansion method and Mask_LaC R-CNN network, this paper realizes the accurate measurement of various morphological characteristics of fish, and design a non-contact measurement system of fish morphological parameters. Because the fish position and image contrast in the data set are too single, data expansion method such as shrinkage transformation, translation transformation, contrast transformation and adding noise are used to simulate a more real scene. For the loss function of Mask R-CNN, smooth L1 loss is improved by using the balanced L1 loss function; the convolution decomposition is used to realize the lightweight network structure, so that the model can accelerate the network while maintaining high accuracy. At the same time, the hole convolution can effectively improve the accuracy of the detection algorithm without additional parameters and computational cost. The enhanced data set and the Mask_LaC R-CNN experiment shows that the improved scheme improves the measurement accuracy. Under the pure background, the mIoU of 50 test images is 0.930, the relative error of body length is 1.46%, and the relative error of body width is 0.65%. Under the complex background, the mIoU of 50 test images is 0.934, the relative error of body length is 6.98%, and the relative error of body width is 8.05%.

Automatic Extraction of Marine Aquaculture Zones from Optical Satellite Images by R3Det with Piecewise Linear Stretching

In recent years, the development of China’s marine aquaculture has brought serious challenges to the marine ecological environment. Therefore, it is significant to classify and extract the aquaculture zone and spatial distribution in order to provide a reference for aquaculture management. However, considering the complex marine aquaculture environment, it is difficult for traditional remote sensing technology and deep learning to achieve a breakthrough in the extraction of large-scale aquaculture zones so far. This study proposes a method based on the combination of piecewise linear stretching and R3Det to classify and extract raft aquaculture and cage aquaculture zones. The grayscale value is changed by piecewise linear stretching to reduce the influence of complex aquaculture backgrounds on the extraction accuracy, to effectively highlight the appearance characteristics of the aquaculture zone, and to improve the image contrast. On this basis, the aquaculture zone is classified and extracted by R3Det. Taking the aquaculture zone of Sansha Bay as the research object, the experimental results showed that the accuracy of R3Det in extracting the number of raft aquaculture and cage aquaculture zones was 98.91% and 97.21%, respectively, and the extraction precision of the area of the aquaculture zone reached 92.08%. The proposed method can classify and extract large-scale marine aquaculture zones more simply and efficiently than common remote sensing techniques.

Potential implications of sperm DNA methylation functional properties in aquaculture management

AbstractThe biology of fish sperm, an important topic in the research of reproduction and fisheries from basic science to evolutionary and applied aspects, has implications for aquaculture management, fish breeding and biological conservation. The quality of spermatozoa plays a vital role in fish fertility, and directly affects the health and performance of offspring. Environmental factors that affect determinants of spermatozoa quality usually reflected in the DNA methylation pattern of the spermatozoa epigenome, which may change offspring's performance. The aim of the present study was to conduct a review on existing data about DNA methylation in fish spermatozoa as a biological tool for identifying the quality of offspring based on their phenotypes and performances. Furthermore, this study provides valuable knowledge from fundamental to applied sciences dealing with enhancement of breeding selection, fish reproduction and environmental adaptation. The review also describes the individual parts related to DNA methylation in fish, including overview of the methods which can be used to study DNA methylation, DNA methylation dynamics and epigenetic inheritance; identification of DNA methylation changes in sperm function in response to internal and external environment constraints, and potential relationships between DNA methylation and physiological regulation of spermatozoa quality determinants. Overall, the present study revealed that our knowledge about intergenerational inheritance of the performance and adaptability of fish through sperm DNA methylation is very limited, and no general conclusion could be approached from literature mostly due to non‐standardized experimental protocol or analytical tools.

Quantifying the 3D structure and function of porosity and pore space in natural sediment flocs

PurposeFlocculated cohesive suspended sediments (flocs) play an important role in all aquatic environments, facilitating the transport and deposition of sediment and associated contaminants with consequences for aquatic health, material fluxes, and morphological evolution. Accurate modelling of the transport and behaviour of these sediments is critical for a variety of activities including fisheries, aquaculture, shipping, and waste and pollution management and this requires accurate measurement of the physical properties of flocs including porosity.MethodsDespite the importance of understanding floc porosity, measurement approaches are indirect or inferential. Here, using μCT, a novel processing and analysis protocol, we directly quantify porosity in natural sediment flocs. For the first time, the complexity of floc pore spaces is observed in 3-dimensions, enabling the identification and quantification of important pore space and pore network characteristics, namely 3D pore diameter, volume, shape, tortuosity, and connectivity.ResultsWe report on the complexity of floc pore space and differentiate effective and isolated pore space enabling new understanding of the hydraulic functioning of floc porosity. We demonstrate that current methodological approaches are overestimating floc porosity by c. 30%.ConclusionThese new data have implications for our understanding of the controls on floc dynamics and the function of floc porosity and can improve the parameterisation of current cohesive sediment transport models.

Perturbation by Antimicrobial Bacteria of the Epidermal Bacterial Flora of Rainbow Trout in Flow-Through Aquaculture.

Simple SummaryThe epidermis and epidermal mucus layer of fish function as a first barrier against waterborne pathogens, while also providing niches for symbiotic microorganisms that can be beneficial to the host’s health. Controlling the composition of the fish skin microflora is important in pathogen management in aquaculture; however, our understanding of the characteristics of this microflora is limited. To elucidate the characteristics of fish skin bacterial flora, we examined the epidermal mucous of rainbow trout reared in flow-through aquaculture as an experimental model with environmental perturbations. Our experimental data indicate that some specific bacteria with antimicrobial activity enter from the natural environment and affect compositional changes in the skin mucous bacterial community by disturbing and occupying it. This perturbation by antimicrobial bacteria can “remodel” the fish skin bacterial flora and thereby affect the host′s health. This study provides novel information on factors influencing the composition of fish skin bacterial flora, which is applicable for controlling fish disease by using beneficial bacteria in aquaculture.The bacterial flora of the epidermal mucus of fish is closely associated with the host’s health and susceptibility to pathogenic infections. In this study, we analyzed the epidermal mucus bacteria of rainbow trout (Oncorhynchus mykiss) reared in flow-through aquaculture under environmental perturbations. Over ~2 years, the bacteria present in the skin mucus and water were analyzed based on the 16S rDNA sequences. The composition of the mucus bacterial community showed significant monthly fluctuations, with frequent changes in the dominant bacterial species. Analysis of the beta- and alpha-diversity of the mucus bacterial flora showed the fluctuations of the composition of the flora were caused by the genera Pseudomonas, Yersinia, and Flavobacterium, and some species of Pseudomonas and Yersinia in the mucus were identified as antimicrobial bacteria. Examination of the antimicrobial bacteria in the lab aquarium showed that the natural presence of antimicrobial bacteria in the mucus and water, or the purposeful addition of them to the rearing water, caused a transition in the mucus bacteria community composition. These results demonstrate that specific antimicrobial bacteria in the water or in epidermal mucus comprise one of the causes of changes in fish epidermal mucus microflora.

Sustainable IoT Solution for Freshwater Aquaculture Management

In recent years, we have seen the impact of global warming on changing weather patterns. The changing weather patterns have shown a significant effect on the annual rainfall. Due to the lack of annual rainfall, developing countries like India have seen a substantial loss in annual crop production. Indian economy largely depends on agro products. To compensate for the economic loss, the Indian government encouraged the farmers to do integrated aquaculture-based farming. Despite government subsidies and training programs, most farmers find it difficult to succeed in aquaculture-based farming. Aquaculture farming needs skills to maintain and monitor underwater environments. The lack of skills for monitoring and maintenance makes the aquaculture business more difficult for farmers. To simplify the pearl farming aquaculture, we have proposed an Internet of Things (IoT)-based intelligent monitoring and maintenance system. The proposed system monitors the water quality and maintains an adequate underwater environment for better production. To maintain an aquaculture environment, we have forecasted the change in water parameters using an ensemble learning method based on random forests (RF). The performance of the RF model compared with the linear regression (LR), support vector regression (SVR), and gradient boosting machine (GBM). The obtained results show that the RF model outperformed the forecast of the DO with 1.428 mean absolute error (MAE) and pH with 0.141 MAE.

Non-contact weight estimation system for fish based on instance segmentation

Non-contact methods for estimating cultured fish weight are essential for aquaculture companies to develop aquaculture strategies and management plans. However, it is challenging for current technologies to precisely measure the size of fish in a densely breeding environment and estimate the weight of fish because of issues including occlusion, fish bending and not facing the camera. This study, which focuses on the aforementioned issues, suggests a technique for creating an instance segmentation dataset appropriate for measuring fish size as well as an attention-based fully convolutional instance segmentation network (CAM-Decoupled-SOLO) to extract fish contour features. This study uses a concatenation approach to fuse low-level features and high-level features in order to safeguard low-level features so as to address the issue of low-level feature information loss in the bottom-up propagation process of feature pyramid networks. Additionally, by combining pixel location information with channel attention mechanism, this work achieves the integration of target location information and channel dimension information. To validate the developed methodology, it has been applied to an aquaculture system. The results showed that the mAP of proposed method would be improved by 2.6% compared with Decoupled-SOLO. Both qualitative and quantitative assessments would be enhanced when compared to the existing well-liked one-stage network. Moreover, to save labor cost and avoid fish damage, an automatic fish perimeter measurement model and a weight prediction system were constructed by combining fish contours extracted by CAM-Decoupled-SOLO and binocular vision. There was a significant correlation between fish perimeter and weight, which can be used to estimate the weight of fish in complex aquaculture environments.

Characteristics of the flow field inside and around a square fish cage considering the circular swimming pattern of a farmed fish school: Laboratory experiments and field observations

The management of marine aquaculture requires an accurate assessment of environmental impacts to achieve an environmentally sustainable system. To study the influence of farmed fish schools on the flow field around a fish cage, a pseudo-fish-school structure model was developed to simulate the circular swimming patterns of farmed fish in laboratory experiments. The drag force acting on the fish cage and current velocities inside and around a modeled square fish cage were investigated. A field survey was also conducted. As a result, the non-uniformity and complexity of the flow field of a stocked cage were observed in laboratory experiments. Circular swimming patterns were found to have obvious influences on the flow field distribution. The drag force of the square fish cage decreased by 11.8% because of the presence of the fish-school structure. Based on the field measurements, the averaged velocity inside and downstream of the full-scale fish cage was reduced by 46.2% and 57.8%, respectively. An acceleration was also observed in the current velocity below the fish cage. The vertical mixing of seawater may be because of the water blockage resulting from the cage and the circular swimming pattern of farmed fish schools. The findings presented in this study can be used as benchmarks for numerical models in assessing the potential environmental impact of fish farm sites.

Underwater fish mass estimation using pattern matching based on binocular system

Fish mass is the main information for judging growth status, regulating water quality environment, and precision feeding and grading in the process of intelligent aquaculture management activities. However, the occlusion, bending, and poor imaging angle of fish body image are still serious challenges for underwater fully automatic mass measurement. The aim of this study was to develop underwater non-contact method to automatically estimate the free-swimming fish mass based on binocular stereo vision technology. The fish body images were automatically selected and obtained by using pattern recognition method based on LabVIEW development platform during the experimental period. All the fish samples were divided into three groups according to mass (200–500 g, 500–800 g, and 800–1200 g), and then subdivided into three groups by imaging angle (orthogonal angles, greater than 45°, and less than 45°). The experiment indicated that the fish mass could be estimated using fish body area with a high coefficient of determination (R2) based on linear model. The mean relative errors between estimated and measured value were 3.37% (orthogonal angles), 4.95% (greater than 45° angles), and 16.59% (less than 45° angles). Significant difference was found in less than 45° group with p < 0.01. These findings showed that the approach put forward in this research could realize fully automatic mass estimation for underwater free-swimming fish and effectively improve the estimation robustness and efficiency.

Optimisation of at-sea culture and harvest conditions for cultivated Macrocystis pyrifera: yield, biofouling and biochemical composition of cultured biomass

Seaweed cultivation is gaining interest world-wide for both food and non-food applications. Global seaweed aquaculture production currently exceeds 32 Mt WW per annum but is dominated (86% of total) by Asian countries. To meet future demand for seaweed products, regions beyond Asia with aquaculture production potential are being explored. The goal of this study was to assess the suitability of the native kelp Macrocystis pyrifera (Phaeophyceae, Laminariales), for aquaculture in Tasmania, south-eastern Australia. M. pyrifera was cultivated on seeded twine on loops (1 – 5 m depth) along 100-m longlines at two sites (Okehampton Bay and Great Taylor Bay) from April-November 2020. Temporal and spatial variability in (1) yield (kg m-1, WW), (2) biofouling (% coverage), and (3) biochemical composition (including proximate composition, fatty acids, dietary minerals, heavy metal profiling, C, N, H, S concentrations and C:N ratio, antioxidants (phenolic compounds), and pigments (Chl-a, Chl-c, fucoxanthin)) was compared amongst the two cultivation sites, at two depths (1 and 5 m) from harvests between July – November 2020. Yield (kg m-1, WW) did not significantly change across harvest times, but was greater at a depth of 1 m compared to 5 m. Biofouling on the kelp blades increased significantly in early spring (September). The biochemical composition of the cultured biomass varied over time, between sites and with depth for most of the compounds analysed. Higher lipid, protein and ash content was reported for cultures cultivated at Okehampton Bay compared to Great Taylor Bay and at 5 m compared to 1 m depth, and levels of these macronutrients decreased during the harvest period. The iodine content was slightly above the tolerable content for dried seaweed products in Australia and New Zealand. The combined results of yield, biofouling, and biochemical composition suggest that, for an April deployment at the sites investigated, M. pyrifera should be harvested in July-August (mid to late winter) to optimise yield and quality of the cultured kelp biomass. These findings provide a better understanding of the variation in growth and quality of cultivated M. pyrifera biomass in the region, and inform future management and development of kelp aquaculture in south-eastern Australia and in a global context.

Influence mechanisms of macro‐infrastructure on micro‐environments in the recirculating aquaculture system and biofloc technology system

AbstractAquaculture intensification has emerged as a potential sustainable aquaculture strategy to contribute to the Food and Agriculture Organisation's United Nations Sustainable Development Goals associated with food security. Recirculating aquaculture systems (RASs) and biofloc technology systems (BFTs) are typical land‐based intensive aquaculture facility models that have been widely researched and applied. The rapid growth of both systems has boosted human nutrition and the regional economy but has also caused concerns about animal welfare, ecological protection, water treatment effectiveness and public health. One of the key links between aquaculture and ecological issues is the treatment of harmful particulates in wastewater, particularly organic metabolic microparticles. These microparticles are derived from decomposition waste feed, faeces and biofilm and provide a surface for bacterial growth and proliferation. The increase in microparticle abundance can directly affect bacterial activity and abundance and adversely affect the environment. Furthermore, the decomposition and motion of these particles are related to the mechanical stress caused by the water flow pattern in aquaculture tanks. The internal configurations of the tank can control the hydrodynamic characteristics, such as the water velocity, uniformity, pressure and turbulence in aquaculture tanks, and thus influence the morphology of particles. This review analyses and discusses how macro‐infrastructure influences the microenvironment in aquaculture tanks. These results provide a theoretical foundation and practical implications for improving the performance of aquaculture systems and environmental management in intensive aquaculture. It is concluded that optimisation of infrastructure design is key to improving the water flow patterns and self‐cleaning performance of tanks and achieving high efficiency of RASs and BFTs, and is critical for the fulfilment of the Sustainable Development Goals in aquaculture.

A PCA-EEMD-CNN-Attention-GRU-Encoder-Decoder Accurate Prediction Model for Key Parameters of Seawater Quality in Zhanjiang Bay.

In order to effectively solve the problem of low accuracy of seawater water quality prediction, an optimized water quality parameter prediction model is constructed in this paper. The model first screened the key factors of water quality data with the principal component analysis (PCA) algorithm, then realized the de-noising of the key factors of water quality data with an ensemble empirical mode decomposition (EEMD) algorithm, and the data were input into the two-dimensional convolutional neural network (2D-CNN) module to extract features, which were used for training and learning by attention, gated recurrent unit, and an encoder–decoder (attention–GRU–encoder–decoder, attention–GED) integrated module. The trained prediction model was used to predict the content of key parameters of water quality. In this paper, the water quality data of six typical online monitoring stations from 2017 to 2021 were used to verify the proposed model. The experimental results show that, based on short-term series prediction, the root mean square error (RMSE), mean absolute percentage error (MAPE), and decision coefficient (R2) were 0.246, 0.307, and 97.80%, respectively. Based on the long-term series prediction, RMSE, MAPE, and R2 were 0.878, 0.594, and 92.23%, respectively, which were all better than the prediction model based on an enhanced clustering algorithm and adam with a radial basis function neural network (ECA–Adam–RBFNN), a prediction model based on a softplus extreme learning machine method with partial least squares and particle swarm optimization (PSO–SELM–PLS), and a wavelet transform-depth Bi–S–SRU (Bi-directional Stacked Simple Recurrent Unit) prediction model. The PCA–EEMD–CNN–attention–GED prediction model not only has high prediction accuracy but can also provide a decision-making basis for the water quality control and management of aquaculture in the waters around Zhanjiang Bay.

Assessing carbon greenhouse gas emissions from aquaculture in China based on aquaculture system types, species, environmental conditions and management practices

Aquaculture is one of the fastest growing food production sectors in the world, but many of the small-hold operations are poorly assessed for their climate impact. We analyzed the literature data on CO2 and CH4 fluxes from various aquaculture systems in China. The mean fluxes varied in the ranges of − 382.45–551.88 g CO2-C m−2 yr−1 and − 0.03–565.09 g CH4-C m−2 yr−1. Aquaculture system reclaimed from mudflat had the highest CH4 emission (54.92 ± 21.00 g C m−2 yr−1) but lowest CO2 emission. Shrimp aquaculture and semi-intensive farming tended to yield higher CH4 emission. Small and shallow systems had significantly higher CO2 and CH4 emissions, with chlorophyll a and dissolved oxygen concentrations as the main environmental drivers. Management practice such as drainage, exposure and desilting during the non-farming period significantly decreased CH4 emission. We estimated that aquaculture systems in China emitted 181.66 Tg CO2-eq yr−1, offsetting ~7% of the national terrestrial carbon sink, with most of the emission concentrated in coastal provinces and along the major rivers in the southeastern quadrant. This study highlights the importance of accounting for greenhouse gas emissions from aquaculture to improve the accuracy of the regional and national carbon budgets.

Towards Sustainable Aquaculture: A Brief Look into Management Issues

Aquaculture’s role has expanded over the past two decades, with the industry contributing to nearly 50% of the overall fish production. Aquaculture production in Asia and Africa contributes a significant share of total global aquaculture output growth. Aquaculture supports livelihoods and income improvement in a number of states, despite the fact that economic situations have indeed been unfavourable and environmental concerns remain undeniable. To meet the growing demand for fish, aquaculture must expand. However, this expansion will not be sustainable unless management and planning are significantly improved. Local, national, and international management are needed to address the social, economic, and environmental problems. These provide the foundation to proper aquaculture management strategies. In considering the involved ecology, water quality, and genetics, aquaculture can have a detrimental impact on the environmental sustainability. This paper highlights the review on site selection with capacity evaluation, analysis of threats and risks, as well as certification and standards, which are all important considerations in achieving a sustainable aquaculture industry.

Toward integrated pest management in bivalve aquaculture.

Pests of bivalve aquaculture are a challenging problem that can reduce productivity, profitability and sustainability. A range of pest management approaches have been developed for bivalve aquaculture, but a general absence of guiding frameworks has limited the scale and permanency of implementation. Applying principles of 'integrated pest management' (IPM) could change this paradigm to improve economic and environmental outcomes. We reviewed existing research and tools for pest management in bivalve aquaculture, with studies grouped under five pillars of IPM: pest ecology (25 studies), bioeconomic cost-benefits (4 studies), continual monitoring (17 studies), proactive prevention (32 studies) and reactive control (65 studies). This body of knowledge, along with insights from terrestrial agriculture, provide a strong foundation for developing and implementing IPM in bivalve aquaculture. For example, IPM principles have been applied by a regional collective of oyster farmers in the US Pacific Northwest to optimize pesticide application and search for other options to control problematic burrowing shrimps. However, IPM has not yet been broadly applied in aquaculture, and data gaps and barriers to implementation need to be addressed. Priorities include establishing meaningful pest-crop bioeconomic relationships for various bivalve farming systems and improving the efficacy and operational scale of treatment approaches. An IPM framework also could guide potential step-change improvements through directing selective breeding for resistance to pests, development of bespoke chemical control agents, applying emerging technologies for remote surveillance and farm management, and regional alignment of management interventions. © 2022 Society of Chemical Industry.

A Dynamic Energy Budget Model for Kuruma Shrimp Penaeus japonicus: Parameterization and Application in Integrated Marine Pond Aquaculture.

Simple SummaryIndividual growth models of animals are the basis of ecosystem models, which are important tools for aquaculture management. The lack of mechanistic growth model studies of kuruma shrimp, an important integrated marine aquaculture species, has hindered ecosystem-level aquaculture management. In this study, an individual growth model of kuruma shrimp was constructed based on the dynamic energy budget theory, and the goodness of fit of both parameterization and application was high. The results showed that the model could reproduce the growth of kuruma shrimp in terms of total length and wet weight.Individual growth models can form the basis of population dynamics assessment and ecosystem model construction. In order to provide a basic module for an ecosystem model of an integrated marine aquaculture pond, an individual growth model was constructed for kuruma shrimp (Penaeus japonicus) based on dynamic energy budget (DEB) theory. The model was first parameterized based on a covariation method using the Add-my-Pet (AmP) procedure. The parametric estimation model underestimated the ultimate abdominal length for female shrimp, and the predicted values of other zero-variate parameters were generally consistent with observed values. The relative errors of the predicted and observed values of the univariate data set within three geographical regions showed acceptable goodness of fit. Parameter estimation achieved an overall goodness of fit with a mean relative error of 0.048 and a symmetric mean squared error of 0.066. A DEB model was constructed using the estimated parameters, and the goodness-of-fit indicators (R square, mean bias and absolute and relative root mean square error) showed that the model was able to reproduce the growth of kuruma shrimp in terms of total length and wet weight with high accuracy. The results provide data to support the subsequent development of integrated aquaculture management at the ecosystem level.

Nile tilapia (Oreochromis niloticus Linnaeus, 1758) culture in Kenya: Emerging production technologies and socio‐economic impacts on local livelihoods

AbstractNile tilapia (Oreochromis niloticus) is one of the most farmed fish globally, with a significant contribution improving local livelihoods, especially in developing countries. Nile tilapia was first cultured in Kenya in 1924 and is the most cultured fish species. Annually, O. niloticus accounts for 62% (∼15,000 tonnes) of total aquaculture production. Although O. niloticus is the most preferred cultured fish, its culture faces challenges, for example, early maturation due to prolific breeding behaviour leading to stunted growth that limits its culture and profitability among smallholder farmers. With the surging demand for locally farmed fish, innovative technologies have emerged to boost aquaculture production. Donor and public research‐funded projects, for instance, the Kenya Climate Smart Agriculture Project, are validating various aquaculture technologies, innovations and management practices (TIMPs) to achieve ‘triple wins’ of increased fish production, improved resilience and reduced greenhouse gas emissions. In addition, the International Fund for Agricultural Development (IFAD)‐funded Aquaculture Business Development Programme aims at commercialising aquaculture to improve local livelihoods. In this study, we adopt a scoping review methodology to review and synthesise published literature on tilapia culture in Kenya to explore current and emerging tilapia production technologies and document their socio‐economic impacts on farmers’ livelihoods. These emerging innovative technologies range from culture systems, for example, biofloc, periphyton, fingerpond technology, integrated aquaculture, breeding and genetics (selective breeding), fish health and biosecurity measures, to post‐harvest loss reduction, value addition and marketing. The study findings reveal that the technologies have great potential to increase tilapia production and profitability and positively impact the local livelihoods of smallholder fish farmers through employment creation, economic growth and better nutrition.

Dietary supplementation of archaeal carotenoids improved antioxidative capacity and regulated immune‐related gene expression of golden trout Oncorhynchus mykiss against challenge

Archaeal carotenoids, as novel bioactive compound, are stronger free radical scavenger. The effects of archaea Halorubrum carotenoids on skin coloration, antioxidative status and immune-related genes expression of golden trout Oncorhynchus mykiss were investigated. In total, 420 fish (10.90 ± 0.06 g) were divided into three groups with four replicates, and fed with commercial diets containing 0 (Ctrl), 25 mg/kg (P25) and 50 mg archaeal carotenoids/kg feed (P50) for 8 weeks. Although no significant difference was observed on growth, the fish fed archaeal carotenoids had significantly higher yellowness and carotenoid content (p < 0.05) in skin. Compared with the Ctrl group, the total antioxidant capacity (T-AOC) in serum was significantly enhanced in the P25 and P50 groups (p < 0.05), but no significant difference on lysozyme activity was obtained (p > 0.05). In liver, the catalase activity significantly decreased in the P50 group (p < 0.05), but T-AOC and superoxide dismutase activity was not significantly regulated by archaeal carotenoids (p > 0.05). The significant improvement of liver glutathione peroxidase in P50 group was observed, while malondialdehyde content significantly decreased (p < 0.05). After ammonia exposure and Aeromonas hydrophilia challenge, higher survival was observed in the P25 and P50 groups, associating with reducing the expression of pro-inflammation cytokines il-1β, but enhancing the expression of anti-inflammation cytokines tgf-β and hsp70. However, ammonia stress and pathogenic challenge caused opposite trends in the expression of tnf-α. Our study confirmed the beneficial role of archaeal carotenoids on skin coloration, antioxidative and immune systems of golden trout, and provided evidence for the potential application of this novel carotenoid in health management of aquaculture.

Remote sensing provides new insights on phytoplankton biomass dynamics and black pearl oyster life-history traits in a Pacific Ocean deep atoll

Thus far, no long-term in situ observation of planktonic biomass have been undertaken to optimize the black-lip pearl oyster aquaculture in the remote Tuamotu atolls. The feasibility of using data from the OLI sensor onboard Landsat-8 satellite to determine chlorophyll a concentrations (Chla) in a deep atoll, Ahe, was then assessed over the 2013–2021 period using 153 images. Validations with in situ observations were satisfactory, while seasonal and spatial patterns in Chla were evidenced within the lagoon. Then, a bioenergetic modelling exercise was undertaken to estimate oyster life-history traits when exposed to the retrieved Chla. The outputs provide spatio-temporal variations in pelagic larval duration (11.1 to 30.6 days), time to reach commercial size (18.8 to 45.3 months) and reproductive outputs (0.5 to 1.7 event year−1). This first study shows the potential of using remote sensing to monitor the trophic status of deep pearl farming lagoons and help aquaculture management.