Search Results (23)

The global fauna of Didymozoidae infecting fishes is very diverse and includes 270 species. Integrative taxonomic studies in this group are rare, and genetic data are lacking for the molecular identification of species. In this study, a new genus and species, Platodidymocystis yamagutii n. gen., n. sp., is described based on morphological and genetic analyses. The new genus is allocated to Didymozoinae but differs from all other genera of this subfamily, mainly by the morphology of the testes and ovary. The genetic analysis and molecular phylogeny using 28S rDNA and ITS2 markers showed P. yamagutii n. gen., n. sp. in a unique cluster in monophyly and most closely related to Platocystis vivipara (Yamaguti, 1970), followed by Didymocystis spp. Additionally, Didymosulcus philobranchiarca (Yamaguti, 1970) was also characterized by integrative taxonomy and Koellikerioides internogastricus Yamaguti, 1970, Didymocystis neothunni (Yamaguti, 1970), and P. vivipara were analyzed by molecular taxonomy. This is the first integrative taxonomic study of Didymozoidae from the Atlantic coast and the first survey to provide novel genetic data for five species of Didymozoidae trematodes, contributing to the increment of the knowledge and expansion of the geographical distribution of didymozoid species parasites of Scombridae in the Southern Atlantic Ocean. Full article

Epipelagic fish communities dominate fish assemblages and are an important part of marine ecosystems due to their high abundance, vertical migration behavior, and global distribution. Purse seine fisheries are key components of marine fisheries in the tropical Western and Central Pacific Ocean (WCPO), primarily targeting skipjack tuna (Katsuwonus pelamis, SKJ), yellowfin tuna (Thunnus albacares, YFT), and bigeye tuna (Thunnus obesus, BET). In this study, WCPO purse seine fishery data from 2014 to 2022, combined with environmental factor data, were used, and Mantel tests and correlation analysis were employed to analyze the diversity, fish coexistence mechanisms, and environmental responses of catch communities under the following two different fishing strategies: free–swimming schools (FSCs) and drifting fish aggregating devices (DFADs). Mantel tests indicated that nitrate (NO_3⁻), the Oceanic Niño Index (ONI), and pH significantly impact the diversity of the FSCs community, whereas NO_3⁻ significantly affects the diversity of the DFADs community. Based on the correlation analysis results, in the FSCs community, yellowfin tuna was positively correlated with bigeye tuna, and yellowfin tuna was negatively correlated with skipjack tuna and black marlin (Istiompax indica, BLM). In the DFADs community, yellowfin tuna was only positively correlated with skipjack tuna and bigeye tuna. In addition, species with high correlations were also positively correlated. The results of this study provide a theoretical basis for the biodiversity conservation of catch communities under two different purse seine fishing strategies in the WCPO. Full article

The large pelagic species play an important role in transferring energy in vast distant marine ecoregions. Results obtained report on extraordinary findings of important commercial species in southeast–south Brazilian waters, including the Southern bluefin tuna Thunnus maccoyii and the Pacific bluefin tuna Thunnus orientalis, an endemic species from the Pacific Ocean. These specimens were identified within the genomic description of 10 individuals randomly selected from the catch to evaluate the catch composition of pelagic longline fisheries off Brazilian waters. Most of the records were from T. maccoyii (6), followed by the Bigeye tuna T. obesus (2), Yellowfin tuna T. albacares (1), and T. orientalis (1). Yellowfin and Bigeye tuna are expected to be captured in the vicinity of the longline fishing areas. However, the unlikely presence of the cold-water T. maccoyii and the warm-water T. orientalis suggests a long migration from common species ranges that could be influenced by climate change. These results imply a readjustment of spatial management structures for these species. Full article

Tuna are economically important as food resources in food markets. However, because tuna is often processed into steaks or fillets, the meat can be difficult to identify through morphological features. For effective fishery management and to protect the rights of consumers, it is necessary to develop a molecular method to accurately identify the species used in tuna products. Herein, we discovered five single-nucleotide polymorphism (SNP) sites via 2b-RAD sequencing and developed five SNP-based real-time polymerase chain reaction assays for the rapid identification of five highly priced tuna species. Three species-specific TaqMan systems were designed to identify albacore tuna (Thunnus alalunga), bigeye tuna (T. obesus), and southern bluefin tuna (T. maccoyii) and two cycling systems were designed to identify yellowfin tuna (T. albacares) and Atlantic bluefin tuna (T. thynnus). The systems showed good specificity and sensitivity (sensitivity of 0.0002 ng μL⁻¹ for albacore tuna, bigeye tuna, and southern bluefin tuna and 0.002 ng μL⁻¹ for yellowfin tuna and Atlantic bluefin tuna). Both systems were able to distinguish the target species from other species in a specific, sensitive, and accurate manner. Thus, these methods can be employed for the identification of species used in tuna products, protecting consumers and producers from economic fraud. Full article

Efficient and accurate fishery forecasting is of great significance in ensuring the efficiency of fishery operations. This paper proposes a fishery forecasting method using a brightness temperature (TB) time series spatial feature extraction and fusion model. Using Indian Ocean bigeye tuna fishery data from 2009 to 2021 as a reference, this paper discusses the feasibility of fishery forecasting using FY-3 Microwave Radiation Imager (MWRI) Level 1 TB data. For this paper, we designed a deep learning network model for radiometer TB time series feature extraction (TimeTB-FishNet) based on the Convolutional Neural Network (CNN), Gated Recurrent Unit (GRU), and Attention mechanism. After expanding the dimensions of TB features, the model uses them together with spatiotemporal feature factors (year, month, longitude, and latitude) as features. By adding the GRU and Attention to the CNN, the CNN-GRU-Attention model architecture is established and can extract deep time series spatial features from the data to achieve the best results. In the model validation experiments, the TimeTB-FishNet model performed optimally, with a coefficient of determination (R²) of 0.6643. In the generalization experiments, the R² also reached 0.6261, with a root mean square error (RMSE) of 46.6031 kg/1000 hook. When the sea surface height (SSH) was introduced, the R² further reached 0.6463, with a lower RMSE of 45.1318 kg/1000 hook. The experimental results show that the proposed method and model are feasible and effective. The proposed model can directly use enhanced radiometer TB data without relying on lagging ocean environmental product data, performing deep temporal and spatial feature extraction for fishery forecasting. This method can provide a reference for the fishing of bigeye tuna in the Indian Ocean. Full article

The Tongan fisheries targeting the species of albacore (Thunnus alalunga), bigeye (Thunnus obesus), skipjack (Katsuwonus pelamis), and yellowfin tuna (Thunnus albacares), comprising the main tuna catch landed, within the EEZ of Tonga is critical to the economy of Tonga. Thus, it is crucial to study the spatiotemporal pattern of their catch and the influence of environmental and physical variables, in addition to the month and year of the catch. To this end, sets of eight generalized additive models were applied to model the distribution of these four species. Selection among competing models was carried out based on k-fold cross-validation, using RMSPE prediction error as a measure of model predictive performance. The following sets of predictors were considered; sea surface temperature, sea surface chlorophyll, bottom depth, month, and year. In addition, to assess the influence of fronts, gradients in SST and Chl-a were computed and used as predictors. Catch year was the most important variable for all, except Albacore tuna, for which month was the important variable. The third most important variable was SST for albacore and bigeye tuna, whereas bottom depth was the most important variable for skipjack and yellowfin tuna. A standardized index of CPUE indicates mostly inter-annual variation in CPUE for albacore and bigeye tuna, whereas a it indicates a general increase in CPUE for skipjack and yellowfin tuna. Hotspots of albacore tuna catches are around the northern and southern edges of the exclusive economic zone and typically during the months of June to August. The bigeye tuna hotspots were concentrated on the eastern side of the islands, in waters overlying trenches; this was most obvious during the months of January to June. Skipjack tuna hotspots were near the edges of the exclusive economic zone, although it is caught in smaller amounts to the three tuna species considered and higher catch rates were observed only after 2014. For yellowfin tuna, the highest catch rates were concentrated around the islands and descending towards the southern edge of the EEZ. As part of the initiative of this study to support national optimal resource management, this study generated standardized CPUE (indices of abundance), an important input in stock assessment, and also looked into the potential influence of environmental and physical variables on the CPUE of these valuable tuna stocks within the EEZ of Tonga. Full article

Despite the crucial role played by international and regional tuna fisheries in facilitating the successful implementation of the ecosystem approach to fisheries management, there exist disparities in viewpoints among these stakeholders, resulting in gaps between regional fisheries management and local communities. Nevertheless, the Tongan government, under the Ministry of Fisheries, is dedicated to the efficient management of its tuna resources, aiming to establish it as the preferred and optimal approach for ensuring the long-term sustainability of its tuna fisheries and the ecosystem services they provide to the community. Recognizing that an appropriate legal, policy and institutional framework is in place for sustainable management of tuna, the first part of this paper presents a review of current Tonga fisheries laws and policies for its tuna fisheries. This review reflects the implementation of an information-based management framework, namely the Tonga National Tuna Fishery Management and Development Plan. The tuna fisheries in Tonga mainly catch albacore (Thunnus alalunga), bigeye (Thunnus obesus), skipjack (Katsuwonus pelamis), and yellowfin (Thunnus albacares) tuna. These tuna species are caught within Tonga’s exclusive economic zones and play a crucial role in the country’s economy; hence, it is crucial to examine the spatio-temporal distributions of their catch in relation to their environmental conditions. In pursuit of this goal, the tasks of mapping (i) the spatio-temporal distribution of catch landed at ports and (ii) the spatio-temporal of environmental conditions were performed. The study utilizes longline catch per unit effort data spanning from 2002 to 2018 for albacore, bigeye, skipjack, and yellowfin tuna. It also incorporates data on environmental conditions, including sea surface temperature, sea surface chlorophyll, sea surface current, and sea surface salinity. Additionally, the El Nino Southern Oscillation Index is mapped in relation to catch data to examine the potential effects of climate change on the tuna catch. Results show that bigeye, skipjack, and yellowfin CPUE show a central–northernmost distribution and are primarily caught between latitudes 14° S–22° S, while albacore, shows a central–southern distribution. The highest CPUE for all species are in latitudes 15.5° S–22.5° S and longitudes 172.5° W–176.5° W. The data indicate that sea surface current velocities range from −0.03 to 0.04 ms⁻¹, sea surface salinity ranges from 34.8 to 35.6 PSU, sea surface chlorophyll concentration varies from 0.03 to 0.1 mg m⁻³, and sea surface temperature fluctuates seasonally, ranging from 18 °C to 30 °C. Mapping also reveals that times of reduced catches in Tonga coincide with periods of moderate to strong El Nino events from 2002 to 2018. Full article

The potential impacts of climate change on the distribution of tuna in Pacific Island countries’ exclusive economic zones have yet to be investigated rigorously and so their persistence and abundance in these areas remain uncertain. Here, we estimate optimal fisheries areas for four tuna species: albacore (Thunnus alalunga), bigeye (Thunnus obesus), skipjack (Katsuwonus pelamis), and yellowfin (Thunnus albacares). We consider different climate change scenarios, RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5, within a set of tuna catch records in the exclusive economic zone of Tonga. Using environmental and CPUE datasets, species distribution modelling estimated and predicted these fisheries areas in the current and future climatic scenarios. Our projections indicate an expansion in area and a shift of productive areas to the southern part of this exclusive economic zone of Tonga. This is an indication that future climatic scenarios might be suitable for the species under study; however, changes in trophic layers, ocean currents, and ocean chemistry might alter this finding. The information provided here will be relevant in planning future national actions towards the proper management of these species. Full article

Tuna are economically important fish species. The automated identification of tuna species is of importance in fishery production and resource assessment in that it would facilitate the informed monitoring of tuna fishing vessels and the establishment of electronic observer systems. As morphological characteristics are important for tuna identification, this study aims to verify the performance of the automated identification of three Thunnus species through morphological characteristics based on different machine learning algorithms. Firstly, morphological outlines were visually analyzed using EFT (elliptic Fourier transform) and CNN (convolutional neural network). Then, the EFT feature data and deep feature data of the tuna outline images were extracted, and principal component analysis of the two different morphological characteristics was performed. Finally, different machine learning algorithms were used to analyze the identification performance of tuna of the same genus and different species. The experimental results showed that EFT features had the highest identification accuracy in KNN (K-nearest neighbor), with 90% for T. obesus, 90% for T. albacores, and 85% for T. alalunga. Deep features had the best identification performance in SVM (support vector machine), with 80% for T. obesus, 90% for T. albacores, and 100% for T. alalunga. Deep features were better than EFT features in identification performance. The biodiversity and intergeneric differences among tuna species can be well analyzed using these two different morphological characteristics. Machine learning algorithms open up the way for rapid near-real-time electronic observer systems in these important international fisheries. Full article

Bioaccumulation is the process by which living organisms accumulate substances, such as pesticides, heavy metals, and other pollutants, from their environment. These substances can accumulate in the organism’s tissues over time, leading to potential health risks. Bioaccumulation can occur in both aquatic and terrestrial ecosystems, and can have a significant impact on the health of both humans and wildlife. The objective of this study is to find out if the concentrations of metals in the tuna species of the Canary Islands are suitable for human consumption and if they pose a health risk. Fifteen samples of Acanthocybium solandri, Katsuwonus pelamis, Thunnus albacares, Thunnus obesus and Thunnus thynnus present in canaries were analyzed. Ten grams of muscle were taken from each specimen and the metals Al, Cd, Cr, Cu, Fe, Li, Ni, Pb and Zn were determined by Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES). The tuna species that presented more metals with a higher concentration compared to the others was T. thynnus, reaching up to 100 times more than the other studied species in Fe content with 137.8 ± 100.9 mg/Kg, which may be due to the fact that it is the largest species that reaches ages of more than fifteen years. The species Thunnus thynnus should not be suitable for commercialization according to the current legislation on the concentrations of Cd in blue fish, since 75% of the specimens studied exceeded the concentration legislated for Cd. A total of 40% of the studied specimens of this this species exceeded the legislated values for the concentration of Pb in oily fish meat, so this species must be monitored to ensure that it does not pose a risk to human health. Full article

Oceanic temperature fluctuations are one of the leading factors affecting marine fish populations. Indian Ocean Dipole (IOD), characterized as the sea surface temperature (SST) anomaly change, is an ocean–atmosphere interactive process causing interannual climate variability in the Indian Ocean. Influences of the IOD on the tuna catch rates are supported by previous research. Yet, there remains limited information about the impacts on the abundance of tuna stocks. In this study, we used the standardized Catch Per Unit Effort (CPUE) index to present the stock abundance and compared the effects of the IOD on the bigeye tuna (Thunnus obesus) and yellowfin tuna (Thunnus albacares) among different management areas of the Indian Ocean Tuna Commission (IOTC). Results show significant correlations between IOD events on both species’ abundance in the tropical western Indian Ocean. However, in the tropical eastern Indian Ocean and the southern Indian Ocean, neither bigeye nor yellowfin tuna abundances were significantly correlated by the IOD. For the whole Indian Ocean, IOD was significantly correlated uniquely with the yellowfin tuna abundance. Our results emphasized the importance of evaluating the climate variability effects over fisheries abundance species by species and per fishing areas analyses. Full article

There is a need to identify the species of similar types of fish, especially those that are commercially sold. Particularly, the price of tuna varies depending on its type, which is difficult to determine as they are sold in cut or processed forms. This study developed a multiplex polymerase chain reaction (PCR) assay to identify the five most common tuna species: bigeye, skipjack, Atlantic bluefin, albacore, and yellowfin tunas. Newly designed species-specific primer sets for these five tuna species were created. Subsequently, the amplicon sizes obtained were 270, 238, 200, 178, and 127 base pairs for bigeye, skipjack, Atlantic bluefin, albacore, and yellowfin tunas, respectively. Each primer’s specificity was further tested using 15 other fish species, and no cross-reactivity was observed. To identify multiple targets in a single reaction, multiplex PCR was optimized to increase its resolution and accuracy. The detection levels of the multiplex PCR assay were confirmed to be 1 pg for all the five tunas. Additionally, it was successfully applied to 32 types of commercial tuna products. Therefore, this multiplex PCR assay could be an efficient identification method for various tuna species. Full article

To avoid heat, treatment induces numerous physicochemical changes under severe conditions in the tuna, cold plasma (CP), as a non-thermal technology, possess objective potential on tuna processing. The effect of cold plasma on the volatile flavor compounds of bigeye tuna (Thunnus obesus) sashimi has been evaluated using electronic nose (E-nose) and gas chromatography-ion mobility spectrometry (GC-IMS). GC–IMS results revealed a total of 33 volatile compounds in tuna slices. The effect of CP treatment on tuna flavor was not significant, furthermore CP could protect volatile freshness compounds such as 1-hexanol. Principal component analysis (PCA) of the E-nose and GC–IMS results could effectively differentiate the effect of storage to tuna sashimi. There was a high correlation between the E-nose and GC–IMS results, providing a theoretical basis for establishing the flavor fingerprint of tuna sashimi. Full article

The performances of three non-destructive sensors, based on different principles, bioelectrical impedance analysis (BIA), near-infrared spectroscopy (NIR) and time domain reflectometry (TDR), were studied to discriminate between unfrozen and frozen-thawed fish. Bigeye tuna (Thunnus obesus) was selected as a model to evaluate these technologies. The addition of water and additives is usual in the fish industry, thus, in order to have a wide range of possible commercial conditions, some samples were injected with different water solutions (based on different concentrations of salt, polyphosphates and a protein hydrolysate solution). Three different models, based on partial least squares discriminant analysis (PLS-DA), were developed for each technology. This is a linear classification method that combines the properties of partial least squares (PLS) regression with the classification power of a discriminant technique. The results obtained in the evaluation of the test set were satisfactory for all the sensors, giving NIR the best performance (accuracy = 0.91, error rate = 0.10). Nevertheless, the classification accomplished with BIA and TDR data resulted also satisfactory and almost equally as good, with accuracies of 0.88 and 0.86 and error rates of 0.14 and 0.15, respectively. This work opens new possibilities to discriminate between unfrozen and frozen-thawed fish samples with different non-destructive alternatives, regardless of whether or not they have added water. Full article

The hydrolysates and peptide fractions of bigeye tuna (Thunnus obesus) skin collagen have been successfully studied. The hydrolysates (HPA, HPN, HPS, HBA, HBN, HBS) were the result of the hydrolysis of collagen using alcalase, neutrase, and savinase. The peptide fractions (PPA, PPN, PPS, PBA, PBN, PBS) were the fractions obtained following ultrafiltration of the hydrolysates. The antioxidant activities of the hydrolysates and peptide fractions were studied using the DPPH method. The effects of collagen types, enzymes, and molecular sizes on the antioxidant activities were analyzed using profile plots analysis. The amino acid sequences of the peptides in the fraction with the highest antioxidant activity were analyzed using LC-MS/MS. Finally, their bioactivity and characteristics were studied using in silico analysis. The hydrolysates and peptide fractions provided antioxidant activity (6.17–135.40 µmol AAE/g protein). The lower molecular weight fraction had higher antioxidant activity. Collagen from pepsin treatment produced higher activity than that of bromelain treatment. The fraction from collagen hydrolysates by savinase treatment had the highest activity compared to neutrase and alcalase treatments. The peptides in the PBN and PPS fractions of <3 kDa had antidiabetic, antihypertensive and antioxidant activities. In conclusion, they have the potential to be used in food and health applications. Full article