Duygu Sazlı, Danial Nassouhi, M. Ergönül, S. Atasağun
{"title":"A Comprehensive Review on Microplastic Pollution in Aquatic Ecosystems and Their Effects on Aquatic Biota","authors":"Duygu Sazlı, Danial Nassouhi, M. Ergönül, S. Atasağun","doi":"10.26650/ase20221186783","DOIUrl":"https://doi.org/10.26650/ase20221186783","url":null,"abstract":"","PeriodicalId":52866,"journal":{"name":"Aquatic Sciences and Engineering","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48794288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Effects of Size Grading on Growth Performance, Survival Rate and Cannibalism in Russian Sturgeon (Acipenser gueldenstaedtii) Larvae Under Small-Scale Hatchery Conditions","authors":"K. Ak","doi":"10.26650/ase20221202625","DOIUrl":"https://doi.org/10.26650/ase20221202625","url":null,"abstract":"","PeriodicalId":52866,"journal":{"name":"Aquatic Sciences and Engineering","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45426784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Benthic Macroinvertebrate Fauna (Clitellata and Chironomidae) of Lake Limni, Gümüşhane, Turkiye","authors":"Deniz Mercan","doi":"10.26650/ase20221195255","DOIUrl":"https://doi.org/10.26650/ase20221195255","url":null,"abstract":"","PeriodicalId":52866,"journal":{"name":"Aquatic Sciences and Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41495091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-09DOI: 10.26650/ase202221172568
Münevver Oral
{"title":"What Reference Genome Assemblies Tell Us and How to Detect the Best Available Version: A Case Study in Trout","authors":"Münevver Oral","doi":"10.26650/ase202221172568","DOIUrl":"https://doi.org/10.26650/ase202221172568","url":null,"abstract":"","PeriodicalId":52866,"journal":{"name":"Aquatic Sciences and Engineering","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41976070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Okan Yeler, G. Aydin, Belgin Çamur Elipek, S. Berberoglu
In this study, the long-term suitability of the area proposals for winter recreation activities in the Seyhan Basin (Türkiye), which is located in the Mediterranean and Central Anatolia regions and includes a large part of the Taurus Mountains, were examined ecologically. For this purpose, the predicted global warming scenarios in the basin and the anthropogenic impacts arising from the planned recreation areas were evaluated for the upper basin (recreation areas) and lower basin (water resources, agricultural lands, and settlements) using a hypothetical risk analysis. For this purpose, multispectral images were obtained by using Landsat 8 Oli Multispectral images of the snow areas in the region in January-February-March 2019, and a hypothetical ecological risk analysis was created considering a total of 5 pressure factors originating from global climate change and anthropogenic effects. These possible factors were determined as flood (S1), drought (S2), sedimentation (S3), aquatic nutrients (S4), and tourist density (S5). The effects of these factors on a total of four features (C1: water quality, C2: fauna-flora, C3: agricultural areas, and C4: settlements) in the region were evaluated by hypothetical grading based on the literature. According to the hypothesis results obtained by the formula and statistical calculations, it was determined that the flood factor (S1) that will occur due to possible snow melt due to global climate change in the winter recreation areas in the studied region is the most significant factor limiting the sustainable usage of the Basin. For this reason, it has been emphasized in this study that the possibility of regions being exposed to the effects of climate change in the future should be taken into account, especially when planning for winter recreation areas. At the end of this study, it was concluded that the ecological balance analysis of basins is important, especially in terms of ensuring the long-term sustainable use of winter recreation areas.
{"title":"Application of Hypothetical Ecological Risk Analysis to Sustainable Usage of Possible Winter Recreation Areas in Seyhan Basin (Türkiye)","authors":"Okan Yeler, G. Aydin, Belgin Çamur Elipek, S. Berberoglu","doi":"10.26650/ase20221115945","DOIUrl":"https://doi.org/10.26650/ase20221115945","url":null,"abstract":"In this study, the long-term suitability of the area proposals for winter recreation activities in the Seyhan Basin (Türkiye), which is located in the Mediterranean and Central Anatolia regions and includes a large part of the Taurus Mountains, were examined ecologically. For this purpose, the predicted global warming scenarios in the basin and the anthropogenic impacts arising from the planned recreation areas were evaluated for the upper basin (recreation areas) and lower basin (water resources, agricultural lands, and settlements) using a hypothetical risk analysis. For this purpose, multispectral images were obtained by using Landsat 8 Oli Multispectral images of the snow areas in the region in January-February-March 2019, and a hypothetical ecological risk analysis was created considering a total of 5 pressure factors originating from global climate change and anthropogenic effects. These possible factors were determined as flood (S1), drought (S2), sedimentation (S3), aquatic nutrients (S4), and tourist density (S5). The effects of these factors on a total of four features (C1: water quality, C2: fauna-flora, C3: agricultural areas, and C4: settlements) in the region were evaluated by hypothetical grading based on the literature. According to the hypothesis results obtained by the formula and statistical calculations, it was determined that the flood factor (S1) that will occur due to possible snow melt due to global climate change in the winter recreation areas in the studied region is the most significant factor limiting the sustainable usage of the Basin. For this reason, it has been emphasized in this study that the possibility of regions being exposed to the effects of climate change in the future should be taken into account, especially when planning for winter recreation areas. At the end of this study, it was concluded that the ecological balance analysis of basins is important, especially in terms of ensuring the long-term sustainable use of winter recreation areas.","PeriodicalId":52866,"journal":{"name":"Aquatic Sciences and Engineering","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46408833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-19DOI: 10.26650/ase202221163202
Jansi Rani Sella Veluswami, Nivetha Panneerselvam
Fish play a prominent role in the food web and fish farming has value for both human consumption and tourist attractions. Due to the increasing importance of marine biodiversity, recognition of fish species has become a prominent task in monitoring the mislabelling of seafood and extinct species. This problem can be solved using traditional manual annotation on the images. To reduce manpow-er, cost, and tremendous time, deep learning approaches are used which always require large datasets. Therefore, fish species identification is a challenging task using disproportionately small data sets. In this research, we develop a new method by refining the squeeze and excitation network for the automatic fish species classification model to identify 23 different types of fish species. To achieve this, a hybrid framework using deep learning is proposed on a large-scale dataset and implemented transfer learning for a small-scale dataset. Deep learning methods can be used to identify fish in underwater images. In this study, we have proposed a new method of hybrid Deep Convolutional Neural Network (CNN) along with a Support Vector Machine (SVM) for classification. Additionally, the Squeeze and Excitation (SE) block has been improved for improved feature extraction. The proposed method achieved an accuracy of 97.90%. Then post-training with the small-scale dataset (Croatian) achieved an accuracy of 94.99% with an 11% improvement compared to Bilinear CNN (B-CNN) (Qui et al., 2018) and can be used in any underwater applications to identify fish species and avoid mislabelling of seafood.
鱼类在食物网中发挥着重要作用，鱼类养殖对人类消费和旅游景点都有价值。由于海洋生物多样性的重要性日益增加，识别鱼类已成为监测海鲜和灭绝物种标签错误的一项突出任务。这个问题可以通过在图像上使用传统的手动注释来解决。为了减少人力、成本和大量时间，使用了总是需要大型数据集的深度学习方法。因此，使用不成比例的小数据集进行鱼类物种识别是一项具有挑战性的任务。在这项研究中，我们开发了一种新的方法，通过改进挤压和激励网络，用于鱼类物种的自动分类模型，以识别23种不同类型的鱼类。为了实现这一点，在大规模数据集上提出了一种使用深度学习的混合框架，并在小规模数据集上实现了迁移学习。深度学习方法可用于识别水下图像中的鱼类。在这项研究中，我们提出了一种新的混合深度卷积神经网络（CNN）和支持向量机（SVM）的分类方法。此外，为了改进特征提取，对挤压和激励（SE）块进行了改进。所提出的方法实现了97.90%的准确率。然后，与双线性CNN（B-CNN）（Qui et al.，2018）相比，使用小规模数据集（克罗地亚）进行的后训练实现了94.99%的准确率，提高了11%，可用于任何水下应用，以识别鱼类并避免海鲜标签错误。
{"title":"Multi-species Fish Identification using Hybrid DeepCNN with Refined Squeeze and Excitation Architecture","authors":"Jansi Rani Sella Veluswami, Nivetha Panneerselvam","doi":"10.26650/ase202221163202","DOIUrl":"https://doi.org/10.26650/ase202221163202","url":null,"abstract":"Fish play a prominent role in the food web and fish farming has value for both human consumption and tourist attractions. Due to the increasing importance of marine biodiversity, recognition of fish species has become a prominent task in monitoring the mislabelling of seafood and extinct species. This problem can be solved using traditional manual annotation on the images. To reduce manpow-er, cost, and tremendous time, deep learning approaches are used which always require large datasets. Therefore, fish species identification is a challenging task using disproportionately small data sets. In this research, we develop a new method by refining the squeeze and excitation network for the automatic fish species classification model to identify 23 different types of fish species. To achieve this, a hybrid framework using deep learning is proposed on a large-scale dataset and implemented transfer learning for a small-scale dataset. Deep learning methods can be used to identify fish in underwater images. In this study, we have proposed a new method of hybrid Deep Convolutional Neural Network (CNN) along with a Support Vector Machine (SVM) for classification. Additionally, the Squeeze and Excitation (SE) block has been improved for improved feature extraction. The proposed method achieved an accuracy of 97.90%. Then post-training with the small-scale dataset (Croatian) achieved an accuracy of 94.99% with an 11% improvement compared to Bilinear CNN (B-CNN) (Qui et al., 2018) and can be used in any underwater applications to identify fish species and avoid mislabelling of seafood.","PeriodicalId":52866,"journal":{"name":"Aquatic Sciences and Engineering","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45973077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-18DOI: 10.26650/ase202221136891
M. Demircan, A. Ekici, Gökhan Tunçelli, Merve Tınkır, İ. Keskin, Devrim Memiş
{"title":"Using The Thick-Shelled River Mussel (Unio crassus) Filtering Ability for Water Treatment Process in Aquaculture Systems: an In Vitro Study on Removal of the Bacteria from The Water","authors":"M. Demircan, A. Ekici, Gökhan Tunçelli, Merve Tınkır, İ. Keskin, Devrim Memiş","doi":"10.26650/ase202221136891","DOIUrl":"https://doi.org/10.26650/ase202221136891","url":null,"abstract":"","PeriodicalId":52866,"journal":{"name":"Aquatic Sciences and Engineering","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49072458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Metin Yazıcı, Y. Mazlum, M. Naz, Çiğdem Ürkü Atasanov, M. Türkmen, T. Akaylı
The effects of adding laurel oil to the experimental diet on growth performance, biochemical compositions of fish and feeds, sand liver and intestine histology in Nile tilapia ( Oreochromis niloticus ) juveniles were evaluated. 180 fish (12±0.02 g) were used in the study. They were randomly placed in 12 tanks with a volume of 500 liters, with 15 fish per tank. The commercial laurel oil was added to the diets at 0, 0.3, 0.6, and 1.2%. The fish were fed with experimental diets twice a day as apparent satiation for 60 days. In the current study, weight gain (WG), feed conversion ratio (FCR), specific growth rate (SGR) and survival rates (SR) were statistically similar (p>0.05). While no difference was observed between protein and ash values in the biochemical analysis of fish, lipid values were found to be lower in the 0.3% and 0.6 supplemented groups compared to the control and 1.2% supplemented groups. In addition, there was no statistical difference in protein, lipid, and ash values in the biochemical composition of the feeds. In the study, essential oil components of Laurus nobilis oil such as Linalool, Elemene, Trans-Caryophyllene, Cis- α -Bisabolene, Α -Terpinyl Acetate, Methyleugenol, β -Eudesmol were determined in low levels. The addition of 0.3% laurel oil to the diet did not cause histopathological findings, and it was found to improve liver and intestinal tissues. In conclusion, it is suggested that 0.3% laurel oil addition can be used as a feed additive in tilapia culture, especially considering the data obtained from growth and histological analyzes. Further studies are deserved need to examine the effects of laurel oil on immunity and resistance to various stress factors in other fish.
{"title":"Effects of Adding Laurel (Laurus nobilis) Essential Oil to the Diet of Tilapia Fish on Growth and Intestinal Histology","authors":"Metin Yazıcı, Y. Mazlum, M. Naz, Çiğdem Ürkü Atasanov, M. Türkmen, T. Akaylı","doi":"10.26650/ase20221101489","DOIUrl":"https://doi.org/10.26650/ase20221101489","url":null,"abstract":"The effects of adding laurel oil to the experimental diet on growth performance, biochemical compositions of fish and feeds, sand liver and intestine histology in Nile tilapia ( Oreochromis niloticus ) juveniles were evaluated. 180 fish (12±0.02 g) were used in the study. They were randomly placed in 12 tanks with a volume of 500 liters, with 15 fish per tank. The commercial laurel oil was added to the diets at 0, 0.3, 0.6, and 1.2%. The fish were fed with experimental diets twice a day as apparent satiation for 60 days. In the current study, weight gain (WG), feed conversion ratio (FCR), specific growth rate (SGR) and survival rates (SR) were statistically similar (p>0.05). While no difference was observed between protein and ash values in the biochemical analysis of fish, lipid values were found to be lower in the 0.3% and 0.6 supplemented groups compared to the control and 1.2% supplemented groups. In addition, there was no statistical difference in protein, lipid, and ash values in the biochemical composition of the feeds. In the study, essential oil components of Laurus nobilis oil such as Linalool, Elemene, Trans-Caryophyllene, Cis- α -Bisabolene, Α -Terpinyl Acetate, Methyleugenol, β -Eudesmol were determined in low levels. The addition of 0.3% laurel oil to the diet did not cause histopathological findings, and it was found to improve liver and intestinal tissues. In conclusion, it is suggested that 0.3% laurel oil addition can be used as a feed additive in tilapia culture, especially considering the data obtained from growth and histological analyzes. Further studies are deserved need to examine the effects of laurel oil on immunity and resistance to various stress factors in other fish.","PeriodicalId":52866,"journal":{"name":"Aquatic Sciences and Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41413687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-10DOI: 10.26650/ase202221159748
A. Jana, Godhuli Sit, Purnachandra Das, A. Chanda, S. Sahu
{"title":"Seasonal Length-Weight Relationships and Condition Factors of Mystus tengara (Hamilton, 1822) in Two Habitats","authors":"A. Jana, Godhuli Sit, Purnachandra Das, A. Chanda, S. Sahu","doi":"10.26650/ase202221159748","DOIUrl":"https://doi.org/10.26650/ase202221159748","url":null,"abstract":"","PeriodicalId":52866,"journal":{"name":"Aquatic Sciences and Engineering","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41657799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-04DOI: 10.26650/ase202221149736
Dilek KAHRAMAN YILMAZ, N. Berik
{"title":"Sensory, Chemical and Microbiological Properties of Trout Sausage (Fermented Sucuk)","authors":"Dilek KAHRAMAN YILMAZ, N. Berik","doi":"10.26650/ase202221149736","DOIUrl":"https://doi.org/10.26650/ase202221149736","url":null,"abstract":"","PeriodicalId":52866,"journal":{"name":"Aquatic Sciences and Engineering","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47513378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：