对广东珠海一养殖池塘中尖吻鲈Lates calcarifer的发病情况进行了调查。调查发现,病鱼体色发黑,剖检可见鳃充血发紫;空肠空胃,肠道微红,脾和肾肿大,有出血点,胆囊充盈,有胆汁渗出,肾发黑,有出血点,其他组织器官无明显变化。从病鱼的鳃...对广东珠海一养殖池塘中尖吻鲈Lates calcarifer的发病情况进行了调查。调查发现,病鱼体色发黑,剖检可见鳃充血发紫;空肠空胃,肠道微红,脾和肾肿大,有出血点,胆囊充盈,有胆汁渗出,肾发黑,有出血点,其他组织器官无明显变化。从病鱼的鳃、肝、肾、肌肉、肠道,和血液中未检查到寄生虫,从肝、脾和肾中未分离到致病菌。参考世界动物卫生组织(Office International des Epi-zooties,OIE)设计引物,提取自然发病鱼各种组织的DNA作为模板,扩增出了预期大小的特异性产物。测序比对显示,扩增的条带的基因序列与真鲷虹彩病毒(Red sea bream iridovirus,RSIV)的基因序列同源性高达98.6%。病理切片显示:肝和脾出现肿大细胞。因此,引起尖吻鲈发病死亡的原因是肿大细胞病毒属虹彩病毒感染。展开更多
A total of 160 barramundi's (Lates calcarifer Bloch, 1790) sampled from four rivers (Tentulia, Balaswar, Bakkhali, and Andarmanik) along the southern coastal region of Bangladesh were investigated in terms of morp...A total of 160 barramundi's (Lates calcarifer Bloch, 1790) sampled from four rivers (Tentulia, Balaswar, Bakkhali, and Andarmanik) along the southern coastal region of Bangladesh were investigated in terms of morphometric characters to reveal the intraspecific variation. Twenty-five morphometric measurements were extracted using the conventional method and subjected to multivariate analyses (i.e., principal component analysis (PCA), discriminate function analysis (DFA), cluster analysis (CA)) to distinguish individuals from different rivers. The result demonstrated that twenty-two out of 25 measurements was statistically significant (Univariate ANOVA) among all four populations. PCA analysis of morphometric characters resulted in two principal components, PC I and PCⅡ which accounted for 79.25% and 4.28% of the total data variance. PC I-PC Ⅱ plot explained 83.53% of total variance differentiated the population of L. calcarifer into two groups. Discriminate analysis correctly classified about 88.1% of the examined fish into the four areas. The UPGMA dendrogram showed that Bakkhali populations were the most morphologically different populations in comparison to other populations, while Andarmanik and Balaswar populations were very close to each other. The strong morphometric variation between Bakkhali and Tentulia, Andarmanik and Balaswar was observed in the present study, suggested the evidence of the separate stock population of barramundi in these locations, which might require distinct stock management strategies for resource sustainability in the waters of southern Bangladesh. However, if these findings are supported by further molecular markers and geometric morphometry, this would be a strong indication of different stocks of this population in the four rivers of southern Bangladesh.展开更多
Total of 1072 Asian seabass or barramundi (Lates calcarifer) were harvested at two different locations in Queensland, Australia. Each fish was digitally photographed and weighed. A subsample of 200 images (100 from ea...Total of 1072 Asian seabass or barramundi (Lates calcarifer) were harvested at two different locations in Queensland, Australia. Each fish was digitally photographed and weighed. A subsample of 200 images (100 from each location) were manually segmented to extract the fish-body area (S in cm2), excluding all fins. After scaling the segmented images to 1mm per pixel, the fish mass values (M in grams) were fitted by a single-factor model (M=aS1.5, a=0.1695 )achieving the coefficient of determination (R2) and the Mean Absolute Relative Error (MARE) of R2=0.9819 and MARE=5.1%, respectively. A segmentation Convolutional Neural Network (CNN) was trained on the 200 hand-segmented images, and then applied to the rest of the available images. The CNN predicted fish-body areas were used to fit the mass-area estimation models: the single-factor model, M=aS1.5, a=0.170, R2=0.9819, MARE=5.1%;and the two-factor model, M= aSb, a=0.124, b=0.155, R2=0.9834, MARE=4.5%.展开更多
文摘对广东珠海一养殖池塘中尖吻鲈Lates calcarifer的发病情况进行了调查。调查发现,病鱼体色发黑,剖检可见鳃充血发紫;空肠空胃,肠道微红,脾和肾肿大,有出血点,胆囊充盈,有胆汁渗出,肾发黑,有出血点,其他组织器官无明显变化。从病鱼的鳃、肝、肾、肌肉、肠道,和血液中未检查到寄生虫,从肝、脾和肾中未分离到致病菌。参考世界动物卫生组织(Office International des Epi-zooties,OIE)设计引物,提取自然发病鱼各种组织的DNA作为模板,扩增出了预期大小的特异性产物。测序比对显示,扩增的条带的基因序列与真鲷虹彩病毒(Red sea bream iridovirus,RSIV)的基因序列同源性高达98.6%。病理切片显示:肝和脾出现肿大细胞。因此,引起尖吻鲈发病死亡的原因是肿大细胞病毒属虹彩病毒感染。
文摘A total of 160 barramundi's (Lates calcarifer Bloch, 1790) sampled from four rivers (Tentulia, Balaswar, Bakkhali, and Andarmanik) along the southern coastal region of Bangladesh were investigated in terms of morphometric characters to reveal the intraspecific variation. Twenty-five morphometric measurements were extracted using the conventional method and subjected to multivariate analyses (i.e., principal component analysis (PCA), discriminate function analysis (DFA), cluster analysis (CA)) to distinguish individuals from different rivers. The result demonstrated that twenty-two out of 25 measurements was statistically significant (Univariate ANOVA) among all four populations. PCA analysis of morphometric characters resulted in two principal components, PC I and PCⅡ which accounted for 79.25% and 4.28% of the total data variance. PC I-PC Ⅱ plot explained 83.53% of total variance differentiated the population of L. calcarifer into two groups. Discriminate analysis correctly classified about 88.1% of the examined fish into the four areas. The UPGMA dendrogram showed that Bakkhali populations were the most morphologically different populations in comparison to other populations, while Andarmanik and Balaswar populations were very close to each other. The strong morphometric variation between Bakkhali and Tentulia, Andarmanik and Balaswar was observed in the present study, suggested the evidence of the separate stock population of barramundi in these locations, which might require distinct stock management strategies for resource sustainability in the waters of southern Bangladesh. However, if these findings are supported by further molecular markers and geometric morphometry, this would be a strong indication of different stocks of this population in the four rivers of southern Bangladesh.
文摘Total of 1072 Asian seabass or barramundi (Lates calcarifer) were harvested at two different locations in Queensland, Australia. Each fish was digitally photographed and weighed. A subsample of 200 images (100 from each location) were manually segmented to extract the fish-body area (S in cm2), excluding all fins. After scaling the segmented images to 1mm per pixel, the fish mass values (M in grams) were fitted by a single-factor model (M=aS1.5, a=0.1695 )achieving the coefficient of determination (R2) and the Mean Absolute Relative Error (MARE) of R2=0.9819 and MARE=5.1%, respectively. A segmentation Convolutional Neural Network (CNN) was trained on the 200 hand-segmented images, and then applied to the rest of the available images. The CNN predicted fish-body areas were used to fit the mass-area estimation models: the single-factor model, M=aS1.5, a=0.170, R2=0.9819, MARE=5.1%;and the two-factor model, M= aSb, a=0.124, b=0.155, R2=0.9834, MARE=4.5%.
