Dalian Fisheries Research Institute

Dalian, China

Dalian Fisheries Research Institute

Dalian, China

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Tian J.-S.,Liaoning Ocean and Fisheries Science Research Institute | Tian J.-S.,CAS Qingdao Institute of Oceanology | Lu Z.-C.,Liaoning Ocean and Fisheries Science Research Institute | Lu Z.-C.,CAS Qingdao Institute of Oceanology | And 6 more authors.
Chinese Journal of Ecology | Year: 2015

This study measured δ13C and δ15N in muscle, liver, kidney, lung, hair, whisker and nail from juvenile and adult captive spotted seals Phoca largha after feeding Clupea harengus and Mallotus villosus for more than 6 months to produce the fractionation in each tissue. Meanwhile, this study estimated the food sources for the wild spotted seals from Liaodong Bay, in terms of δ13C and δ15N fractionations in muscle, liver and kidney of wild spotted seals and its potential foods in Liaodong Bay. The results showed that the highest δ13C value in captive spotted seals was in whisker (3.5‰), followed by hair (3.2‰), nail (3.0‰), muscle (1.3‰), lung (1.0‰), liver (0.5‰) and kidney (0.3‰). The highest δ15N value in captive spotted seals was in kidney (2.8‰), followed by liver (2.7‰), muscle (2.6‰), nail (2.6‰), whisker (2.6‰), lung (2.4‰) and hair (1.8‰). The δ13C values in captive pup were -22.4‰, -23.0‰ and -22.1‰ in muscle, kidney and liver, respectively. The δ13C value in milk was -24.8‰. The δ13C values in wild adult spotted seals from Liaodong Bay were -18.6‰, -19.1‰ and -18.7‰ in muscle, kidney and liver, respectively. According to the fractionation (1.3‰) of δ13C in captive spotted seal muscle, the estimated food sources for wild spotted seals from Liaodong Bay were mainly from fishes (especially pelagic and meso-demersal fishes), and some cephalopoda and shrimps as well. © 2015, Editorial Board of Chinese Journal of Ecology. All rights reserved.


Song X.,Ocean University of China | Pan Y.,Ocean University of China | Ma Z.,Dalian Fisheries Research Institute | Dong D.,Ocean University of China | Huang Z.,Ocean University of China
Chinese Journal of Environmental Engineering | Year: 2015

The wastewater purification abilities of Bacillus subtilis, yeast, lactobacillus and mixed strains were evaluated in order to optimize the biofilm technology in wastewater treatment systems. The experiments were carried out for 35 days. Eight treatments were set up and sterile saline was set as control. Results show that the concentrations of ammonia nitrogen (NH4+-N) and nitrite nitrogen (NO2--N) were significantly lower in treatments than control, respectively (P<0.05). The removal rates of NH4+-N and NO2--N were both more than 90% in mixed strains treatment systems, which were significantly higher than other treatments (P<0.05). Significantly lower phosphate were observed in treatments inoculated with Bacillus subtilis (0.2 mg/L) than treatments without Bacillus subtilis (0.59 mg/L) (P<0.05). The concentrations of chemical oxygen demand (CODMn) were significantly lower in treatments compared the control (P<0.05), but there were no significant differences among the treatments (P>0.05). The mixed strains treatment systems had the highest removal rate of CODMn (76.9%). In conclusion, the most efficient purification ability are attained in the treatment with mixture of three kinds of strains and mixed strains treatment systems are superior to single bacteria treatment systems. ©, 2015, Science Press. All right reserved.


Ma Z.,Dalian Fisheries Research Institute | Ma Z.,Ocean University of China | Song X.,Ocean University of China | Wan R.,Ocean University of China | And 2 more authors.
Aquaculture | Year: 2014

We used a backpropagation neural network (BP-NN) model to predict the water quality in intensive (300PLs/m2) Litopenaeus vannamei shrimp tanks. The model has a tan-sigmoid transfer function for the hidden layer and a linear transfer function for the output layer. It was developed using measured water quality data that were generated over 120days (from 1 July to 28 October 2008) with weekly monitoring in four different shrimp tanks. Nine parameters were selected as input variables: water temperature, pH, total ammonia nitrogen, nitrite nitrogen, nitrate nitrogen, dissolved inorganic phosphorus, chlorophyll-a, chemical oxygen demand, and five-day biochemical oxygen demand. The Levenberg-Marquardt algorithm was used to overcome the shortcomings of the traditional BP algorithm; that is, low computational power and getting stuck in local minima. The number of hidden layer nodes was optimized by a trial and error approach, and five optimal neuron nodes were identified. The computed results for water quality show good agreement with the experimental values. The correlation coefficients of the training, testing, and training+testing sets between computed results and experimental values are 0.990, 0.979, and 0.992 respectively. The simulation results reveal that the BP-NN model efficiently predicts the water quality in intensive shrimp tanks. © 2014.

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