Sulfide-containing waste streams are generated by a number of industries. It is emitted into the environment as dis- solved sulfide (S2- and HS-) in wastewaters and as H2S in waste gases. Due to its corrosive nature, ...Sulfide-containing waste streams are generated by a number of industries. It is emitted into the environment as dis- solved sulfide (S2- and HS-) in wastewaters and as H2S in waste gases. Due to its corrosive nature, biological hydrogen sulfide removal processes are being investigated to overcome the chemical and disposal costs associated with existing chemically based removal processes. The nitrogen and sulfur metabolism interacts at various levels of the wastewater treatment process. Hence, the sulfur cycle offers possibilities to integrate nitrogen removal in the treatment process, which needs to be further optimized by appropriate design of the reactor configuration, optimization of performance parameters, retention of biomass and optimization of biomass growth. The present paper reviews the biotechnological advances to remove sulfides from various environments.展开更多
Water hyacinth (Eichhornia crassipes (Mart.) Solms) is a prolific free floating aquatic macrohpyte found in tropical and subtropical parts of the earth. The effects of pollutants from textile wastewater on the anatomy...Water hyacinth (Eichhornia crassipes (Mart.) Solms) is a prolific free floating aquatic macrohpyte found in tropical and subtropical parts of the earth. The effects of pollutants from textile wastewater on the anatomy of the plant were studied. Water hyacinth exhibits hydrophytic adaptations which include reduced epidermis cells lacking cuticle in most cases, presence of large air spaces (7～50 μm), reduced vascular tissue and absorbing structures. Textile waste significantly affected the size of root cells.The presence of raphide crystals was noted in parenchyma cells of various organs in treated plants.展开更多
Objective During present investigation the data of a laboratory-scale anoxic sulfide oxidizing （ASO） reactor were used in a neural network system to predict its performance. Methods Five uncorrelated components of t...Objective During present investigation the data of a laboratory-scale anoxic sulfide oxidizing （ASO） reactor were used in a neural network system to predict its performance. Methods Five uncorrelated components of the influent wastewater were used as the artificial neural network model input to predict the output of the effluent using back-propagation and general regression algorithms. The best prediction performance is achieved when the data are preprocessed using principal components analysis （PCA） before they are fed to a back propagated neural network. Results Within the range of experimental conditions tested, it was concluded that the ANN model gave predictable results for nitrite removal from wastewater through ASO process. The model did not predict the formation of sulfate to an acceptable manner. Conclusion Apart from experimentation, ANN model can help to simulate the results of such experiments in finding the best optimal choice for ASO based denitrification. Together with wastewater collection and the use of improved treatment systems and new technologies, better control of wastewater treatment plant （WTP） can lead to more effective maneuvers by its operators and, as a consequence, better effluent quality.展开更多
Brix weight per stool (BW) of sugarcane is a complex trait, which is the final product of a combination of many components. Diallel cross experiments were conducted during a period of two years for BW and its five com...Brix weight per stool (BW) of sugarcane is a complex trait, which is the final product of a combination of many components. Diallel cross experiments were conducted during a period of two years for BW and its five component traits, in- cluding stalk diameter (SD), stalk length (SL), stalk number (SN), stalk weight (SW), and brix scale (BS) of sugarcane. Phenotypic data of all the six traits were analyzed by mixed linear model and their phenotype variances were portioned into additive (A), dominance (D), additive×environment interaction (AE) and dominance×environment interaction (DE) effects, and the correlations of A, D, AE and DE effects between BW and its components were estimated. Conditional analysis was employed to investigate the contribution of the components traits to the variances of A, D, AE and DE effects of BW. It was observed that the heritabilities of BW were significantly attributed to A, D and DE by 23.9%, 30.9% and 28.5%, respectively. The variance of A effect for BW was significantly affected by SL, SN and BS by 25.3%, 93.7% and 17.4%, respectively. The variances of D and DE effects for BW were also significantly influenced by all the five components by 5.1%～85.5%. These determinants might be helpful in sugarcane breeding and provide valuable information for multiple-trait improvement of BW.展开更多
基金Project supported by the National Natural Science Foundation ofChina (No. 30070017)the Science and Technology Foundationfor Key Project of Zhejiang Province (No. 2003C13005), China
文摘Sulfide-containing waste streams are generated by a number of industries. It is emitted into the environment as dis- solved sulfide (S2- and HS-) in wastewaters and as H2S in waste gases. Due to its corrosive nature, biological hydrogen sulfide removal processes are being investigated to overcome the chemical and disposal costs associated with existing chemically based removal processes. The nitrogen and sulfur metabolism interacts at various levels of the wastewater treatment process. Hence, the sulfur cycle offers possibilities to integrate nitrogen removal in the treatment process, which needs to be further optimized by appropriate design of the reactor configuration, optimization of performance parameters, retention of biomass and optimization of biomass growth. The present paper reviews the biotechnological advances to remove sulfides from various environments.
基金Project (No. 30070017) supported by the National Natural Science Foundation of China
文摘Water hyacinth (Eichhornia crassipes (Mart.) Solms) is a prolific free floating aquatic macrohpyte found in tropical and subtropical parts of the earth. The effects of pollutants from textile wastewater on the anatomy of the plant were studied. Water hyacinth exhibits hydrophytic adaptations which include reduced epidermis cells lacking cuticle in most cases, presence of large air spaces (7～50 μm), reduced vascular tissue and absorbing structures. Textile waste significantly affected the size of root cells.The presence of raphide crystals was noted in parenchyma cells of various organs in treated plants.
文摘Objective During present investigation the data of a laboratory-scale anoxic sulfide oxidizing （ASO） reactor were used in a neural network system to predict its performance. Methods Five uncorrelated components of the influent wastewater were used as the artificial neural network model input to predict the output of the effluent using back-propagation and general regression algorithms. The best prediction performance is achieved when the data are preprocessed using principal components analysis （PCA） before they are fed to a back propagated neural network. Results Within the range of experimental conditions tested, it was concluded that the ANN model gave predictable results for nitrite removal from wastewater through ASO process. The model did not predict the formation of sulfate to an acceptable manner. Conclusion Apart from experimentation, ANN model can help to simulate the results of such experiments in finding the best optimal choice for ASO based denitrification. Together with wastewater collection and the use of improved treatment systems and new technologies, better control of wastewater treatment plant （WTP） can lead to more effective maneuvers by its operators and, as a consequence, better effluent quality.
基金Project supported partly by the National Science and TechnologySupport Program (No. 2006BAD10A09-08), Chinathe Great Science Research Program of Guangdong Province (No. A20602),China
文摘Brix weight per stool (BW) of sugarcane is a complex trait, which is the final product of a combination of many components. Diallel cross experiments were conducted during a period of two years for BW and its five component traits, in- cluding stalk diameter (SD), stalk length (SL), stalk number (SN), stalk weight (SW), and brix scale (BS) of sugarcane. Phenotypic data of all the six traits were analyzed by mixed linear model and their phenotype variances were portioned into additive (A), dominance (D), additive×environment interaction (AE) and dominance×environment interaction (DE) effects, and the correlations of A, D, AE and DE effects between BW and its components were estimated. Conditional analysis was employed to investigate the contribution of the components traits to the variances of A, D, AE and DE effects of BW. It was observed that the heritabilities of BW were significantly attributed to A, D and DE by 23.9%, 30.9% and 28.5%, respectively. The variance of A effect for BW was significantly affected by SL, SN and BS by 25.3%, 93.7% and 17.4%, respectively. The variances of D and DE effects for BW were also significantly influenced by all the five components by 5.1%～85.5%. These determinants might be helpful in sugarcane breeding and provide valuable information for multiple-trait improvement of BW.
