In this work, sugar cane juice was fermented to produce polyhydroxyalkanoates （PHAs） by Alcaligenes latus TISTR 1403 and A. eutrophus TISTR 1095. The juice was characterized and composed of total sugars 105.5 g·...In this work, sugar cane juice was fermented to produce polyhydroxyalkanoates （PHAs） by Alcaligenes latus TISTR 1403 and A. eutrophus TISTR 1095. The juice was characterized and composed of total sugars 105.5 g·L^-1 （sucrose 36.6g·L^-1 , fructose 26.0g·L^-1 , glucose 21.8g·L^-1 and other sugars 21.1g·L^-1 ）. Each inoculums （ 10%, v/v） was separately cultivated in the medium containing 20g·L^-1 total sugars under condition （30℃, 200 rpm, pH 6.5-7）. It was found that the A. eutrophus can be grown better than the A. latus. Only the A. eutrophus was further cultured under different total sugar concentrations （20, 30, 40 and 50g·L^-1 ）. The optimal contents of total sugar, dry cell mass （DCM） and maximum PHAs were obtained at 50g·L^-1 , 6.013g·L^-1 and 1.84g·L^-1 , respectively after 60 h fermentation which were converted to biomass yield （Yx/s）, product yield （Yp/5）, specific product yield （Yp/x） and productivity of 0.163, 0.05, 0.306 and 0.031 g.Llhl. Large scale of PHAs production was conducted in 5 L fermentor using the optimal condition obtained under 30% dissolved oxygen. The DCM and the maximum PHAs were 5.881g·L^-1 and 1.281g·L^-1 which were calculated to values of Yx/s, Yp/s, Yp/x and productivity at 0.19, 0.04, 0.218 and 0.021g·L^-1 , respectively.展开更多
River water plays a key role in human health, and in social and economic development, and is often affected by both natural factors and human activities. An in-depth understanding of the role of these factors can help...River water plays a key role in human health, and in social and economic development, and is often affected by both natural factors and human activities. An in-depth understanding of the role of these factors can help in developing an effective catchment management strategy to protect precious water resources. This study analyzed river water quality, patterns of terrestrial and riparian ecosystems, intensity of agricultural activities, industrial structure, and spatial distribution of pollutant emissions in the Haihe River Basin in China for the year of 2010, identifying the variables that have the greatest impact on river water quality. The area percentage of farmland in study area, the percentage of natural vegetation cover in the 1000-m riparian zone, rural population density, industrial Gross Domestic Product(GDP)/km^2, and industrial amino nitrogen emissions were all significantly correlated with river water quality(P < 0.05). Farming had the largest impact on river water quality, explaining 43.0% of the water quality variance, followed by the coverage of natural vegetation in the 1000-m riparian zone, which explained 36.2% of the water quality variance. Industrial amino nitrogen emissions intensity and rural population density explained 31.6% and 31.4% of the water quality variance, respectively, while industrial GDP/km^2 explained 26.6%. Together, these five indicators explained 67.3% of the total variance in water quality. Consequently, water environmental management of the Haihe River Basin should focus on adjusting agricultural activities, conserving riparian vegetation, and reducing industrial pollutant emissions by optimizing industrial structure. The results demonstrate how human activities drive the spatial pattern changes of river water quality, and they can provide reference for developing land use guidelines and for prioritizing management practices to maintain stream water quality in a large river basin.展开更多
文摘In this work, sugar cane juice was fermented to produce polyhydroxyalkanoates （PHAs） by Alcaligenes latus TISTR 1403 and A. eutrophus TISTR 1095. The juice was characterized and composed of total sugars 105.5 g·L^-1 （sucrose 36.6g·L^-1 , fructose 26.0g·L^-1 , glucose 21.8g·L^-1 and other sugars 21.1g·L^-1 ）. Each inoculums （ 10%, v/v） was separately cultivated in the medium containing 20g·L^-1 total sugars under condition （30℃, 200 rpm, pH 6.5-7）. It was found that the A. eutrophus can be grown better than the A. latus. Only the A. eutrophus was further cultured under different total sugar concentrations （20, 30, 40 and 50g·L^-1 ）. The optimal contents of total sugar, dry cell mass （DCM） and maximum PHAs were obtained at 50g·L^-1 , 6.013g·L^-1 and 1.84g·L^-1 , respectively after 60 h fermentation which were converted to biomass yield （Yx/s）, product yield （Yp/5）, specific product yield （Yp/x） and productivity of 0.163, 0.05, 0.306 and 0.031 g.Llhl. Large scale of PHAs production was conducted in 5 L fermentor using the optimal condition obtained under 30% dissolved oxygen. The DCM and the maximum PHAs were 5.881g·L^-1 and 1.281g·L^-1 which were calculated to values of Yx/s, Yp/s, Yp/x and productivity at 0.19, 0.04, 0.218 and 0.021g·L^-1 , respectively.
基金Under the auspices of National Natural Science Foundation of China(No.41371538)Independent Project of State Key Laboratory of Urban and Regional Ecology,Research Center for Eco-Environmental Sciences,Chinese Academy of Sciences(No.SKLURE2008-1-02)
文摘River water plays a key role in human health, and in social and economic development, and is often affected by both natural factors and human activities. An in-depth understanding of the role of these factors can help in developing an effective catchment management strategy to protect precious water resources. This study analyzed river water quality, patterns of terrestrial and riparian ecosystems, intensity of agricultural activities, industrial structure, and spatial distribution of pollutant emissions in the Haihe River Basin in China for the year of 2010, identifying the variables that have the greatest impact on river water quality. The area percentage of farmland in study area, the percentage of natural vegetation cover in the 1000-m riparian zone, rural population density, industrial Gross Domestic Product(GDP)/km^2, and industrial amino nitrogen emissions were all significantly correlated with river water quality(P < 0.05). Farming had the largest impact on river water quality, explaining 43.0% of the water quality variance, followed by the coverage of natural vegetation in the 1000-m riparian zone, which explained 36.2% of the water quality variance. Industrial amino nitrogen emissions intensity and rural population density explained 31.6% and 31.4% of the water quality variance, respectively, while industrial GDP/km^2 explained 26.6%. Together, these five indicators explained 67.3% of the total variance in water quality. Consequently, water environmental management of the Haihe River Basin should focus on adjusting agricultural activities, conserving riparian vegetation, and reducing industrial pollutant emissions by optimizing industrial structure. The results demonstrate how human activities drive the spatial pattern changes of river water quality, and they can provide reference for developing land use guidelines and for prioritizing management practices to maintain stream water quality in a large river basin.
