To break the narrow diversity bottleneck of the wheat D genome, a set of Aegilops tauschii-wheat introgression(A-WI) lines was developed by crossing Ae. tauschii accession T015 with common wheat elite cultivar Zhoumai...To break the narrow diversity bottleneck of the wheat D genome, a set of Aegilops tauschii-wheat introgression(A-WI) lines was developed by crossing Ae. tauschii accession T015 with common wheat elite cultivar Zhoumai 18(Zhou18). A high-density genetic map was constructed based on Single Nucleotide Polymorphism(SNP) markers and 15 yield-related traits were evaluated in 11 environments for detecting quantitative trait loci(QTL). A total of 27 environmentally stable QTL were identified in at least five environments, 20 of which were derived from Ae. tauschii T015, explaining up to 24.27% of the phenotypic variations. The major QTL for kernel length(KL), QKl-2D.5, was delimited to a physical interval of approximately 2.6 Mb harboring 52 candidate genes. Three Kompetitive Allele Specific PCR(KASP)markers were successfully developed based on nonsynonymous nucleotide mutations of candidate gene AetT093_2Dv1G100900.1 and showed that A-WI lines with the T015 haplotype had significantly longer KL than the Zhou18 haplotype across all 11 environments. Four primary valuable A-WIs with good trait performance and carrying yield-related QTL were selected for breeding improvement. The results will facilitate the efficient transfer of beneficial genes from Ae. tauschii into wheat cultivars to improve wheat yield and other traits.展开更多
Industrial emissions are the main source of atmospheric pollutants in China.Accurate and reasonable prediction of the emission of atmospheric pollutants from single enterprise can determine the exact source of atmosph...Industrial emissions are the main source of atmospheric pollutants in China.Accurate and reasonable prediction of the emission of atmospheric pollutants from single enterprise can determine the exact source of atmospheric pollutants and control atmospheric pollution precisely.Based on China’s coking enterprises in 2020,we proposed a quantitative method for pollutant emission standards and introduced the quantification results of pollutant emission standards(QRPES)into the construction of support vector regression(SVR)and random forest regression(RFR)prediction methods for SO_(2) emission of coking enterprises in China.The results show that,affected by the types of coke ovens and regions,China’s current coking enterprises have implemented a total of 21 emission standards,with marked differences.After adding QRPES,it was found that the root mean squared error(RMSE)of SVR and RFR decreased from 0.055 kt/a and 0.059 kt/a to 0.045 kt/a and 0.039 kt/a,and the R2 increased from 0.890 and 0.881 to 0.926 and 0.945,respectively.This shows that the QRPES can greatly improve the prediction accuracy,and the SO_(2) emissions of each enterprise are highly correlated with the strictness of standards.The predicted result shows that 45%of SO_(2) emissions from Chinese coking enterprises are concentrated in Shanxi,Shaanxi and Hebei provinces in central China.The method created in this paper fills in the blank of forecasting method of air pollutant emission intensity of single enterprise and is of great help to the accurate control of air pollutants.展开更多
To identify the concentrations and sources of heavy metals, and to assess soil environmental quality, 63 soil samples were collected in Yibin City, Sichuan Province, China. Mean concentrations of As, Pb, Zn, and Cu we...To identify the concentrations and sources of heavy metals, and to assess soil environmental quality, 63 soil samples were collected in Yibin City, Sichuan Province, China. Mean concentrations of As, Pb, Zn, and Cu were 10.55, 61.23, 138.88 and 56.35 mg/kg, respectively. As concentrations were comparable to background values, while Pb, Zn, and Cu concentrations were higher than their corresponding background values. Industrial areas exhibited the highest concentrations of As, Pb, Zn, and Cu, while the lowest concentrations occurred in parks. Statistical analysis was performed and two cluster groups of metals were identified with Pb, Zn, and Cu in one group and As in the other. Spatial distribution maps indicated that Pb, Zn, and Cu were mainly controlled by anthropogenic activities, whereas As could be mainly accounted for by soil parent materials. Pollution index values of As, Pb, Zn, and Cu varied in the range of 0.24-1.93, 0.66-7.24, 0.42-4.19, and 0.62-5.25, with mean values of 0.86, 1.98, 1.61, and 1.78, respectively. The integrated pollution index (IPI) values of these metals varied from 0.82 to 3.54, with a mean of 1.6 and more than 90% of soil samples were moderately or highly contaminated with heavy metals. The spatial distribution of IPI showed that newer urban areas displayed relatively lower heavy metal contamination in comparison with older urban areas.展开更多
Lateral transportation of soil heavy metals in rainfall events could significantly increase the scope of pollution. Therefore, it is necessary to develop a model with high accuracy to simulate the migration quantity o...Lateral transportation of soil heavy metals in rainfall events could significantly increase the scope of pollution. Therefore, it is necessary to develop a model with high accuracy to simulate the migration quantity of heavy metals. A model for heavy metal migration simulation was developed based on the SWAT(Soil and Water Assessment Tool) model. This model took into consideration the influence of soil p H value, soil particle size, runoff volume, sediment amount,concentration of water-soluble heavy metals dissolved in runoff and insoluble absorbed to the soil particles. This model was reasonable in Huanjiang watershed, Guangxi Zhuang Autonomous Region, south China, covering an area of 273 km^2. The optimal drainage area threshold was determined by analyzing the effects of watershed subdivision on the simulation results to ensure the simulation accuracy. The main conclusions of this paper were:(1) watershed subdivision could affect simulation migration quantity of heavy metals;(2) the quantity of heavy metals transported by sediment accounted for 97%–99% of the total migration quantity in the study watershed. Therefore, sediment played the most important role in heavy metal migration;(3) the optimal drainage area threshold percentage to ensure high simulation accuracy was determined to be 2.01% of the total watershed;(4) with the optimal threshold percentage, this model could simulate the migration quantity of As, Pb and Cd accurately at the total watershed and subwatershed level. The results of this paper were useful for identifying the key regions with heavy metal migration.展开更多
It is essential to determine the heavy metal concentrations in sewage sludge to select appropriate disposal methods. We conducted a national survey of heavy metal concentrations of sewage sludge samples from 107 munic...It is essential to determine the heavy metal concentrations in sewage sludge to select appropriate disposal methods. We conducted a national survey of heavy metal concentrations of sewage sludge samples from 107 municipal sewage treatment plants located in 48 cities covering the 31 provinces and autonomous regions, as well as Hong Kong, Macao and Taiwan by Xinjiang Production and Construction Corps in 2006, and identified the temporal trends of heavy metal contents in sewage sludge by comparison with surveys conducted in 1994-2001. In 2006, the average concentrations of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn in sewage sludge were 20.2, 1.97, 93.1, 218.8, 2.13, 48.7, 72.3, and 1058mg.kg-1, respectively. Because of the decreased discharge of heavy metals into industrial wastewater in China and the increasingly stringent regulations governing the content of industrial wastes entering sewers, the average concentrations of Cd, Cr, Cu, Hg, Ni, Pb, and Zn have decreased by 32.3%, 49.7%, 54.9%, 25.0%, 37.2%, 44.8%, and 27.0%, respectively, during the past 12 years. The concentrations of Cd, Cr, Cu, Ni, and Zn in the samples exceeded the heavy metal limits of the Discharge Standard of Pollutants for Municipal Wastewater Treatment Plant in China (GB 18918-2002) by 6.5%, 3.7%, 6.5%, 6.5%, and 11.2%, respectively. From these results, 85 of the 107 municipal sludges analyzed would be considered suitable for land application.展开更多
Aegilops tauschii,the wild progenitor of wheat D-genome and a valuable germplasm for wheat improvement,has a wide natural distribution from eastern Turkey to China.However,the phylogenetic relationship and dispersion ...Aegilops tauschii,the wild progenitor of wheat D-genome and a valuable germplasm for wheat improvement,has a wide natural distribution from eastern Turkey to China.However,the phylogenetic relationship and dispersion history of Ae.tauschii in China has not been scientifically clarified.In this study,we genotyped 208 accessions(with 104 in China)using dd RAD sequencing and 55K SNP array,and classified the population into six sublineages.Three possible spreading routes or events were identified,resulting in specific distribution patterns,with four sublineages found in Xinjiang,one in Qinghai,two in Shaanxi and one in Henan.We also established the correlation of SNP-based,karyotypebased and spike-morphology-based techniques to demonstrate the internal classification of Ae.tauschii,and developed consensus dataset with 1245 putative accessions by merging data previously published.Our analysis suggested that eight inter-lineage accessions could be assigned to the putative Lineage 3and these accessions would help to conserve the genetic diversity of the species.By developing the consensus phylogenetic relationships of Ae.tauschii,our work validated the hypothesis on the dispersal history of Ae.tauschii in China,and contributed to the efficient and comprehensive germplasm-mining of the species.展开更多
基金financially supported by the National Natural Science Foundation of China (32230079, 32001492, 31871615, and31901547)Natural Science Foundation of Henan Province(222301420102)。
文摘To break the narrow diversity bottleneck of the wheat D genome, a set of Aegilops tauschii-wheat introgression(A-WI) lines was developed by crossing Ae. tauschii accession T015 with common wheat elite cultivar Zhoumai 18(Zhou18). A high-density genetic map was constructed based on Single Nucleotide Polymorphism(SNP) markers and 15 yield-related traits were evaluated in 11 environments for detecting quantitative trait loci(QTL). A total of 27 environmentally stable QTL were identified in at least five environments, 20 of which were derived from Ae. tauschii T015, explaining up to 24.27% of the phenotypic variations. The major QTL for kernel length(KL), QKl-2D.5, was delimited to a physical interval of approximately 2.6 Mb harboring 52 candidate genes. Three Kompetitive Allele Specific PCR(KASP)markers were successfully developed based on nonsynonymous nucleotide mutations of candidate gene AetT093_2Dv1G100900.1 and showed that A-WI lines with the T015 haplotype had significantly longer KL than the Zhou18 haplotype across all 11 environments. Four primary valuable A-WIs with good trait performance and carrying yield-related QTL were selected for breeding improvement. The results will facilitate the efficient transfer of beneficial genes from Ae. tauschii into wheat cultivars to improve wheat yield and other traits.
基金supported by the National Key R&D Program of China(No.2018YFC1800106)。
文摘Industrial emissions are the main source of atmospheric pollutants in China.Accurate and reasonable prediction of the emission of atmospheric pollutants from single enterprise can determine the exact source of atmospheric pollutants and control atmospheric pollution precisely.Based on China’s coking enterprises in 2020,we proposed a quantitative method for pollutant emission standards and introduced the quantification results of pollutant emission standards(QRPES)into the construction of support vector regression(SVR)and random forest regression(RFR)prediction methods for SO_(2) emission of coking enterprises in China.The results show that,affected by the types of coke ovens and regions,China’s current coking enterprises have implemented a total of 21 emission standards,with marked differences.After adding QRPES,it was found that the root mean squared error(RMSE)of SVR and RFR decreased from 0.055 kt/a and 0.059 kt/a to 0.045 kt/a and 0.039 kt/a,and the R2 increased from 0.890 and 0.881 to 0.926 and 0.945,respectively.This shows that the QRPES can greatly improve the prediction accuracy,and the SO_(2) emissions of each enterprise are highly correlated with the strictness of standards.The predicted result shows that 45%of SO_(2) emissions from Chinese coking enterprises are concentrated in Shanxi,Shaanxi and Hebei provinces in central China.The method created in this paper fills in the blank of forecasting method of air pollutant emission intensity of single enterprise and is of great help to the accurate control of air pollutants.
基金supported by the National Basic Research Program (973) of China (No. 2008CB418200)the National Natural Science Foundation of China (No.40973087, U0833603)
文摘To identify the concentrations and sources of heavy metals, and to assess soil environmental quality, 63 soil samples were collected in Yibin City, Sichuan Province, China. Mean concentrations of As, Pb, Zn, and Cu were 10.55, 61.23, 138.88 and 56.35 mg/kg, respectively. As concentrations were comparable to background values, while Pb, Zn, and Cu concentrations were higher than their corresponding background values. Industrial areas exhibited the highest concentrations of As, Pb, Zn, and Cu, while the lowest concentrations occurred in parks. Statistical analysis was performed and two cluster groups of metals were identified with Pb, Zn, and Cu in one group and As in the other. Spatial distribution maps indicated that Pb, Zn, and Cu were mainly controlled by anthropogenic activities, whereas As could be mainly accounted for by soil parent materials. Pollution index values of As, Pb, Zn, and Cu varied in the range of 0.24-1.93, 0.66-7.24, 0.42-4.19, and 0.62-5.25, with mean values of 0.86, 1.98, 1.61, and 1.78, respectively. The integrated pollution index (IPI) values of these metals varied from 0.82 to 3.54, with a mean of 1.6 and more than 90% of soil samples were moderately or highly contaminated with heavy metals. The spatial distribution of IPI showed that newer urban areas displayed relatively lower heavy metal contamination in comparison with older urban areas.
基金supported by the Hi-Tech Research and Development Program(863)of China(No.2014AA06A513)the Beijing Postdoctoral Research Foundation+2 种基金the Project of Heavy Metal Risk Warning and Phytoremediation in Mining Concentrated Area(No.GJHZ201308)the Special Fund for Environment Protection Research in the Public Interest(No.201409044)the Study on Heavy Metal Accumulation Risk and Early Warning in Typical Ore Concentration Area(No.201111020-4)
文摘Lateral transportation of soil heavy metals in rainfall events could significantly increase the scope of pollution. Therefore, it is necessary to develop a model with high accuracy to simulate the migration quantity of heavy metals. A model for heavy metal migration simulation was developed based on the SWAT(Soil and Water Assessment Tool) model. This model took into consideration the influence of soil p H value, soil particle size, runoff volume, sediment amount,concentration of water-soluble heavy metals dissolved in runoff and insoluble absorbed to the soil particles. This model was reasonable in Huanjiang watershed, Guangxi Zhuang Autonomous Region, south China, covering an area of 273 km^2. The optimal drainage area threshold was determined by analyzing the effects of watershed subdivision on the simulation results to ensure the simulation accuracy. The main conclusions of this paper were:(1) watershed subdivision could affect simulation migration quantity of heavy metals;(2) the quantity of heavy metals transported by sediment accounted for 97%–99% of the total migration quantity in the study watershed. Therefore, sediment played the most important role in heavy metal migration;(3) the optimal drainage area threshold percentage to ensure high simulation accuracy was determined to be 2.01% of the total watershed;(4) with the optimal threshold percentage, this model could simulate the migration quantity of As, Pb and Cd accurately at the total watershed and subwatershed level. The results of this paper were useful for identifying the key regions with heavy metal migration.
基金Acknowledgements The authors thank Professor Qi-Tang Wu of South China Agricultural University and Professor Pin-Jin He of Tongji University for their assistance in sampling sewage sludge. This research was sponsored by the National Natural Science Foundation of China (Grant No. 41271478), and the National High Technology Research and Development Program of China (863 Program) (Grant No. 2012AA06A202).
文摘It is essential to determine the heavy metal concentrations in sewage sludge to select appropriate disposal methods. We conducted a national survey of heavy metal concentrations of sewage sludge samples from 107 municipal sewage treatment plants located in 48 cities covering the 31 provinces and autonomous regions, as well as Hong Kong, Macao and Taiwan by Xinjiang Production and Construction Corps in 2006, and identified the temporal trends of heavy metal contents in sewage sludge by comparison with surveys conducted in 1994-2001. In 2006, the average concentrations of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn in sewage sludge were 20.2, 1.97, 93.1, 218.8, 2.13, 48.7, 72.3, and 1058mg.kg-1, respectively. Because of the decreased discharge of heavy metals into industrial wastewater in China and the increasingly stringent regulations governing the content of industrial wastes entering sewers, the average concentrations of Cd, Cr, Cu, Hg, Ni, Pb, and Zn have decreased by 32.3%, 49.7%, 54.9%, 25.0%, 37.2%, 44.8%, and 27.0%, respectively, during the past 12 years. The concentrations of Cd, Cr, Cu, Ni, and Zn in the samples exceeded the heavy metal limits of the Discharge Standard of Pollutants for Municipal Wastewater Treatment Plant in China (GB 18918-2002) by 6.5%, 3.7%, 6.5%, 6.5%, and 11.2%, respectively. From these results, 85 of the 107 municipal sludges analyzed would be considered suitable for land application.
基金supported by the National Natural Science Foundation of China(32001492)the Ministry of Agriculture of China(2016ZX08009)the Natural Science Foundation of Henan(202300410053)。
文摘Aegilops tauschii,the wild progenitor of wheat D-genome and a valuable germplasm for wheat improvement,has a wide natural distribution from eastern Turkey to China.However,the phylogenetic relationship and dispersion history of Ae.tauschii in China has not been scientifically clarified.In this study,we genotyped 208 accessions(with 104 in China)using dd RAD sequencing and 55K SNP array,and classified the population into six sublineages.Three possible spreading routes or events were identified,resulting in specific distribution patterns,with four sublineages found in Xinjiang,one in Qinghai,two in Shaanxi and one in Henan.We also established the correlation of SNP-based,karyotypebased and spike-morphology-based techniques to demonstrate the internal classification of Ae.tauschii,and developed consensus dataset with 1245 putative accessions by merging data previously published.Our analysis suggested that eight inter-lineage accessions could be assigned to the putative Lineage 3and these accessions would help to conserve the genetic diversity of the species.By developing the consensus phylogenetic relationships of Ae.tauschii,our work validated the hypothesis on the dispersal history of Ae.tauschii in China,and contributed to the efficient and comprehensive germplasm-mining of the species.