4篇
您的检索式：作者名="LUO Xuecai"
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| 1 | The synthesis of new ultraviolet absorber UV-1200显示文摘 | GAO Shixiang HUANG Yongming LUO Xuecai | 1997 | Chemical Industry Times1997，11，1： | 1 |
| 2 | An amperometric cholesterol biosensor based on multiwalled carbon nanotubes and organically modified sol-gel/chitosan hybrid composite film显示文摘 | Xuecai Tan Minjian Li Peixiang Cai Lijun Luo Xiaoyong Zou | 2004 | Analytical Biochemistry2004，，1： | 1 |
| 3 | Variation characteristics of acid rain in Zhuzhou,Central China over the period 2011-2020显示文摘Zhuzhou was one of the most polluted cities in China with the serious acid rain.Due to the implementation of air pollution control measures from 2016 to 2018,the acid rain pollution in this city has reduced.In order to understand the recent situation,a comprehensive study on the acid rain was carried out from January 2011 to December 2020.The pH values during the study period varied from 3.3 to 7.5,with a volume-weighted mean value of 4.7.The predominant acidic components of the precipitation were SO_(4)^(2-)and NO_(3)^(-),accounting for 89.3% of the total anions.The ratio of non-sea-salt SO_(4)^(2-)to NO_(3)^(-)showed a decreasing trend,revealing that the pollution type of acid rain changed from sulfuric acid type to sulfuric acid and nitric acid compound type.The correlation analysis(p<0.05)showed that SO_(4)^(2-)was positively correlated with NH_(4)^(+),Ca^(2+),and Mg^(2+);hence,it predominated in precipitation as(NH_(4))_(2)SO_(4),NH_(4)HSO_(4),CaSO_(4),and MgSO_(4).Significant positive correlation of Ca^(2+)with Mg^(2+)shows that they may originated mainly from crust.Significant positive correlation between SO_(4)^(2-)and F^(-)and Cl^(-)indicate that their source may be related to the non-ferrous metal smelting industry in Zhuzhou.Further correlation analysis shows that emissions from the non-ferrous metal smelting industry in the area have a large significant on SO_(4)^(2-)and F^(-)in precipitation,while Cl^(-)may still be emitted from other anthropogenic sources. | Jiahao Ren Liquan Zhu Xi Zhang Yuqian Luo Xuecai Zhong Bowen Li Yuwen Wang Kai Zhang | 2024 | Journal of Environmental Sciences2024，，4： | 0 |
| 4 | Genomic prediction of yield performance among single-cross maize hybrids using a partial diallel cross design显示文摘Genomic prediction(GP)in plant breeding has the potential to predict and identify the best-performing hybrids based on the genotypes of their parental lines.In a GP experiment,34 elite inbred lines were selected to make 285 single-cross hybrids in a partial-diallel cross design.These lines represented a mini-core collection of Chinese maize germplasm and comprised 18 inbred lines from the Stiff Stalk heterotic group and 16 inbred lines from the Non-Stiff Stalk heterotic group.The parents were genotyped by sequencing and the 285 hybrids were phenotyped for nine yield and yield-related traits at two locations in the summer sowing area(SUS)and three locations in the spring sowing area(SPS)in the main maizeproducing regions of China.Multiple GP models were employed to assess the accuracy of trait prediction in the hybrids.By ten-fold cross-validation,the prediction accuracies of yield performance of the hybrids estimated by the genomic best linear unbiased prediction(GBLUP)model in SUS and SPS were 0.51 and 0.46,respectively.The prediction accuracies of the remaining yield-related traits estimated with GBLUP ranged from 0.49 to 0.86 and from 0.53 to 0.89 in SUS and SPS,respectively.When additive,dominance,epistasis effects,genotype-by-environment interaction,and multi-trait effects were incorporated into the prediction model,the prediction accuracy of hybrid yield performance was improved.The ratio of training to testing population and size of training population optimal for yield prediction were determined.Multiple prediction models can improve prediction accuracy in hybrid breeding. | Ping Luo Houwen Wang Zhiyong Ni Ruisi Yang Fei Wang Hongjun Yong Lin Zhang Zhiqiang Zhou Wei Song Mingshun Li Jie Yang Jianfeng Weng Zhaodong Meng Degui Zhang Jienan Han Yong Chen Runze Zhang Liwei Wang Meng Zhao Wenwei Gao Xiaoyu Chen Wenjie Li Zhuanfang Hao Junjie Fu Xuecai Zhang Xinhai Li | 2023 | The Crop Journal2023，11，6： | 0 |
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