The maize population Csyn 4 was improved for three cycles with three recurrent selection methods MS1, MS1-HS, and MHSRRS in northern China. A total of 40 NC Ⅱ testcrosses were made by four testers with Csyn 4 and 10 ...The maize population Csyn 4 was improved for three cycles with three recurrent selection methods MS1, MS1-HS, and MHSRRS in northern China. A total of 40 NC Ⅱ testcrosses were made by four testers with Csyn 4 and 10 improved populations, which were evaluated in four environments in the cropping season of 2005. Analysis of variance indicated a significant progress （P〈 0.05） in yield and other chief agronomic traits in the improved populations and testcrosses, demonstrating that the three recurrent selection methods were effective for increasing grain yield of testcrosses and improvement of general combining ability in maize population. The average grain yield increase of population Csyn 4 in MS1, MS1-HS, and MHSRRS recurrent selections was 266.7 kg ha^-1 （5.3%）, 288.0 kg ha^-1 （5.7%）, and 231.3 kg ha^-1 （4.6%） per cycle, while the grain yield of S 1 progeny of population for Csyn 4 was increased by 420.0 kg ha^-1 （10.9%）, 376.0 kg ha^-1 （9.8%）, and 414.7 kg ha^-1 （10.8%） per cycle in MS1, MS1-HS, and MHSRRS recurrent selections, respectively. Linear responses （b） in the MS1, MS1-HS, and MHSRRS recurrent selections were the same as the realized responses of the selection （G） for grain yield increase of Csyn 4 and S1 progeny of the populations. The grain yield of testcrosses increased by 3.3-5.2% on average per cycle. The value of heterosis did not display any differences amongst the different cycles of selections. The GCA for yield component traits of population Csyn 4 was improved significantly by means of three selection methods, whereas the GCA for plant height, ear height, days to silking, and days to pollen did not show significant increase in the recurrent selections. GCA for the number of tassel branches were decreased in the selections, while GCA for the number of plant leaves were increased, but the difference was not significant.展开更多
This paper deals with dynamic airspace sectorization （DAS） problem by an improved genetic algorithm （iGA）. A graph model is first constructed that represents the airspace static structure. Then the DAS problem is ...This paper deals with dynamic airspace sectorization （DAS） problem by an improved genetic algorithm （iGA）. A graph model is first constructed that represents the airspace static structure. Then the DAS problem is formulated as a graph-partitioning problem to balance the sector workload under the premise of ensuring safety. In the iGA, multiple populations and hybrid coding are applied to determine the optimal sector number and airspace sectorization. The sector constraints are well satisfied by the improved genetic operators and protect zones. This method is validated by being applied to the airspace of North China in terms of three indexes, which are sector balancing index, coordination workload index and sector average flight time index. The improvement is obvious, as the sector balancing index is reduced by 16.5 %, the coordination workload index is reduced by 11.2 %, and the sector average flight time index is increased by 11.4 % during the peak-hour traffic.展开更多
文摘The maize population Csyn 4 was improved for three cycles with three recurrent selection methods MS1, MS1-HS, and MHSRRS in northern China. A total of 40 NC Ⅱ testcrosses were made by four testers with Csyn 4 and 10 improved populations, which were evaluated in four environments in the cropping season of 2005. Analysis of variance indicated a significant progress （P〈 0.05） in yield and other chief agronomic traits in the improved populations and testcrosses, demonstrating that the three recurrent selection methods were effective for increasing grain yield of testcrosses and improvement of general combining ability in maize population. The average grain yield increase of population Csyn 4 in MS1, MS1-HS, and MHSRRS recurrent selections was 266.7 kg ha^-1 （5.3%）, 288.0 kg ha^-1 （5.7%）, and 231.3 kg ha^-1 （4.6%） per cycle, while the grain yield of S 1 progeny of population for Csyn 4 was increased by 420.0 kg ha^-1 （10.9%）, 376.0 kg ha^-1 （9.8%）, and 414.7 kg ha^-1 （10.8%） per cycle in MS1, MS1-HS, and MHSRRS recurrent selections, respectively. Linear responses （b） in the MS1, MS1-HS, and MHSRRS recurrent selections were the same as the realized responses of the selection （G） for grain yield increase of Csyn 4 and S1 progeny of the populations. The grain yield of testcrosses increased by 3.3-5.2% on average per cycle. The value of heterosis did not display any differences amongst the different cycles of selections. The GCA for yield component traits of population Csyn 4 was improved significantly by means of three selection methods, whereas the GCA for plant height, ear height, days to silking, and days to pollen did not show significant increase in the recurrent selections. GCA for the number of tassel branches were decreased in the selections, while GCA for the number of plant leaves were increased, but the difference was not significant.
基金funded by the Joint Funds of the National Natural Science Foundation of China (61079001)
文摘This paper deals with dynamic airspace sectorization （DAS） problem by an improved genetic algorithm （iGA）. A graph model is first constructed that represents the airspace static structure. Then the DAS problem is formulated as a graph-partitioning problem to balance the sector workload under the premise of ensuring safety. In the iGA, multiple populations and hybrid coding are applied to determine the optimal sector number and airspace sectorization. The sector constraints are well satisfied by the improved genetic operators and protect zones. This method is validated by being applied to the airspace of North China in terms of three indexes, which are sector balancing index, coordination workload index and sector average flight time index. The improvement is obvious, as the sector balancing index is reduced by 16.5 %, the coordination workload index is reduced by 11.2 %, and the sector average flight time index is increased by 11.4 % during the peak-hour traffic.
