| 1 | Evaluation and Bulked Segregant Analysis of Major Yield QTL qtl12.1 Introgressed into Indigenous Elite Line for Low Water Availability under Water Stress显示文摘Near isogenic lines carrying large-effect QTL (qtl12.1), which has a consistent influence on grain yield under upland drought stress conditions in a wide range of environments, were evaluated under water stress in the fields. The line which gave higher yield under drought was crossed with a local elite line, PMK3, and forwarded to F2:3 generation. Significant variation was found among the F2:3 lines for agronomic traits under water stress in the fields. Low to high broad sense heritability (H) for investigated traits was also found. Water stress indicators such as leaf rolling and leaf drying were negatively correlated with plant height, biomass and grain yield under stress. Bulked segregant analysis (BSA) was performed with the markers in the vicinity of qtl12.1, and RM27933 was found to be segregated perfectly well in individual components of drought resistant and drought susceptible bulks which were bulked based on yield under water stress among F2:3 lines. Hence, this simple and breeder friendly marker, RM27933, may be useful as a potentially valuable candidate marker for the transfer of the QTL qtl12.1 in the regional breeding program. Bioinformatic analysis of the DNA sequence of the qtl12.1 region was also done to identify and analyze positional candidate genes associated with this QTL and to ascertain the putative molecular basis of qtl12.1. | N.Manikanda BOOPATHI Gat SWAPNASHRI P.KAVITHA S.SATHISH R.NITHYA Wickneswari RATNAM Arvind KUMAR | 2013 | Rice science2013，20，1： | 1 |
| 2 | Energy-Efficient Clustering Using Optimization with Locust Game Theory显示文摘Wireless sensor networks(WSNs)are made up of several sensors located in a specific area and powered by a finite amount of energy to gather environmental data.WSNs use sensor nodes(SNs)to collect and transmit data.However,the power supplied by the sensor network is restricted.Thus,SNs must store energy as often as to extend the lifespan of the network.In the proposed study,effective clustering and longer network lifetimes are achieved using mul-ti-swarm optimization(MSO)and game theory based on locust search(LS-II).In this research,MSO is used to improve the optimum routing,while the LS-II approach is employed to specify the number of cluster heads(CHs)and select the best ones.After the CHs are identified,the other sensor components are allo-cated to the closest CHs to them.A game theory-based energy-efficient clustering approach is applied to WSNs.Here each SN is considered a player in the game.The SN can implement beneficial methods for itself depending on the length of the idle listening time in the active phase and then determine to choose whether or not to rest.The proposed multi-swarm with energy-efficient game theory on locust search(MSGE-LS)efficiently selects CHs,minimizes energy consumption,and improves the lifetime of networks.The findings of this study indicate that the proposed MSGE-LS is an effective method because its result proves that it increases the number of clusters,average energy consumption,lifespan extension,reduction in average packet loss,and end-to-end delay. | P.Kavitha Rani Hee-Kwon Chae Yunyoung Nam Mohamed Abouhawwash | 2023 | Intelligent Automation & Soft Computing2023，，6： | 0 |
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