首页> 中文期刊> 《农业科学学报(英文版)》 >What are the differences in yield formation among two cucumber(Cucumis sativus L.)cultivars and their F1hybrid?

What are the differences in yield formation among two cucumber(Cucumis sativus L.)cultivars and their F1hybrid?

         

摘要

To elucidate the mechanisms underlying the differences in yield formation among two parents(P1 and P2) and their F1 hybrid of cucumber, biomass production and whole source–sink dynamics were analyzed using a functional–structural plant model(FSPM) that simulates both the number and size of individual organs. Observations of plant development and organ biomass were recorded throughout the growth periods of the plants. The GreenLab Model was used to analyze the differences in fruit setting, organ expansion, biomass production and biomass allocation. The source–sink parameters were estimated from the experimental measurements. Moreover, a particle swarm optimization algorithm(PSO) was applied to analyze whether the fruit setting is related to the source–sink ratio. The results showed that the internal source–sink ratio increased in the vegetative stage and reached a peak until the first fruit setting. The high yield of hybrid F1 is the compound result of both fruit setting and the internal source–sink ratio. The optimization results also revealed that the incremental changes in fruit weight result from the increases in sink strength and proportion of plant biomass allocation for fruits. The model-aided analysis revealed that heterosis is a result of a delicate compromise between fruit setting and fruit sink strength. The organlevel model may provide a computational approach to define the target of breeding by combination with a genetic model.

著录项

  • 来源
    《农业科学学报(英文版)》 |2020年第7期|1789-1801|共13页
  • 作者单位

    The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 P.R.China;

    Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing 100190 P.R.China;

    Innovation Center for Parallel Agriculture Qingdao Academy of Intelligent Industries Qingdao 266109 P.R.China;

    School of Computer Science and Information Engineering Chongqing Technology and Business University Chongqing 400067 P.R.China;

    College of Information and Electrical Engineering China Agricultural University Beijing 100083 P.R.China;

    College of Land Science and Technology China Agricultural University Beijing 100193 P.R.China;

    Agricultural Genomes Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen 518124 P.R.China;

    AMAP University Montpellier CIRAD CNRS INRA IRD Montpellier 34000 France;

    The School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing 100049 P.R.China;

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