Analyzing and optimizing yield formation of tomato introgression lines using plant model

文献类型： 外文期刊

第一作者： Kang, Mengzhen

作者： Kang, Mengzhen;Wang, Xiujuan;Kang, Mengzhen;Wang, Xiujuan;Qi, Rui;Jia, Zhi-Qi;de Reffye, Philippe;Huang, San-Wen

作者机构：

关键词： GreenLab model; Yield formation; Parameter estimation; Tomato introgression line; Optimization

期刊名称：EUPHYTICA （ 影响因子：1.614； 五年影响因子：1.883 ）

ISSN： 0014-2336

年卷期： 2021 年 217 卷 6 期

页码：

收录情况： SCI

摘要： Generally, the relation between quantitative trait loci (QTLs) and yield is empirical, and their roles in source-sink dynamics are unclear. A tomato introgression line (IL) population (S. pennellii ILs) was applied to analyze the effect of chromosome segment from wild cultivar on numerous yield-related phenotypes, including plant yield, the weight of vegetative part, the number and weight of individual fruits. A functional-structural plant model was applied to analyze the difference in yield formation of tomato ILs. Measurements on organ biomass were performed at four stages during the growth period of plants. Source and sink parameters were estimated from the experimental measurements of different organs for each IL, discovering how the final yield is linked to the fruit number, size and expansion process. The correlation and distribution of source-sink parameters for ILs were analyzed. The sink parameters were optimized to find a better combination of ILs to improve the yield using Particle Swarm Optimisation (PSO) algorithm. Optimization results indicate a potential yield increase of 35% for the control M82. This model-assisted analysis provides a promising approach to deeper insight in phenotypic data.

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