Analyzing and optimizing yield formation of tomato introgression lines using plant model
Kang, Mengzhen1,2; Wang, Xiujuan1,3; Qi, Rui4; Jia, Zhi-Qi5; de Reffye, Philippe6; Huang, San-Wen7
Source PublicationEUPHYTICA
ISSN0014-2336
2021-06-01
Volume217Issue:6Pages:17
Abstract

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.

KeywordGreenLab model Yield formation Parameter estimation Tomato introgression line Optimization
DOI10.1007/s10681-021-02834-8
WOS KeywordFUNCTIONAL-STRUCTURAL MODEL ; LYCOPERSICON-PENNELLII ; FRUIT SIZE ; NATURAL VARIATION ; GROWTH ; LEAF ; GREENLAB ; IDENTIFICATION ; MORPHOGENESIS ; RESPONSES
Indexed BySCI
Language英语
Funding ProjectNatural Science Foundation of China[62076239] ; Natural Science Foundation of China[31700315] ; Chinese Academy of Science (CAS)-Thailand National Science and Technology Development Agency (NSTDA) Joint Research Program[GJHZ2076]
Funding OrganizationNatural Science Foundation of China ; Chinese Academy of Science (CAS)-Thailand National Science and Technology Development Agency (NSTDA) Joint Research Program
WOS Research AreaAgriculture ; Plant Sciences
WOS SubjectAgronomy ; Plant Sciences ; Horticulture
WOS IDWOS:000646556800001
PublisherSPRINGER
Sub direction classification人工智能+农业
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/44492
Collection复杂系统管理与控制国家重点实验室_平行智能技术与系统团队
Corresponding AuthorWang, Xiujuan
Affiliation1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100949, Peoples R China
3.Chinese Acad Sci, Beijing Engn Res Ctr Intelligent Syst & Technol, Inst Automat, Beijing 100190, Peoples R China
4.Amadeus, 485 Route Pin Montard, F-06410 Biot, France
5.Coll Hort Henan Agr Univ, Zhengzhou 450002, Peoples R China
6.Univ Montpellier, CNRS, AMAP, CIRAD,INRA,IRD, F-34000 Montpellier, France
7.Chinese Acad Agr Sci, Agr Genomes Inst Shenzhen, Shenzhen 518124, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Kang, Mengzhen,Wang, Xiujuan,Qi, Rui,et al. Analyzing and optimizing yield formation of tomato introgression lines using plant model[J]. EUPHYTICA,2021,217(6):17.
APA Kang, Mengzhen,Wang, Xiujuan,Qi, Rui,Jia, Zhi-Qi,de Reffye, Philippe,&Huang, San-Wen.(2021).Analyzing and optimizing yield formation of tomato introgression lines using plant model.EUPHYTICA,217(6),17.
MLA Kang, Mengzhen,et al."Analyzing and optimizing yield formation of tomato introgression lines using plant model".EUPHYTICA 217.6(2021):17.
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