AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (3.3 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research paper | Open Access

Genetic analysis of the seed dehydration process in maize based on a logistic model

Shuangyi Yina, Jun Liua, Tiantian Yanga, Pengcheng Lia, Yang Xua, Huimin Fanga, Shuhui Xua, Jie Weia, Lin Xueb, Derong Haob, Zefeng Yanga( ), Chenwu Xua( )
Jiangsu Provincial Key Laboratory of Crop Genetics and Physiology, Co-Innovation Center for Modern Production Technology of Grain Crops, Key Laboratory of Plant Functional Genomics of Ministry of Education, Yangzhou University, Yangzhou 225009, Jiangsu, China
Jiangsu Yanjiang Institute of Agricultural Sciences, Nantong 226541, Jiangsu, China

Peer review under responsibility of Crop Science Society of China and Institute of Crop Science, CAAS.

Show Author Information

Abstract

Seed moisture at harvest is a critical trait affecting maize quality and mechanized production, and is directly determined by the dehydration process after physiological maturity. However, the dynamic nature of seed dehydration leads to inaccurate evaluation of the dehydration process by conventional determination methods. Seed dry weight and fresh weight were recorded at 14 time points after pollination in a recombinant inbred line (RIL) population derived from two inbred lines with contrasting seed dehydration dynamics. The dehydration curves of RILs were determined by fitting trajectories of dry weight accumulation and dry weight/fresh weight ratio change based on a logistic model, allowing the estimation of eight characteristic parameters that can be used to describe dehydration features. Quantitative trait locus (QTL) mapping, taking these parameters as traits, was performed using multiple methods. Single-trait QTL mapping revealed 76 QTL associated with dehydration characteristic parameters, of which the phenotypic variation explained (PVE) was 1.03% to 15.24%. Multiple-environment QTL analysis revealed 21 related QTL with PVE ranging from 4.23% to 11.83%. Multiple-trait QTL analysis revealed 58 QTL, including 51 pleiotropic QTL. Combining these mapping results revealed 12 co-located QTL and the dehydration process of RILs was divided into three patterns with clear differences in dehydration features. These results not only deepen general understanding of the genetic characteristics of seed dehydration but also suggest that this approach can efficiently identify associated genetic loci in maize.

References

【1】
【1】
 
 
The Crop Journal
Pages 182-193

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
Yin S, Liu J, Yang T, et al. Genetic analysis of the seed dehydration process in maize based on a logistic model. The Crop Journal, 2020, 8(2): 182-193. https://doi.org/10.1016/j.cj.2019.06.011

1008

Views

13

Downloads

15

Crossref

N/A

Web of Science

18

Scopus

0

CSCD

Received: 04 April 2019
Revised: 28 May 2019
Accepted: 27 July 2019
Published: 20 October 2019
© 2019 Crop Science Society of China and Institute of Crop Science, CAAS.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).