Predicting biomass of rice with intermediate traits: Modeling method combining crop growth models and genomic prediction models-Reference-Cited by-同舟云学术

Predicting biomass of rice with intermediate traits: Modeling method combining crop growth models and genomic prediction models

Published:2020-06-19 Issue:6 Volume:15 Page:e0233951
ISSN:1932-6203
Container-title:PLOS ONE
language:en
Short-container-title:PLoS ONE

Author:

Toda Yusuke,Wakatsuki Hitomi,Aoike Toru,Kajiya-Kanegae Hiromi,Yamasaki Masanori,Yoshioka Takuma,Ebana Kaworu,Hayashi Takeshi,Nakagawa Hiroshi,Hasegawa Toshihiro,Iwata Hiroyoshi^ORCID

Funder

Japan Society for the Promotion of Science

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference69 articles.

1. Prediction of Total Genetic Value Using Genome-Wide Dense Marker Maps;THE Meuwissen;Genetics,2001

2. Changes in genetic selection differentials and generation intervals in US Holstein dairy cattle as a result of genomic selection;A García-Ruiz;Proceedings of the National Academy of Sciences,2016

3. Jannink. Genomic, Marker-Assisted, and Pedigree-BLUP Selection Methods for β-Glucan Concentration in Elite Oat;G Asoro;Crop Sci,2013

4. Genetic Gain from Phenotypic and Genomic Selection for Quantitative Resistance to Stem Rust of Wheat;J Rutkoski;Plant Genome

5. Potential of Genomic Selection in Mass Selection Breeding of an Allogamous Crop: An Empirical Study to Increase Yield of Common Buckwheat;S Yabe;Front Plant Sci,2018

Cited by 14 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Robotized indoor phenotyping allows genomic prediction of adaptive traits in the field;Nature Communications;2023-10-19

2. Upcycling rice yield trial data using a weather-driven crop growth model;Communications Biology;2023-07-21

3. Integrating biophysical crop growth models and whole genome prediction for their mutual benefit: a case study in wheat phenology;Journal of Experimental Botany;2023-05-13

4. Imaging Sensor-Based High-Throughput Measurement of Biomass Using Machine Learning Models in Rice;Agriculture;2023-04-12

5. Predicting Genotype × Environment × Management (G × E × M) Interactions for the Design of Crop Improvement Strategies;Plant Breeding Reviews;2022-11-18