Multitrait, Random Regression, or Simple Repeatability Model in High‐Throughput Phenotyping Data Improve Genomic Prediction for Wheat Grain Yield-Reference-Cited by-同舟云学术

Multitrait, Random Regression, or Simple Repeatability Model in High‐Throughput Phenotyping Data Improve Genomic Prediction for Wheat Grain Yield

Published:2017-07 Issue:2 Volume:10 Page:
ISSN:1940-3372
Container-title:The Plant Genome
language:en
Short-container-title:Plant Genome

Author:

Sun Jin¹,Rutkoski Jessica E.¹²,Poland Jesse A.³,Crossa José²,Jannink Jean‐Luc¹⁴,Sorrells Mark E.¹

Affiliation:

1. Dep. of Plant Breeding and GeneticsCornell Univ.IthacaNY14853USA

2. CIMMYTKm. 45, Carretera México‐Veracruz, El BatánTexcocoCP56237Mexico

3. Dep. of Plant Pathology and Dep. of AgronomyKansas State Univ.ManhattanKS66506USA

4. USDA–ARS R.W. Holley Center for Agriculture and HealthIthacaNY14853USA

Funder

United States Agency for International Development

Publisher

Wiley

Subject

Plant Science,Agronomy and Crop Science,Genetics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.3835/plantgenome2016.11.0111

Reference39 articles.

1. Heritabilities and genetic correlations for egg weight traits in Iranian fowl by multi trait and random regression models;Ahrabi M.P.;Int. J. Adv. Biol. Biom. Res.,2015

2. Field high-throughput phenotyping: the new crop breeding frontier

3. Random regression analyses using B-spline functions to model growth of Nellore cattle

4. Butler D. Cullis B. Gilmour A. andGogel B..2009.Mixed models for S language environments: ASReml‐R reference manual. Queensland Dep. of Primary Industries Queensland Australia.https://www.vsni.co.uk/downloads/asreml/release3/asreml‐R.pdf

5. Ridge Regression and Other Kernels for Genomic Selection with R Package rrBLUP

Cited by 146 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. Advancing water absorption capacity in hard winter wheat using a multivariate genomic prediction approach;Crop Science;2024-08-24

2. Modeling soybean growth: A mixed model approach;PLOS Computational Biology;2024-07-11

3. Integrating environmental gradients into breeding: application of genomic reactions norms in a perennial species;Heredity;2024-06-28

4. Leveraging genomics and temporal high‐throughput phenotyping to enhance association mapping and yield prediction in sesame;The Plant Genome;2024-06-26

5. Rice breeding for low input agriculture;Frontiers in Plant Science;2024-06-21