Multi‐trait genomic prediction improves selection accuracy for enhancing seed mineral concentrations in pea-Reference-Cited by-同舟云学术

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Multi‐trait genomic prediction improves selection accuracy for enhancing seed mineral concentrations in pea

Published:2022-10-03 Issue:4 Volume:15 Page:
ISSN:1940-3372
Container-title:The Plant Genome
language:en
Short-container-title:The Plant Genome

Author:

Atanda Sikiru Adeniyi¹^ORCID,Steffes Jenna¹,lan Yang¹,Al Bari Md Abdullah¹,Kim Jeong‐Hwa¹,Morales Mario¹,Johnson Josephine P.¹,Saludares Rica¹,Worral Hannah²,Piche Lisa¹,Ross Andrew¹,Grusak Mike³^ORCID,Coyne Clarice⁴^ORCID,McGee Rebecca⁵⁶,Rao Jiajia¹,Bandillo Nonoy¹^ORCID

Affiliation:

1. Dep. of Plant Sciences North Dakota State Univ. Fargo ND 58108‐6050 USA

2. North Central Research Extension Center NDSU 5400 Hwy. 83 South Minot ND 58701 USA

3. Edward T. Schafer Agricultural Research Center USDA‐ARS 1616 Albrecht Blvd. N Fargo ND 58102‐2765 USA

4. USDA–ARS Plant Germplasm Introduction and Testing, Washington State Univ. Pullman WA 99164 USA

5. USDA–ARS Grain Legume Genetics and Physiology Research Pullman WA 99164 USA

6. Dep. of Horticulture Washington State Univ. Pullman WA 99164 USA

Publisher

Wiley

Subject

Plant Science,Agronomy and Crop Science,Genetics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/tpg2.20260

Reference47 articles.

1. Scalable Sparse Testing Genomic Selection Strategy for Early Yield Testing Stage

2. Harnessing Genetic Diversity in the USDA Pea Germplasm Collection Through Genomic Prediction

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