Smart breeding driven by big data, artificial intelligence, and integrated genomic-enviromic prediction-Reference-Cited by-同舟云学术

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Smart breeding driven by big data, artificial intelligence, and integrated genomic-enviromic prediction

Published:2022-11 Issue:11 Volume:15 Page:1664-1695
ISSN:1674-2052
Container-title:Molecular Plant
language:en
Short-container-title:Molecular Plant

Author:

Xu Yunbi,Zhang Xingping,Li Huihui,Zheng Hongjian,Zhang Jianan,Olsen Michael S.,Varshney Rajeev K.,Prasanna Boddupalli M.,Qian Qian

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering

Reference247 articles.

1. Deep learning versus parametric and ensemble methods for genomic prediction of complex phenotypes;Abdollahi-Arpanahi;Genet. Sel. Evol,2020

2. Genomic models with genotype × environment interaction for predicting hybrid performance: an application in maize hybrids;Acosta Pech;Theor. Appl. Genet,2017

3. Genome-wide association studies using binned genotypes;An;Heredity,2020

4. Performance prediction of crosses in plant breeding through genotype by environment interactions;Ansarifar;Sci. Rep.,2020

5. Translating high-throughput phenotyping into genetic gain;Araus;Trends Plant Sci.,2018

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