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Bioinformatics in Plant Breeding and Research on Disease Resistance
In the context of plant breeding, bioinformatics can empower genetic and genomic selection to determine the optimal combination of genotypes that will produce a desired phenotype and help expedite the isolation of these new varieties. Bioinformatics is also instrumental in collecting and processing...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9696050/ https://www.ncbi.nlm.nih.gov/pubmed/36432847 http://dx.doi.org/10.3390/plants11223118 |
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author | Mu, Huiying Wang, Baoshan Yuan, Fang |
author_facet | Mu, Huiying Wang, Baoshan Yuan, Fang |
author_sort | Mu, Huiying |
collection | PubMed |
description | In the context of plant breeding, bioinformatics can empower genetic and genomic selection to determine the optimal combination of genotypes that will produce a desired phenotype and help expedite the isolation of these new varieties. Bioinformatics is also instrumental in collecting and processing plant phenotypes, which facilitates plant breeding. Robots that use automated and digital technologies to collect and analyze different types of information to monitor the environment in which plants grow, analyze the environmental stresses they face, and promptly optimize suboptimal and adverse growth conditions accordingly, have helped plant research and saved human resources. In this paper, we describe the use of various bioinformatics databases and algorithms and explore their potential applications in plant breeding and for research on plant disease resistance. |
format | Online Article Text |
id | pubmed-9696050 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96960502022-11-26 Bioinformatics in Plant Breeding and Research on Disease Resistance Mu, Huiying Wang, Baoshan Yuan, Fang Plants (Basel) Review In the context of plant breeding, bioinformatics can empower genetic and genomic selection to determine the optimal combination of genotypes that will produce a desired phenotype and help expedite the isolation of these new varieties. Bioinformatics is also instrumental in collecting and processing plant phenotypes, which facilitates plant breeding. Robots that use automated and digital technologies to collect and analyze different types of information to monitor the environment in which plants grow, analyze the environmental stresses they face, and promptly optimize suboptimal and adverse growth conditions accordingly, have helped plant research and saved human resources. In this paper, we describe the use of various bioinformatics databases and algorithms and explore their potential applications in plant breeding and for research on plant disease resistance. MDPI 2022-11-15 /pmc/articles/PMC9696050/ /pubmed/36432847 http://dx.doi.org/10.3390/plants11223118 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Mu, Huiying Wang, Baoshan Yuan, Fang Bioinformatics in Plant Breeding and Research on Disease Resistance |
title | Bioinformatics in Plant Breeding and Research on Disease Resistance |
title_full | Bioinformatics in Plant Breeding and Research on Disease Resistance |
title_fullStr | Bioinformatics in Plant Breeding and Research on Disease Resistance |
title_full_unstemmed | Bioinformatics in Plant Breeding and Research on Disease Resistance |
title_short | Bioinformatics in Plant Breeding and Research on Disease Resistance |
title_sort | bioinformatics in plant breeding and research on disease resistance |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9696050/ https://www.ncbi.nlm.nih.gov/pubmed/36432847 http://dx.doi.org/10.3390/plants11223118 |
work_keys_str_mv | AT muhuiying bioinformaticsinplantbreedingandresearchondiseaseresistance AT wangbaoshan bioinformaticsinplantbreedingandresearchondiseaseresistance AT yuanfang bioinformaticsinplantbreedingandresearchondiseaseresistance |