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231039

Artificial Intelligence for Plant Genomics and Crop Improvement

Article

Last updated: 01 Jan 2025

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Abstract

BECAUSE of rapidly increasing population growth rates, food scarcity has developed into a serious global problem. Furthermore, population growth is expected to reach nine billion by 2050, likely resulting in dramatic issues with the global food supply and accessibility. Numerous technologies are being developed to boost food production in agriculture to close the food gap and overcome obstacles such as climate change, water scarcity, disease, and pests. Understanding plant genomics may facilitate the identification, cloning, and sequencing of genes involved in resistance to adverse environmental influences. Numerous techniques for crop improvement have emerged over the last few decades, including tissue culture transformation and mutagenesis. Recently, artificial intelligence and machine learning have been integrated as a potential multidisciplinary approach to enhancing and improving the agriculture sector, including food, and this field is rapidly evolving. This review explores plant genomics as a solution to future food security concerns by examining the relationship of agriculture, food production, and artificial intelligence as a promising approach for determining the genome and its variations to genetically improve crops in future agriculture.

DOI

10.21608/ejbo.2022.83200.1731

Keywords

agriculture, artificial intelligence, crop improvement, Deep learning, Machine Learning, Plant genomics

Authors

First Name

Yasmine

Last Name

Hatem

MiddleName

-

Affiliation

Faculty of Biotechnology; October University for Modern Sciences and Arts (MSA), Cairo, Egypt

Email

yasmin.hatem@msa.edu.eg

City

Cairo

Orcid

-

First Name

Gehan

Last Name

Hammad

MiddleName

-

Affiliation

Faculty of Biotechnology; October University for Modern Sciences and Arts (MSA), Cairo, Egypt

Email

gmhammad@msa.edu.eg

City

Cairo

Orcid

-

First Name

Gehan

Last Name

Safwat

MiddleName

-

Affiliation

Faculty of Biotechnology; October University for Modern Sciences and Arts (MSA), Cairo, Egypt

Email

gehan.safwat@hotmail.co.uk

City

Cairo

Orcid

-

Volume

62

Article Issue

2

Related Issue

33732

Issue Date

2022-05-01

Receive Date

2021-07-04

Publish Date

2022-05-01

Page Start

291

Page End

303

Print ISSN

0375-9237

Online ISSN

2357-0350

Link

https://ejbo.journals.ekb.eg/article_231039.html

Detail API

https://ejbo.journals.ekb.eg/service?article_code=231039

Order

1

Type

Review

Type Code

1,042

Publication Type

Journal

Publication Title

Egyptian Journal of Botany

Publication Link

https://ejbo.journals.ekb.eg/

MainTitle

Artificial Intelligence for Plant Genomics and Crop Improvement

Details

Type

Article

Created At

22 Jan 2023