Artificial Intelligence for Plant Genomics and Crop Improvement | ||||
| Egyptian Journal of Botany | ||||
| Article 1, Volume 62, Issue 2, May 2022, Page 291-303 PDF (1.51 MB) | ||||
| Document Type: Special Issue (Review) | ||||
| DOI: 10.21608/ejbo.2022.83200.1731 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Yasmine Hatem; Gehan Hammad  ; Gehan Safwat
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| Faculty of Biotechnology; October University for Modern Sciences and Arts (MSA), Cairo, Egypt | ||||
| 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. | ||||
| Keywords | ||||
| Agriculture; Artificial intelligence; Crop improvement; Deep learning; Machine learning; Plant genomics | ||||
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