审查人工智能 (AI) 方法在作物研究中的应用
Suvojit Bose1, Saptarshi Banerjee2, Soumya Kumar3
1Department of Vegetables and Spice Crops, Uttar Banga Krishi Viswavidyalaya, Pundibari, Cooch Behar, 736165, West Bengal, India.
Journal of applied genetics
|January 12, 2024
概括
人工智能 (AI),包括机器学习 (ML) 和深度学习 (DL),通过分析大型数据集进行基因组选择和精确的表型化,为全球粮食安全加速育种,提供先进的作物改进.
科学领域:
- 农业科学 农业科学
- 计算生物学 计算生物学
- 遗传学 是一个遗传学.
背景情况:
- 养活日益增长的全球人口需要先进的作物改良技术.
- 人工智能 (AI),包括机器学习 (ML) 和深度学习 (DL),模拟机器中的人类智能来分析复杂的数据.
研究的目的:
- 提供ML和DL在作物改良中的应用的全面概述.
- 突出AI在增强基因组选择,基因组编辑和加速繁殖的表型预测方面的潜力.
主要方法:
- 对大规模基因组和表型数据集应用的ML和DL算法的审查.
- 分析AI在概括模式,优化预测和促进基因型选择方面的作用.
主要成果:
- ML和DL技术在分析大量的遗传和特征数据方面是有效的.
- 人工智能有助于开发精确的预测模型,用于基因组选择和精确的表型.
结论:
- 人工智能,ML和DL为高级作物改进提供了高效,特定和安全的方法.
- 这些计算方法对于加速育种计划和应对农业挑战至关重要.
相关概念视频
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