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使用人工智能技术评估作物水压力的最新方法:一篇评论

Soo Been Cho¹, Hidayat Mohamad Soleh¹, Ji Won Choi¹

¹Department of Biosystems Engineering, College of Agricultural and Life Sciences, Gyeongsang National University, 501, Jinju-daero, Jinju-si 52828, Gyeongsangnam-do, Republic of Korea.

Sensors (Basel, Switzerland)

|October 16, 2024

概括

这项研究审查了人工智能 (AI) 和远程传感用于作物水压力监测. 这些技术有助于提高农业生产率,减轻气候变化对作物的影响.

科学领域:

农业科学农业科学
环境科学环境科学
计算机科学计算机科学

背景情况:

全球气温上升和气候变化加剧了作物水压.
降水模式的变化给农业生产率带来了重大挑战.
有效监测和预测作物水压对于可持续农业至关重要.

研究的目的:

系统地审查人工智能 (AI) 和遥感技术的整合,用于作物水压力管理.
评估各种非破坏性遥感平台和人工智能技术在监测和预测作物水压方面的有效性.
在数据有限的条件下探索这些技术的战略组合,以提高农业生产率.

主要方法:

对人工智能和遥感在农业中的整合进行系统的文献审查.
对非破坏性遥感平台的分析:RGB,热和高光谱成像.
对人工智能技术的评估:机器学习,深度学习,整体方法,GAN和XAI.

主要成果:

人工智能和遥感为监测作物水压提供了有效的,非破坏性的方法.
不同的平台和人工智能技术在准确性和适用性方面表现出不同的优势.
战略整合可以提高作物水应激预测,即使数据有限.

结论:

人工智能和遥感的整合对于应对气候变化对农业的影响至关重要.
这些技术为改善水压下的作物产量和质量提供了工具.
进一步的研究可以优化适应性和可持续农业系统的综合方法.

关键词:

人工智能 (AI) 是一种人工智能.农作物农作物农作物深度学习是一种深度学习.机器学习是机器学习.水的压力是水压力.

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