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基于人工智能的生长阶段分类和草种植中的精确营养管理的SmartBerry
Daison Darlan1, Oladayo S Ajani1, Joon Woo An2
1Department of Artificial Intelligence, Kyungpook National University, Daegu, Republic of Korea.
Scientific reports
|April 23, 2025
概括
人工智能 (AI) 可以精确地分类草生长阶段,以更好地管理营养. 这种人工智能方法可以提高可持续园艺的作物产量和质量.
科学领域:
- 农业科学 农业科学
- 计算机科学 计算机科学
- 园艺园艺 园艺园艺
背景情况:
- 传统农业面临着环境挑战,需要可持续的做法.
- 优化营养管理对于作物产量和质量至关重要.
- 人工智能在农业中的应用正在扩大,但缺乏对草生长阶段的具体关注.
研究的目的:
- 使用人工智能解决草生长阶段分类尚未探索的领域.
- 开发一个强大的数据集,用于对AI模型进行基准测试.
- 为了实现园艺中的精确和可持续的营养管理.
主要方法:
- 在七个生长阶段收集了草植物的新温室数据集.
- 基于基准的多个最先进的AI模型用于增长阶段分类.
- 使用测试准确度评估模型性能.
主要成果:
- EfficientNetB7模型实现了0.837.7的测试准确度.
- 这证明了AI在分类草生长阶段的有效性.
- 在现有数据集和方法中发现了空白.
结论:
- 人工智能驱动的生长阶段分类是优化草营养管理的一个有希望的方法.
- 准确的分类可以提高产量和水果质量.
- 开发的数据集和基准测试为未来的研究提供了基础.
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