植物识别应用程序无法可靠地识别美国中西部有毒和食用植物
Kevan Long1,2, Andrew Townesmith3, Alex Overmiller2
1Division of Emergency Medicine, Saint Louis University School of Medicine, St. Louis, MO, United States.
Clinical toxicology (Philadelphia, Pa.)
|August 3, 2023
概括
植物识别的智能手机应用程序对采集者来说是不可靠的. 即使是流行的应用程序也错误地将有毒植物视为可食用植物,强调了人类植物学专业知识的必要性,以防止中毒.
科学领域:
- 植物学 植物学
- 毒理学 毒理学 毒理学
- 移动技术 移动技术
背景情况:
- 植物中毒是一个重大的公共卫生问题,导致许多紧急访问.
- 植物学知识有限的个人经常使用智能手机应用程序来识别野生植物以获取食物.
- 这些应用程序在区分食用植物和有毒植物方面的准确性基本上是未知的.
研究的目的:
- 评估智能手机应用程序在识别植物方面的可靠性.
- 评估这些应用程序在美国中西部区分食用物种和有毒物种的能力.
- 为了确定当前的技术是否可以安全地指导食决策.
主要方法:
- 根据区域的可用性和错误识别的可能性,选择了16种植物物种 (5种可食用,3种半有毒,8种有毒).
- 植物学家识别并拍摄了不同生长阶段的植物标本.
- 四个流行的植物识别应用程序 (LeafSnap,PictureThis,Pl@ntNet,PlantSnap) 用于分析.
主要成果:
- 总体而言,属的识别准确率为76% (PictureThis: 96%,PlantSnap: 53%).
- 鉴定物种的准确性平均为58% (PictureThis: 94%,PlantSnap: 34%).
- 在11种有毒物种中,有5种被至少一个应用错误地确定为食用物种.
结论:
- 智能手机应用程序用于植物识别的准确性差异很大,PictureThis显示了最高的性能.
- 目前的应用程序不够可靠,无法安全识别食用野生植物.
- 采集者需要大量的植物知识,以确保安全采集和避免有毒植物的摄入.
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