在camu-camu中使用视觉变压器自动测量甲酸水平
Juan Carlos Gutiérrez Cáceres1, Paolo Cesar Leonel Blancas Lopez2, Richard Esmith Gaviria Huanio2
1Faculty Computer Science, Universidad Nacional de San Agustin, Arequipa, Peru.
Frontiers in plant science
|December 12, 2025
概括
本研究介绍了一种基于图像的自动化方法,用于估计camu-camu.camu中的 Askorbic 酸. 该系统使用计算机视觉准确预测维生素C水平,使生产者和制药行业受益.
科学领域:
- 农业科学 农业科学
- 生物技术是生物技术.
- 计算机视觉 计算机视觉
背景情况:
- 卡姆卡姆 (Myrciaria dubia) 是一种热带水果,含有异常高的维生素C.
- 传统的测量甲酸量化的方法需要专门的实验室设备,这限制了现场应用.
- 需要具有成本效益,可访问的方法来评估水果中的维生素C.
研究的目的:
- 开发一种全自动化和具有成本效益的方法,使用图像分析量化camu-camu中的 Askorbic 酸.
- 评估使用水果大小和成熟阶段来预测甲酸度的可行性.
- 推进计算机视觉在制药和农业领域的应用.
主要方法:
- 开发了一个集成的管道,将实时检测变压器 (RT-DETR) 用于果实检测和视觉变压器 (ViT) 用于成熟阶段分类.
- 设计了一种基于图像的估计模型,根据水果大小和成熟阶段来预测甲酸度.
- 性能与YOLOv8和VGG16.6等既有模型进行了比较.
主要成果:
- RT-DETR实现了高精度 (0.970) 和回忆 (0.976),超过了YOLOv8.
- 与VGG16 (0.946) 相比,ViT分类器显示出更高的精度 (0.970).
- 基于图像的估计模型显示了非常低的预测误差,证实了它对甲酸量化的可靠性.
结论:
- 拟议的自动化系统提供了一个实用,可扩展和准确的解决方案,用于直接从图像中估计 Askorbic 酸.
- 这项技术为camu-camu生产商提供了显著的好处,因为它可以快速评估质量.
- 该研究强调了计算机视觉在制药行业用于水果质量分析的潜力.
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