Zapanta Niña Rose, Santos Rhenz Hannah, Pineda Jericho Ivan, Pedrosa Jireh Sealtiel, Rabelas Kristine Joyce, Samontan Charina, Alvarez Lourdes, Deocaris Chester
Department of Biology, College of Science, Polytechnic University of the Philippines, Sta. Mesa, Manila, 1016, Philippines.
Department of Physical Science, College of Science, Polytechnic University of the Philippines, Sta. Mesa, Manila, 1016, Philippines.
Biol Methods Protoc. 2025 Jan 12;10(1):bpaf004. doi: 10.1093/biomethods/bpaf004. eCollection 2025.
Fungi are eukaryotic organisms grouped based on different traits of their morphology. In 1970, R. W. Rayner published to provide a standardized system for identifying color in fungi. While its terminologies have contributed a standard way of color matching for taxonomic diagnoses, this method using the personal color perception of the observer does not guarantee accuracy. Considering the diversity of fungi, visual color matching is expected to be challenging without a standard assisting instrument. In this study, the R package PUPMCR is developed to approximate the color name and associated pigments of fungal species based on the pixel coordinates of its uploaded image. This software utilizes CIELAB and RGB color spaces as well as Euclidean and Chi-square distance metric systems. The package is tested and validated using 300 fungal images as a dataset for conducting interrater reliability tests. Results showed the highest agreement for parameters utilizing the RGB color space (Cohen's kappa values: 0.655 ± 0.013 for RGB and Euclidean; 0.658 ± 0.004 for RGB and Chi-square), attributed to its computational efficiency, which facilitates more uniform binning and universally scaled distance metrics. The produced color-identifying tool is also available as a Shiny web application (https://pupmcr.shinyapps.io/PUPMCR/) to allow better accessibility for users on the World Wide Web. The development of PUPMCR not only benefits a variety of users from its free accessibility but also provides a more reliable color identification system in the field of mycology.
真菌是根据其形态的不同特征进行分类的真核生物。1970年,R. W. 雷纳发表了相关内容,以提供一种用于识别真菌颜色的标准化系统。虽然其术语为分类诊断提供了一种标准的颜色匹配方法,但这种基于观察者个人颜色感知的方法并不能保证准确性。考虑到真菌的多样性,如果没有标准辅助工具,视觉颜色匹配预计会具有挑战性。在本研究中,开发了R包PUPMCR,以根据上传图像的像素坐标来近似真菌物种的颜色名称和相关色素。该软件利用CIELAB和RGB颜色空间以及欧几里得和卡方距离度量系统。使用300张真菌图像作为数据集进行评分者间可靠性测试,对该包进行了测试和验证。结果表明,利用RGB颜色空间的参数一致性最高(RGB和欧几里得的科恩卡方值:0.655±0.013;RGB和卡方的科恩卡方值:0.658±0.004),这归因于其计算效率,它有助于更均匀的分箱和通用缩放的距离度量。生成的颜色识别工具还可以作为一个闪亮的网络应用程序(https://pupmcr.shinyapps.io/PUPMCR/)使用,以便全球用户更方便地访问。PUPMCR的开发不仅因其免费可用性而使各种用户受益,还在真菌学领域提供了一个更可靠的颜色识别系统。