Collaborative Research: IDBR: New Technology to Measure Oganismal Color Phenotypes: 3D, Hyperspectral, UV-Vis, Virtual Reality Models of Organismal Coloration

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。 这个项目是耶鲁大学和杜克大学的研究人员之间的合作。颜色是许多多细胞生物的重要特征。生物体颜色的科学描述需要详细记录生物体表面反射率的光谱和空间变化。由于许多生物体在交流和伪装中使用颜色，因此生物体的颜色应该在生物体本身，其捕食者和生态伙伴的整个可见光谱上进行描述。目前，还没有可接受的技术方法同时捕获详细的光谱数据和空间几何。 该项目将开发一种新技术，以同时捕获生物体表面几何形状的精确三维（3D）虚拟模型，以及生物体表面光谱反射率空间变化的详细数据。该项目将结合联合收割机3D激光扫描、高光谱成像和3D表面建模来记录各种生物的颜色。除了每个像素的红色、绿色和蓝色（RGB）分量和亮度信息之外，每个高光谱图像还捕获整个反射光谱。该研究还将实施并进一步开发一种新的成像技术，该技术使用计算方法在一次曝光中捕获整个高光谱数据立方体。这项研究将特别关注鸟类，它们具有丰富的颜色多样性和复杂的四色锥视觉系统。 利用这些独特的数据集，将开发新的数学工具，用于对生物体表面的颜色变化进行空间和比较分析，因为它出现在生物体本身的视觉系统中。这些新工具将应用于鸟类羽色变异、机制和进化的初步研究。 这项技术有可能改变生物学家量化、分析和研究生物体颜色的方式。颜色数据集将在耶鲁大学永久管理，并可供其他研究人员和公众使用。研究结果将发表在同行评审的科学期刊上，并将通过《科学美国人》和《自然历史》等科普期刊向更多的受众提供。研究结果也将通过一个新的耶鲁皮博迪博物馆展览传达给纽黑文的种族多样性，城市和经济弱势社区。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). This project is a collaboration between investigators at Yale University and at Duke University. Color is a crucial feature of many multicellular organisms. Scientific description of organism color requires detailed documentation of both the spectral and spatial variation in reflectance of the surface of the organism. Because many organisms use colors in communication and camouflage, organism color should be described over the entire visible spectrum of the organisms themselves, their predators, and ecological partners. Currently, there are no accepted technological methods for capturing detailed spectral data and spatial geometry at the same time. This project will develop a new technology to capture simultaneously an accurate, three-dimensional (3D) virtual model of organism surface geometry, and detailed data on the spatial variation in the spectral reflectance over the surface of the organism. The project will combine 3D laser scanning, hyperspectral imaging, and 3D surface modeling to record the color of diverse organisms. Beyond red, green and blue (RGB) components and brightness information for each pixel, each hyperspectral image captures an entire reflectance spectrum. The research will also implement and further develop a new imaging technology that uses computational methods to capture the entire hyperspectral data cube in a single exposure. The research will focus specifically on birds, which have great color diversity and complex four color cone visual systems. Using these unique data sets, new mathematical tools will be developed for the spatial and comparative analysis of variation in color over the surface of the organism as it appears to the visual systems of organisms themselves. These new tools will be applied in pilot studies of avian plumage color variation, mechanism, and evolution. The proposed technology has the potential to transform the way biologists quantify, analyze, and study the color of organisms. The color data sets will be permanently curated at Yale University, and available for other researchers and the public. The results will be published in peer-reviewed scientific journals, and will be made available to larger audiences through popular science journals like Scientific American and Natural History. Results will also be communicated locally to ethnically diverse, urban, and economically disadvantaged communities in New Haven, CT through a new Yale Peabody Museum exhibit.