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An automated approach for microplastics analysis using focal plane array (FPA) FTIR microscopy and image analysis

机译:使用焦平面阵列(Fpa)FTIR显微镜和图像分析的微塑料分析的自动化方法

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摘要

The analysis of imaging data derived from micro-Fourier transform infrared (μFTIR) microscopy is a powerful tool allowing the analysis of microplastics enriched on membrane filters. In this study we present an automated approach to reduce the time demand currently needed for data analyses. We developed a novel analysis pipeline, based on the OPUS© Software by Bruker, followed by image analysis with Python and Simple ITK image processing modules. By using this newly developed pipeline it was possible to analyse datasets from focal plane array (FPA) μFTIR mapping of samples containing up to 1.8 million single spectra. All spectra were compared against a database of different synthetic and natural polymers by various routines followed by benchmark tests with focus on accuracy and quality. The spectral correlation was optimized for high quality data generation, which allowed image analysis. Based on these results an image analysis approach was developed, providing information on particle numbers and sizes for each polymer detected. It was possible to collect all data with relative ease even for complex sample matrices. This approach significantly decreases the time demand for the interpretation of complex FTIR-imaging data and significantly increases the data quality.
机译:从微傅立叶变换红外(μFTIR)显微镜获得的成像数据的分析是一种强大的工具,可以分析富集在膜滤器上的微塑料。在这项研究中,我们提出了一种自动化的方法来减少当前数据分析所需的时间。我们基于Bruker的OPUS©软件开发了新颖的分析管道,随后使用Python和Simple ITK图像处理模块进行了图像分析。通过使用这个新开发的管线,可以分析焦平面阵列(FPA)μFTIR映射的数据集,这些数据包含多达180万个单一光谱。通过各种例行程序,然后进行以准确性和质量为重点的基准测试,将所有光谱与不同合成和天然聚合物的数据库进行比较。光谱相关性经过优化,可生成高质量数据,从而可以进行图像分析。基于这些结果,开发了一种图像分析方法,可提供有关每种检测到的聚合物的颗粒数量和大小的信息。即使是复杂的样本矩阵,也可以相对轻松地收集所有数据。这种方法显着减少了解释复杂FTIR成像数据的时间需求,并显着提高了数据质量。

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