School of Food and Environment , Dalian University of Technology , Panjin 124221 , China.
State Key Laboratory of Environmental Criteria and Risk Assessment , Chinese Research Academy of Environmental Sciences , Beijing 100012 , China.
Environ Sci Technol. 2019 May 7;53(9):5151-5158. doi: 10.1021/acs.est.8b07321. Epub 2019 Apr 15.
Microplastics (MPs) in aquatic organisms are raising increasing concerns regarding their potential damage to ecosystems. To date, Raman and Fourier transform infrared spectroscopy techniques have been widely used for detection of MPs in aquatic organisms, which requires complex protocols of tissue digestion and MP separation and are time- and reagent-consuming. This novel approach directly separates, identifies, and characterizes MPs from the hyperspectral image (HSI) of the intestinal tract content in combination with a support vector machine classification model, instead of using the real digestion/separation protocols. The procedures of HSI acquisition (1 min) and data analysis (5 min) can be completed within 6 min plus the sample preparation and drying time (30 min) where necessary. This method achieved a promising efficiency (recall >98.80%, precision >96.22%) for identifying five types of MPs (particles >0.2 mm). Moreover, the method was also demonstrated to be effective on field fish from three marine fish species, revealing satisfying detection accuracy (particles >0.2 mm) comparable to Raman analysis. The present technique omits the digestion protocol (reagent free), thereby significantly reducing reagent consumption, saving time, and providing a rapid and efficient method for MP analysis.
微塑料(MPs)在水生生物体内引起了越来越多的关注,因为它们可能对生态系统造成损害。迄今为止,拉曼和傅里叶变换红外光谱技术已广泛用于检测水生生物中的 MPs,这些技术需要复杂的组织消化和 MP 分离协议,既费时又费试剂。本研究提出了一种新方法,该方法直接从肠道内容物的高光谱图像(HSI)中分离、识别和表征 MPs,同时结合支持向量机分类模型,而无需使用实际的消化/分离方案。HSI 采集(1 分钟)和数据分析(5 分钟)的过程可以在 6 分钟内完成,加上必要的样品制备和干燥时间(30 分钟)。该方法对五种类型的 MPs(粒径>0.2 毫米)的识别效率较高(召回率>98.80%,精度>96.22%)。此外,该方法还成功应用于三种海洋鱼类的野外鱼类,对粒径>0.2 毫米的 MPs 检测具有较高的准确性,与拉曼分析相当。本技术省略了消化方案(无试剂),从而显著减少了试剂消耗,节省了时间,为 MPs 分析提供了一种快速有效的方法。