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Shape matters for microplastics, but its definition, particularly for hyperspectral imaged microplastics, remains ambiguous and inexplicit, leading to incomparability across data. Hyperspectral imaging is a common approach for quantification, yet no unambiguous microplastic shape classification exists. We conducted an expert-based survey and proposed a set of clear and concise shapes (, , , , , , , , and ). The categories were validated on images of 11,042 microplastics from four environmental compartments (seven matrices: indoor air; wastewater influent, effluent, and sludge; marine water; stormwater; and stormwater pond sediments), by inviting five experts to score each shape. We found that the proposed shapes were well defined, representative, and distinguishable to the human eye, especially for and . , , and were though less distinguishable but dominated in all water and solid matrices. Indoor air held more , an abstract shape that appeared mostly for particles below 30 μm. This study highlights the need for assessing the recognizability of chosen shape categories prior to reporting data. Shapes with a clear and stringent definition would increase comparability and reproducibility across data and promote harmonization in microplastic research.
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http://dx.doi.org/10.1021/acs.est.3c03517 | DOI Listing |
Front Plant Sci
August 2025
Jilin Academy of Agricultural Sciences Peanut Institute, Gongzhuling, Jilin, China.
Introduction: Sorghum is an important food and feed crop. Identifying sorghum seed varieties is crucial for ensuring seed quality, improving planting efficiency, and promoting sustainable agricultural development.
Methods: This study proposes a high-precision classification method based on the fusion of RGB images and hyperspectral data, using an improved deep residual convolutional neural network.
J Am Chem Soc
September 2025
Department of Chemistry and Biochemistry, UC San Diego, La Jolla, California 92093, United States.
Chemical imaging holds great promise for chemical, materials, and biological applications. However, its contrast often relies on subtle spectral differences arising from molecular-level changes. Here, we introduce label-free chemical imaging based on bond-specific coherent interference, which is highly sensitive to nanoscopic structural variations in collagen fibers.
View Article and Find Full Text PDFSci Total Environ
September 2025
Department of Geological Sciences and Geological Engineering, Queen's University, 99 University Ave, K7L 3N6 Kingston, Ontario, Canada.
Hyperspectral data have been overshadowed by multispectral data for studying algal blooms for decades. However, newer hyperspectral missions, including the recent Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) Ocean Color Instrument (OCI), are opening the doors to accessible hyperspectral data, at spatial and temporal resolutions comparable to ocean color and multispectral missions. Simulation studies can help to understand the potential of these hyperspectral sensors prior to launch and without extensive field data collection.
View Article and Find Full Text PDFJ Food Sci
September 2025
College of Food and Bioengineering, Zhengzhou University of Light Industry, Zhengzhou, China.
Primary agricultural products are closely related to our daily lives, as they serve not only as raw materials for food processing but also as products directly purchased by consumers. These products face the issue of freshness decline and spoilage during both production and consumption. Freshness degradation induces sensory deterioration and nutritional loss and promotes harmful substance accumulation, causing gastrointestinal issues or even endangering life.
View Article and Find Full Text PDFJ Dairy Sci
September 2025
Advance Image Processing Research Laboratory (AIPRL), Institute of Computer and Software Engineering, Khwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan 64200, Pakistan.
Food contamination remains a serious global concern due to its health risks, with milk being one of the most commonly adulterated foods in developing countries such as Pakistan, India, and Bangladesh. Accurate detection of milk contamination is essential for ensuring consumer safety and maintaining food industry standards. This study explores both invasive and noninvasive approaches for contamination analysis.
View Article and Find Full Text PDF