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  • Hyperspectral image process...
    Gomez-Gonzalez, Emilio; Fernandez-Muñoz, Beatriz; Barriga-Rivera, Alejandro; Navas-Garcia, Jose Manuel; Fernandez-Lizaranzu, Isabel; Munoz-Gonzalez, Francisco Javier; Parrilla-Giraldez, Ruben; Requena-Lancharro, Desiree; Guerrero-Claro, Manuel; Gil-Gamboa, Pedro; Rosell-Valle, Cristina; Gomez-Gonzalez, Carmen; Mayorga-Buiza, Maria Jose; Martin-Lopez, Maria; Muñoz, Olga; Martin, Juan Carlos Gomez; Lopez, Maria Isabel Relimpio; Aceituno-Castro, Jesus; Perales-Esteve, Manuel A.; Puppo-Moreno, Antonio; Cozar, Francisco Jose Garcia; Olvera-Collantes, Lucia; de los Santos-Trigo, Silvia; Gomez, Emilia; Pernaute, Rosario Sanchez; Padillo-Ruiz, Javier; Marquez-Rivas, Javier

    Scientific reports, 08/2021, Letnik: 11, Številka: 1
    Journal Article

    Abstract Optical spectroscopic techniques have been commonly used to detect the presence of biofilm-forming pathogens (bacteria and fungi) in the agro-food industry. Recently, near-infrared (NIR) spectroscopy revealed that it is also possible to detect the presence of viruses in animal and vegetal tissues. Here we report a platform based on visible and NIR (VNIR) hyperspectral imaging for non-contact, reagent free detection and quantification of laboratory-engineered viral particles in fluid samples (liquid droplets and dry residue) using both partial least square-discriminant analysis and artificial feed-forward neural networks. The detection was successfully achieved in preparations of phosphate buffered solution and artificial saliva, with an equivalent pixel volume of 4 nL and lowest concentration of 800 TU· $$\upmu$$ μ L −1 . This method constitutes an innovative approach that could be potentially used at point of care for rapid mass screening of viral infectious diseases and monitoring of the SARS-CoV-2 pandemic.