%0 Journal Article 
%A Gómez‑González, Emilio
%A Fernández‑Muñoz, Beatriz
%A Barriga‑Rivera, Alejandro
%A Navas‑García, José Manuel
%A Fernández‑Lizaranzu, Isabel
%A Munoz‑González, Francisco Javier
%A Parrilla‑Giráldez, Rubén
%A Requena‑Lancharro, Desiree
%A Guerrero‑Claro, Manuel
%A Gil‑Gamboa, Pedro
%A Rosell‑Valle, Crsitina
%A Gómez‑González, Carmen
%A Mayorga‑Buiza, Maria José
%A Martín‑López, María
%A Muñoz, Olga
%A Gómez Martín, Juan Carlos
%A Relimpio López, María Isabel
%A Aceituno‑Castro, Jesús
%A Perales‑Esteve, Manuel A.
%A Puppo‑Moreno, Antonio
%A García Cózar, Francisco José
%A Olvera Collantes, Lucía
%A de los Santos‑Trigo, Silvia
%A Gómez, Emilia
%A Sánchez Pernaute, Rosario
%A Padillo‑Ruiz, Javier
%A Márquez‑Rivas, Javier
%T Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples
%D 2021
%@ 2045-2322
%U http://hdl.handle.net/10498/25717
%X 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.mu 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.
%~ Universidad de Cádiz