Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples
| Field | Value | Language |
| dc.contributor.author | Gomez-Gonzalez, Emilio | en |
| dc.contributor.author | Fernandez-Muñoz, Beatriz | en |
| dc.contributor.author | Barriga-Rivera, Alejandro | en |
| dc.contributor.author | Navas-Garcia, Jose Manuel | en |
| dc.contributor.author | Fernandez-Lizaranzu, Isabel | en |
| dc.contributor.author | Munoz-Gonzalez, Francisco Javier | en |
| dc.contributor.author | Parrilla-Giraldez, Ruben | en |
| dc.contributor.author | Requena-Lancharro, Desiree | en |
| dc.contributor.author | Guerrero-Claro, Manuel | en |
| dc.contributor.author | Gil-Gamboa, Pedro | en |
| dc.contributor.author | Rosell-Valle, Cristina | en |
| dc.contributor.author | Gomez-Gonzalez, Carmen | en |
| dc.contributor.author | Mayorga-Buiza, Maria Jose | en |
| dc.contributor.author | Martin-Lopez, Maria | en |
| dc.contributor.author | Muñoz, Olga | en |
| dc.contributor.author | Martin, Juan Carlos Gomez | en |
| dc.contributor.author | Lopez, Maria Isabel Relimpio | en |
| dc.contributor.author | Aceituno-Castro, Jesus | en |
| dc.contributor.author | Perales-Esteve, Manuel A. | en |
| dc.contributor.author | Puppo-Moreno, Antonio | en |
| dc.contributor.author | Cozar, Francisco Jose Garcia | en |
| dc.contributor.author | Olvera-Collantes, Lucia | en |
| dc.contributor.author | de los Santos-Trigo, Silvia | en |
| dc.contributor.author | Gomez, Emilia | en |
| dc.contributor.author | Pernaute, Rosario Sanchez | en |
| dc.contributor.author | Padillo-Ruiz, Javier | en |
| dc.contributor.author | Marquez-Rivas, Javier | en |
| dc.date.accessioned | 2021-10-19T02:28:18Z | |
| dc.date.available | 2021-10-19T02:28:18Z | |
| dc.date.issued | 2021 | |
| dc.identifier.uri | https://hdl.handle.net/2123/26558 | |
| dc.description.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. | en |
| dc.language.iso | en | en |
| dc.rights | Other | |
| dc.subject | COVID-19 | en |
| dc.subject | Coronavirus | en |
| dc.title | Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples | en |
| dc.type | Article | en |
| dc.identifier.doi | 10.1038/s41598-021-95756-3 | |
| usyd.faculty | Faculty of Engineering, School of Biomedical Engineering |
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