Cargando…
Accelerating the Detection of Bacteria in Food Using Artificial Intelligence and Optical Imaging
In assessing food microbial safety, the presence of Escherichia coli is a critical indicator of fecal contamination. However, conventional detection methods require the isolation of bacterial macrocolonies for biochemical or genetic characterization, which takes a few days and is labor-intensive. In...
Autores principales: | Ma, Luyao, Yi, Jiyoon, Wisuthiphaet, Nicharee, Earles, Mason, Nitin, Nitin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society for Microbiology
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9888199/ https://www.ncbi.nlm.nih.gov/pubmed/36533914 http://dx.doi.org/10.1128/aem.01828-22 |
Ejemplares similares
-
Quantitative Imaging of Bacteriophage Amplification for Rapid Detection of Bacteria in Model Foods
por: Wisuthiphaet, Nicharee, et al.
Publicado: (2022) -
Application of Engineered Bacteriophage T7 in the Detection of Bacteria in Food Matrices
por: Wisuthiphaet, Nicharee, et al.
Publicado: (2021) -
Rapid detection of Escherichia coli using bacteriophage-induced lysis and image analysis
por: Yang, Xu, et al.
Publicado: (2020) -
Rapid detection of Escherichia coli in beverages using genetically engineered bacteriophage T7
por: Wisuthiphaet, Nicharee, et al.
Publicado: (2019) -
Spectroscopy Approaches for Food Safety Applications: Improving Data Efficiency Using Active Learning and Semi-supervised Learning
por: Zhang, Huanle, et al.
Publicado: (2022)