Spectroscopic quantification of bacteria using artificial neural networks.
Fourier transform-infrared spectroscopy, in conjunction with artificial neural networks, has been used for identification and classification of selected foodborne pathogens. Five bacterial species (Enterococcus faecium, Salmonella Enteritidis, Bacillus cereus, Yersinia enterocolitica, Shigella boydii) and five Escherichia coli strains (O103, O55, O121, O30, O26) suspended in phosphate-buffered saline were enumerated to provide seven different concentrations ranging from 10(9) to 10(3) CFU/ ml. The trained artificial neural networks were then validated with an independent subset of samples and compared with the traditional plate count method. It was found that the concentration-based classification of the species was 100% correct and the strain-based classification was 90 to 100% accurate.
Gupta
Mathala J
MJ
Department of Agricultural and Biological Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, USA.
Irudayaraj
Joseph
J
Debroy
Chitrita
C
D001409:Bacillus cereus / Q000145:classification / Q000302:isolation & purification; D001419:Bacteria / Q000145:classification* / Q000302:isolation & purification*; D015373:Bacterial Typing Techniques / Q000379:methods*; D015169:Colony Count, Microbial; D016984:Enterococcus faecium / Q000145:classification / Q000302:isolation & purification; D004925:Escherichia / Q000145:classification / Q000302:isolation & purification; D005506:Food Contamination / Q000032:analysis*; D005516:Food Microbiology; D016571:Neural Networks, Computer; D012477:Salmonella enteritidis / Q000145:classification / Q000302:isolation & purification; D012680:Sensitivity and Specificity; D012761:Shigella boydii / Q000145:classification / Q000302:isolation & purification; D013045:Species Specificity; D017550:Spectroscopy, Fourier Transform Infrared / Q000379:methods*; D015008:Yersinia enterocolitica / Q000145:classification / Q000302:isolation & purification