'American Society of Agricultural and Biological Engineers (ASABE)'
Abstract
Not AvailableFTIR Absrobance spectra in conjunction with artificaial Neural Networks(ANNs) were used to differentiate selected microorganisms at the generic and serogroup levels. The ANN consisted of three layers with 595 input nodes, 50 nodes at the hidden layer and 5 output nides(one for each microorganism or strain). The replications of each experiment were conducted, and 70% of the data was used for training and 30% for validation of the network. Result indicated that differentiation could be achieved at an accuracy of 80% to 100% at thegeneric level nd 90% to 100% at the serogroup level at 10 * * 3 CFU/ml concentration.Not Availabl
