Optical spectral reflectance and multi-spectral image analysis techniques w
ere investigated to characterize chicken hearts for real-time disease detec
tion. Spectral signatures of five categories of chicken hearts (airsacculit
is, ascites, normal, cadaver and septicemia) were obtained from optical ref
lectance measurements taken with a visible/near-infrared spectroscopic syst
em in the range 473 to 974 nm. Multivariate statistical analysis was applie
d to select the most significant wavelengths from the chicken heart reflect
ance spectra. By optimizing the selection of wavelengths of interest for di
fferent poultry diseases, four wavelengths were selected (495, 535, 585, an
d 605 nm). The multi-spectral imaging system utilizes four narrow-band filt
ers to provide four spectrally discrete images on a single CCD focal-plane.
Using the filters at the wavelengths selected from the reflectance spectra
, it was possible to easily implement multi-spectral arithmetic operations
for disease detection. Based on analysis (t-test) of spectral image data, t
he multi-spectral imaging method could potentially differentiate individual
diseases in chicken hearts in real time. All conditions except cadaver wer
e shown to be separable (92-100%) by discriminant algorithms involving diff
erences of average image intensities.