Current applications of machine vision in agriculture are briefly reviewed. The requirements and recent developments of hardware and software for machine vision systems are discussed, with emphases on multispectral and hyperspectral imaging for modern food inspection. Examples of applications for detection of disease, defects, and contamination on poultry carcasses and apples are also given. Future trends of machine vision technology applications are discussed. #

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Surface-enhanced Raman (SERS) spectra of various batches of bacteria adsorbed on silver colloidal nanoparticles were collected to explore the potential of the SERS technique for rapid and routine identification of E. coli and L. monocytogenes cultures. Relative standard deviation (RSD) of SERS spectra from silver colloidal suspensions and ratios of SERS peaks from small molecules (K(3)PO(4)) were used to evaluate the reproducibility, stability, and binding effectiveness of citrate-reduced silver colloids over batch and storage processes. The results suggested consistent reproducibility of silver colloids over batch process and also stability and consistent binding effectiveness over an eight-week storage period. A variety of mixtures of E. coli/L. monocytogenes cultures with different colloidal batches revealed that, despite large variations in relative intensities and positions of SERS active bands, characteristic and unique bands at 712 and 390 cm(-1) were consistently observed and were the strongest in E. coli and L. monocytogenes cultures, respectively. Two specific bands were used to develop simple algorithms in the evaluation of binding effectiveness of silver colloids over storage and further to identify E. coli and L. monocytogenes cultures with a 100% success. A single spectrum acquisition took 5 approximately 6 min, and a minimum of 25 microL silver colloid was directly mixed with 25 microL volume of incubated bacterial culture. The short acquisition time and small volume of incubated bacterial culture make silver colloidal nanoparticle based SERS spectroscopy ideal for potential use in the routine and rapid screening of E. coli and L. monocytogenes cultures on large scales. This is the first report of the development of simple and universal algorithms for bacterial identification from the respective exclusive SERS peaks.