Species Identification, Automated

A variety of commercial kits and automated systems are available to test the abilities of bacteria to assimilate, ferment, decarboxylate, or cleave selected organic compounds.46 Their reliability for species identification is usually greater with cultures from clinical samples, where a limited number of bacteria are commonly encountered, and less with environmental soil and water samples, where a great many uncommon or previously unidentified species not in the database are likely to be present.29,45 Additional tests beyond those found in the commercial kits may be necessary for example, the hydrolysis of various nitriles and amides is useful for identifying Rhodococcus spp.47 Some commercial kits for clinical use feature antimicrobial susceptibility testing.21... 

A data file is generated for ail ions with precursors of m/z 85 within a mass range of m/z 250 to m/z 500. Profiling of acylcarnitines as [M-l-H] molecular ions allows identification, automated calculation of quantitative and semiquanti-tative concentrations for each acylcarnitine species against the internal standards, and comparison with age-appropriate reference intervals. 

The need for high-throughput screening methods of human mutations has stimulated the development of CE-based methods for SSCP analysis. For detection of ssDNA, PCR is carried out with primers labeled at the 5 site with fluorescence dyes. Two different labels may be used for identification of the forward and reverse strands. Advantages of CE-SSCP are speed of electrophoresis (ca. 10 min), high sensitivity, reproducibility, and the possibility of automation (Andersen et al., 2003 Hestekin et al., 2006). In food analysis, CE-SSCP has been used to identify bacteria (see Section 5.4.4) but, to the knowledge of the author, not to species identification of meat, fish, or other food up to now. 

Gaston, K.J. and O Neill, M.A. (2004) Automated species identification Why not Philosophical Transactions of the Royal Society of London, Series B, 359 655-667. 

Automated taxon identification (ATI) (originally designated automated species identification). 

Chesmore, E. D., Swarbrick, M.D. and Eemminella, O.P. (1997) Automated analysis of insect sounds using TESPAR and expert systems - A new method for species identification. In Information Technology, Plant Pathology and Biodiversity (eds P. Bridge et al.), CAB International, Wallingford, UK, pp. 273-287. 

DAISY A Practical Computer-Based Tool for Semi-Automated Species Identification... 

A survey of techniques then being used in allied fields showed that, for fully automated species identification (where the user simply supplies the system with an image of the unknown, presses a button and gets an answer), approaches being developed for the machine identification of human faces provided an ideal initial starting point. 

Enicospilus species are all very similar in appearance. Therefore, it is difficult for nonspecialists to differentiate between them. Enicospilus thus represents a difficult test case for an automated species identification system. 

Automated Extraction and Analysis of Morphological Features for Species Identification... 

The classical approach to species identification is that of qualitative morphological and quantitative morphometric analysis. Thus, taxonomists perform the identification task by visual observation and measurement of morphological and morphometric features (i.e. the colour of feathers, the shape of wings, the distance between the eyes, the angle between two veins). A natural way to automate the traditional taxonomic ways of species identification by visual observation and measurement is to employ methods of image analysis. Furthermore, since taxonomic descriptions rely on morphological and morphometric features, a feature-based approach seems appropriate. 

An interesting development is the combination of HPLC and on-line measurement of reducing capacity or antioxidative activity. This approach allows both direct identification of antioxidative species in complex foods and quantification of the contribution to the overall antioxidative capacity in the absence of synergistic and antagonistic effects. Major advantages are less sample handling and the ability to rim large series of samples in an automated process. 

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