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<OL> <LI> Compare goat meat samples with different bacterial concentrations, fat/moisture contents, and sequential growth times to distinguish between E. coli and non-E. coli cultures using an electronic nose. <LI> To determine the lowest concentration level(s) at which the sensors can distinguish between E. coli and non-E. coli cultures in a medium. <LI> Develop artificial networks to classify data from electronic nose in order to distinguish between E. coli cultures and non-E. coli cultures on surface of goat meat.
NON-TECHNICAL SUMMARY: This research will be done to develop an electronic nose method for rapid detection of E. coli cultures on goat meat surfaces.
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APPROACH: Methods of detection of food-borne pathogens, such as E. coli cultures, are still laborious. It takes one to five days to get conformation and it is not feasible for food plants. The overall goal of this project is to develop an electronic nose method for rapid detection of E. coli cultures on goat meat surfaces. If we can confirm that the method works, we will then try to implement this method to detect bacteria with other meat such as beef, pork, and chicken.
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PROGRESS: 2004/01 TO 2004/12<BR>
Further tests have been done for goat meat with E. coli bacteria. Our experiments indicate that the e-nose can detect bacteria but not with 100% accuracy. Since there are a lot of factors affecting the results more experiments need to be done before the accuracy can be predicted. It seems that the e-nose is not able to detect very low concentration of the contaminant. However, 100% identification could not be obtained consistently even with higher concentration or density. The results from the experiments indicated that e-nose has a potential for being used as a tool for rapid detection of contamination, however more experiments need to be done before any conclusion can be drawn
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IMPACT: 2004/01 TO 2004/12<BR>
The impact of the research findings would be of enormous importance and influence on the rapid detection of E. coli on goat meat surfaces. The technology thus generated could be used for the HACCP program in the meat industries.
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PROGRESS: 2003/01/01 TO 2003/12/31<BR>
Goat meat was obtained from the goat meat center at Fort Valley State University (FVSU), goat meat research center. E. coli was grown overnight at 37 degrees C with continuous shaking in a125 ml flask. The optical density (O.D) of this culture was adjusted to give a concentration of about 108 cfu/ml (colony forming units per ml). This culture was used to inoculate the meat pieces. The e-nose was trained with two classes, class 1 was meat with no bacteria (good) and class2 was meat inoculated with bacteria (bad). 6 to 7 exposures were used to get a cross validation of 91 -100%. Meat pieces of about 2x3 cm was prepared and placed in jars of 50ml volume. These were then inoculated with 300ìl of the bacterial culture, covered with parafilm to make it air tight and left at room temperature for 2-4 hours to collect the gas produced by the bacteria. The head space thus generated was then sniffed using trained e-nose (Cyranose-320) to detect the presence of the bacteria. Our experiments indicate that the e-nose can detect bacteria but not with 100% accuracy. The correct identification varied from 18 to 77 % in different batches with 300 ìl of the culture and 2 h head space accumulation time. The increase in time to 3 and 4 h did not yield much difference in the results. However, the e-nose once trained could be used for identification without updating the training set for at least 2 weeks. The results from the experiments indicated that e-nose has a potential for being used as a tool for rapid detection of contamination, however more experiments need to be done before any conclusion can be drawn. Since there are a lot of factors affecting the results more experiments need to be done before the accuracy can be predicted. It seems that the e-nose is not able to detect very low concentration of the contaminant. However, 100% identification could not be obtained consistently even with higher concentration or density.
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IMPACT: 2003/01/01 TO 2003/12/31<BR>
The impact of the research findings would be of enormous importance and influence on the rapid detection of E. coli on goat meat surfaces. The technology thus generated could be used for the HACCP program in the meat industries.
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PROGRESS: 2002/01/01 TO 2002/12/31<BR>
A Cyanose 320 was used to rapidly detect pathogenic bacteria in chicken carcass and rice sample classification. The Spreeta biosensor was tested for feasibility in rapid detection of bacteria in chicken carcass. The results of this study demonstrated that the SPR biosensor has the potential for rapid and specific pathogen detection. The SPR biosensor is capable of reporting the presence of bacteria in 30 min at levels of 10,000,000 CFU/ml. With further investigation and refinements, there may be more promising uses for electronic nose and biosensor in food safety and control applications such as multisensor data fusion.
<BR> <BR>
IMPACT: 2002/01/01 TO 2002/12/31<BR>
The impact of the research findings would be of enormous importance and influence on the rapid detection of E. coli on goat meat surfaces. The technology thus generated could be used for the HACCP program in the meat industries.