Image Analysis as a Rapid Pathogen Detection Method for Use in Poultry Industry

Singh, Neha; Slavik, Michael F.; Wang, X.; Li, Y.

doi:10.1111/j.1745-4581.1997.tb00163.x

Cited by 3 publications

(4 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…No positive correlation and significant variation of TSC was found in three different hall and in differed broiler carcass .This signifies the fact that all these meats are more or less handled in the same manner. The findings are also closely related to the findings of several other researchers (Mead et al1994, Boonmar et al 1998and Singh et al 1997. The variation of TVC in meats of three dining hall was significant (P<0.05) at 5% level of probability as shown in Table 2.…”

Section: Resultssupporting

confidence: 90%

Assessment of bacterial load of poultry meat used at dining hall of Bangladesh Agricultural University campus

Hossain

Hoda

Hossen

et al. 2015

Asian J. Med. Biol. Res

View full text Add to dashboard Cite

The present study was undertaken to investigate the microbiological quality of poultry meat used in different hall of Bangladesh Agricultural University campus. Sanitary condition of dining hall was assessed by using a standard questionnaire. Thirty samples were collected from Isha Khan hall, Fazlul Haque hall and Taposhi Rabeya hall. Microbial load was determined by total viable count (TVC), total coliform count (TCC) and total salmonella count (TSC). Samples were inoculated into various selective media such as plate count (PCA) agar, xylose lysine deoxycholate Agar (XLDA) and MacConkey agar (MCA). It is found that the age of maximum workers (53%) is between 25-35 years. Educational level of dining workers are in same frequency of illiterate and below class eight. Only 6.7% are SSC passed. Most of dining workers have no knowledge on hygienic practices. 43.3% partially know about hygienic practices and 3.3% have no knowledge. Sanitary condition of dining hall is not satisfactory. Only 3.3% disinfectants are used in dining hall. There is no proper washing facilities. About 63.3% washing facilities are in medium level. Only E. coli and Salmonella spp. were isolated and identified from the samples. The mean value of TVC, TCC and TSC in broiler thigh meats of Isha Khan hall, Fazlul Haque hall and Taposhi Rabeya hall are log 5.65, log 5.77, log 6.06 CFU/g, log 3.26, 3.41, 3.42 CFU/g and log 2.95, log 2.92 log 2.97 CFU/g respectively. The variation of TVC in meats of different dining hall was significant (p<0.05) at 5% level of probability whereas TCC and TSC obtained from meat samples of different hall were not significant (p<0.05). Presence of Escherichia coli and Salmonella spp. in meat must need particular attention as these organisms are responsible for causing harm to public health. Suggestions have been given to improve the present sanitary condition of dining hall to minimize bacterial load.Asian J. Med. Biol. Res. June 2015, 1(1): 9-16

show abstract

Section: Resultssupporting

confidence: 90%

Assessment of bacterial load of poultry meat used at dining hall of Bangladesh Agricultural University campus

Hossain

Hoda

Hossen

et al. 2015

Asian J. Med. Biol. Res

View full text Add to dashboard Cite

show abstract

“…The bacteriologist spent an average of 1 min to analyze each image manually for a total of 1 h and 40 min. Comparing with other reported investigations (Singh et al 1997 andHuang et al 1999) the time needed by our system is approximately 40 min less because they did not take advantages of the implementation of a multiplane focus scanning. However, the system speed could be improved if a faster computer were used.…”

Section: Multi-plane Focus Performancementioning

confidence: 70%

A MACHINE VISION SYSTEM USING IMMUNO‐FLUORESCENCE MICROSCOPY FOR RAPID RECOGNITION OF SALMONELLA TYPHIMURIUM

Trujillo

Griffis

Li³

et al. 2001

Rapid Methods Automation Mic

Self Cite

View full text Add to dashboard Cite

The objective of this research was to develop an automated system using image processing and statistical modeling techniques to identify and enumerate bacteria on slides containing Salmonella typhimurium. Pictures of bacterial cells were acquired with a CCD camera attached to a motorized fluorescence microscope. A shape boundary modeling technique, based on the use of circular autoregressive model parameters, was used. A minimum‐distance classifier was trained with ten images belonging to each shape class (rod shape and circle shape). Experimental results showed that the model parameters could be used as descriptors of shape boundaries detected in digitized binary images of bacterial cells. In spite of the advantages of human vision, the differences between the computer and a bacteriologist in recognizing and counting of Salmonella cells were less than 8%. The computer analyzed each image in approximately 5 s (a total of 2 h including sample preparation), while the bacteriologist spent an average of 1 min for each image.

show abstract

“…The image processing steps are shown in Figure 6 (Huang et al 1999, Singh et al 1997. The red color channel was extracted to boost the red values in the RGB image.…”

Section: The Image Processing Of the Area Distribution Methodsmentioning

confidence: 99%

“…Image processing was performed using Image Pro-Plus 3.0 (Media Cybernetics 1997) (Cybernetics, Silver Spring, Md., USA). The image processing steps are shown in Figure 6 (Huang et al 1999, Singh et al 1997. The red color channel was extracted to boost the red values in the RGB image.…”

Section: The Image Processing Of the Area Distribution Methodsmentioning

confidence: 99%

Image analysis of particle dispersions in microscopy images of cryo‐sectioned sausages

Köhler¹,

Høst²,

Ofstad³

2001

Scanning

View full text Add to dashboard Cite

Summary:Two feature extraction methods, the threedimensional (3-D) local box-counting method and the area distribution method, are presented to describe the fat dispersion pattern on digital microscopy images of cryo-sectioned sausages. Both methods calculate whole arrays of variables for each microscopy image. The 3-D box-counting method calculates scale dependent (local) dimensions. This is in contrast to common fractal methods, which are univariate. Principal component analysis (PCA) was used to show that different sausages yield different fat dispersion patterns. Partial least square regression (PLS) shows that there is a correlation between the variables gained with both methods and the fat content.

show abstract

Image Analysis as a Rapid Pathogen Detection Method for Use in Poultry Industry

Cited by 3 publications

References 8 publications

Assessment of bacterial load of poultry meat used at dining hall of Bangladesh Agricultural University campus

Assessment of bacterial load of poultry meat used at dining hall of Bangladesh Agricultural University campus

A MACHINE VISION SYSTEM USING IMMUNO‐FLUORESCENCE MICROSCOPY FOR RAPID RECOGNITION OF SALMONELLA TYPHIMURIUM

Image analysis of particle dispersions in microscopy images of cryo‐sectioned sausages

Contact Info

Product

Resources

About