Logistic regression model for predicting microbial growth and antibiotic resistance occurrence in swiftlet (Aerodramus Fuciphagus) faeces

Leong Sui Sien, . and Lihan Samuel, . and Ling Teck Yee, . and Chia Hwa Chuan, . Logistic regression model for predicting microbial growth and antibiotic resistance occurrence in swiftlet (Aerodramus Fuciphagus) faeces. pp. 113-123. ISSN 2672-7226

This study proposes a logistic model of the environmental factors which may affect bacterial growth and antibiotic resistance in the swiftlet industry. The highest total mean faecal bacterial (FB) colonies counts (11.863.11 log‚�‚ cfu/ g) were collected from Kota Samarahan in Sarawak Malaysia and the lowest (6.711.09 log‚�‚ cfu/g) from Sibu in both rainy and dry season from March 2016 till September 2017. FB isolates were highly resistant against penicillin G (42.2018.35). Enterobacter and Enterococcal bacteria were resistant to streptomycin (40.0051.64) and vancomycin (77.5041.58). The model indicated that the bacteria could grow well under conditions of higher faecal acidity (pH 8.27) dry season higher mean daily temperature (33.83C) and faecal moisture content (41.24) of swiftlet houses built in an urban area with significant regression (P0.0005 N100). The probability of the development of antibiotic resistance () increased 0.50 times if the faecal acidity increased by one unit with significant contribution to the prediction (P 0.012). Understanding how these microbial species react to environmental parameters according to this model allowed us to estimate their interaction outcomes and growth especially in an urban environment which may pose a health hazard to people.

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Abstract

This study proposes a logistic model of the environmental factors which may affect bacterial growth and antibiotic resistance in the swiftlet industry. The highest total mean faecal bacterial (FB) colonies counts (11.863.11 log‚�‚ cfu/ g) were collected from Kota Samarahan in Sarawak Malaysia and the lowest (6.711.09 log‚�‚ cfu/g) from Sibu in both rainy and dry season from March 2016 till September 2017. FB isolates were highly resistant against penicillin G (42.2018.35). Enterobacter and Enterococcal bacteria were resistant to streptomycin (40.0051.64) and vancomycin (77.5041.58). The model indicated that the bacteria could grow well under conditions of higher faecal acidity (pH 8.27) dry season higher mean daily temperature (33.83C) and faecal moisture content (41.24) of swiftlet houses built in an urban area with significant regression (P0.0005 N100). The probability of the development of antibiotic resistance () increased 0.50 times if the faecal acidity increased by one unit with significant contribution to the prediction (P 0.012). Understanding how these microbial species react to environmental parameters according to this model allowed us to estimate their interaction outcomes and growth especially in an urban environment which may pose a health hazard to people.

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Item Type:	Article
AGROVOC Term:	Swifts
AGROVOC Term:	Birds
AGROVOC Term:	Regression analysis
AGROVOC Term:	Faeces
AGROVOC Term:	Antibiotic resistance
AGROVOC Term:	Microbial culture
AGROVOC Term:	Disease occurrence
AGROVOC Term:	Environmental factors
AGROVOC Term:	Prediction
AGROVOC Term:	Urban environment
Depositing User:	Mr. AFANDI ABDUL MALEK
Last Modified:	24 Apr 2025 00:55
URI:	http://webagris.upm.edu.my/id/eprint/9964

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