Logistic regression model for predicting microbial growth and antibiotic resistance occurrence in swiftlet (Aerodramus fuciphagus) faeces
2021
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 (11.86±3.11 log10 cfu/ g) were collected from
Kota Samarahan in Sarawak, Malaysia, and the lowest (6.71±1.09 log10 cfu/g) from Sibu in
both rainy and dry season from March 2016 till September 2017. FB isolates were highly
resistant against penicillin G (42.20±18.35%). Enterobacter and Enterococcal bacteria
were resistant to streptomycin (40.00±51.64%) and vancomycin (77.50±41.58%). The
model indicated that the bacteria could grow well under conditions of higher faecal acidity
(pH 8.27), dry season, higher mean daily temperature (33.83°C) and faecal moisture content
(41.24%) of swiftlet houses built in an urban area with significant regression (P<0.0005,
N=100). 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.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
22
References
0
Citations
NaN
KQI