5 resultados para MPN
em eResearch Archive - Queensland Department of Agriculture
Resumo:
Aims: To assist in the development of safe piggery effluent re-use guidelines by determining the level of selected pathogens and indicator organisms in the effluent ponds of 13 south-east Queensland piggeries. Methods and Results: The numbers of thermotolerant coliforms, Campylobacter jejuni/coli, Erysipelothrix rhusiopathiae, Escherichia coli, Salmonella and rotavirus were determined in 29 samples derived from the 13 piggeries. The study demonstrated that the 13 final effluent ponds contained an average of 1Æ2 · 105 colony-forming units (CFU) 100 ml)1 of thermotolerant coliforms and 1Æ03 · 105 CFU 100 ml)1 of E. coli. The Campylobacter level varied from none detectable (two of 13 piggeries) to a maximum of 930 most probable number (MPN) 100 ml)1 (two of 13 piggeries). Salmonella was detected in the final ponds of only four of the 13 piggeries and then only at a low level (highest level being 51 MPN 100 ml)1). No rotavirus and no Erysip. rhusiopathiae were detected. The average log10 reductions across the ponding systems to the final irrigation pond were 1Æ77 for thermotolerant coliforms, 1Æ71 for E. coli and 1Æ04 for Campylobacter. Conclusions: This study has provided a baseline knowledge on the levels of indicator organisms and selected pathogens in piggery effluent. Significance and Impact of the Study: The knowledge gained in this study will assist in the development of guidelines to ensure the safe and sustainable re-use of piggery effluent.
Resumo:
Aims: To investigate the occurrence and levels of Arcobacter spp. in pig effluent ponds and effluent-treated soil. Methods and Results: A Most Probable Number (MPN) method was developed to assess the levels of Arcobacter spp. in seven pig effluent ponds and six effluent-treated soils, immediately after effluent irrigation. Arcobacter spp. levels in the effluent ponds varied from 6.5 × 105 to 1.1 × 108 MPN 100 ml-1 and in freshly irrigated soils from 9.5 × 102 to 2.8 × 104 MPN g-1 in all piggery environments tested. Eighty-three Arcobacter isolates were subjected to an abbreviated phenotypic test scheme and examined using a multiplex polymerase chain reaction (PCR). The PCR identified 35% of these isolates as Arcobacter butzleri, 49% as Arcobacter cryaerophilus while 16% gave no band. All 13 nonreactive isolates were subjected to partial 16S rDNA sequencing and showed a high similarity (>99%) to Arcobacter cibarius. Conclusions: A. butzleri, A. cryaerophilus and A. cibarius were isolated from both piggery effluent and effluent-irrigated soil, at levels suggestive of good survival in the effluent pond. Significance and Impact of the Study: This is the first study to provide quantitative information on Arcobacter spp. levels in piggery effluent and to associate A. cibarius with pigs and piggery effluent environments.
Resumo:
This study assessed the levels of two key pathogens, Salmonella and Campylobacter, along with the indicator organism Escherichia coli in aerosols within and outside poultry sheds. The study ranged over a 3-year period on four poultry farms and consisted of six trials across the boiler production cycle of around 55 days. Weekly testing of litter and aerosols was carried out through the cycle. A key point that emerged is that the levels of airborne bacteria are linked to the levels of these bacteria in litter. This hypothesis was demonstrated by E. coli. The typical levels of E. coli in litter were similar to 10(8) CFU g(-1) and, as a consequence, were in the range of 10(2) to 10(4) CFU m(-3) in aerosols, both inside and outside the shed. The external levels were always lower than the internal levels. Salmonella was only present intermittently in litter and at lower levels (10(3) to 10(5) most probable number [MPN] g(-1)) and consequently present only intermittently and at low levels in air inside (range of 0.65 to 4.4 MPN m(-3)) and once outside (2.3 MPN m(-3)). The Salmonella serovars isolated in litter were generally also isolated from aerosols and dust, with the Salmonella serovars Chester and Sofia being the dominant serovars across these interfaces. Campylobacter was detected late in the production cycle, in litter at levels of around 107 MPN g(-1). Campylobacter was detected only once inside the shed and then at low levels of 2.2 MPN m(-3). Thus, the public health risk from these organisms in poultry environments via the aerosol pathway is minimal.
Resumo:
1. Litter samples were collected at the end of the production cycle from spread litter in a single shed from each of 28 farms distributed across the three Eastern seaboard States of Australia. 2. The geometric mean for Salmonella was 44 Most Probable Number (MPN)/g for the 20 positive samples. Five samples were between 100 and 1000 MPN/g and one at 105 MPN/g, indicating a range of factors are contributing to these varying loads of this organism in litter. 3. The geometric mean for Campylobacter was 30 MPN/g for the 10 positive samples, with 7 of these samples being 100 MPN/g. The low prevalence and incidence of Campylobacter were possibly due to the rapid die-off of this organism. 4. E. coli values were markedly higher than the two key pathogens (geometric mean 20 x 105 colony forming units (cfu)/g) with overall values being more or less within the same range across all samples in the trial, suggesting a uniform contribution pattern of these organisms in litter. 5. Listeria monocytogenes was absent in all samples and this organism appears not to be an issue in litter. 6. The dominant (70% of the isolates) Salmonella serovar was S. Sofia (a common serovar isolated from chickens in Australia) and was isolated across all regions. Other major serovars were S. Virchow and S. Chester (at 10%) and S. Bovismorbificans and S. Infantis (at 8%) with these serovars demonstrating a spatial distribution across the major regions tested. 7. There is potential to re-use litter in the environment depending on end use and the support of relevant application practices and guidelines.
Resumo:
Limitations in quality bedding material have resulted in the growing need to re-use litter during broiler farming in some countries, which can be of concern from a food-safety perspective. The aim of this study was to compare the Campylobacter levels in ceca and litter across three litter treatments under commercial farming conditions. The litter treatments were (a) the use of new litter after each farming cycle; (b) an Australian partial litter re-use practice; and (c) a full litter re-use practice. The study was carried out on two farms over two years (Farm 1, from 2009–2010 and Farm 2, from 2010–2011), across three sheds (35,000 to 40,000 chickens/shed) on each farm, adopting three different litter treatments across six commercial cycles. A random sampling design was adopted to test litter and ceca for Campylobacter and Escherichia coli, prior to commercial first thin-out and final pick-up. Campylobacter levels varied little across litter practices and farming cycles on each farm and were in the range of log 8.0–9.0 CFU/g in ceca and log 4.0–6.0 MPN/g for litter. Similarly the E. coli in ceca were ∼log 7.0 CFU/g. At first thin-out and final pick-up, the statistical analysis for both litter and ceca showed that the three-way interaction (treatments by farms by times) was highly significant (P < 0.01), indicating that the patterns of Campylobacter emergence/presence across time vary between the farms, cycles and pickups. The emergence and levels of both organisms were not influenced by litter treatments across the six farming cycles on both farms. Either C. jejuni or C. coli could be the dominant species across litter and ceca, and this phenomenon could not be attributed to specific litter treatments. Irrespective of the litter treatments in place, cycle 2 on Farm 2 remained campylobacter-free. These outcomes suggest that litter treatments did not directly influence the time of emergence and levels of Campylobacter and E. coli during commercial farming.