Are Growth Performance and Fecal Score in Weaning Pigs Affected by the Inclusion Level of Potato Protein Concentrate and the Enclosed Glycoalkaloids in Iso-Nitrogenous Diets?

Glycoalkaloids (GA) are anti-nutritional factors in standard potato protein concentrate (PPC) fed to piglets. Increasing levels of standard PPC was expected to affect growth performance and fecal score negatively. Seven-hundred-and-twenty pigs (7-30 kg) were fed one of the following four diets within three feeding phases (days 0-13, 13-24, and 24-45): control (CTRL), PPC standard inclusion (PPC-S; 4%, 2%, and 0%), high PPC inclusion (PPC-H; 8%, 3.5%, and 2%), and extremely high PPC inclusion (PPC-EH; 12%, 5%, and 3.5%). During days 0-13, CTRL displayed no difference in growth performance compared with the three experimental groups (PPC-S, PPC-H, and PPC-EH). During days 13-24, PPC-H achieved greater (p < 0.001) average daily feed intake (ADFI) compared to CTRL. During days 24-45, no differences between groups were observed. For the overall experimental period (0-45 days), PPC-H displayed greater average daily gain (ADG) (p = 0.010) and ADFI (p = 0.024) compared to CTRL. The feed conversion ratio (FCR) remained unaffected between the groups for all experimental periods. Increasing levels of PPC and hence GA did not affect the probability of diarrhea. In conclusion, increased standard PPC and hence increased levels of GA in isonitrogenous diets did not negatively affect growth performance nor fecal score in piglets (7-30 kg).

Using state space models to monitor and estimate the effects of interventions on treatment risk and milk yield in dairy farms.

Fast, flexible, and internally valid analytical tools are needed to evaluate the effects of management interventions made on dairy farms to support decisions about which interventions to continue or discontinue. The objective of this observational study was to demonstrate the use of state space models (SSM) to monitor and estimate the effect of interventions on 2 specific outcomes: a dynamic linear model (DLM) evaluating herd-level milk yield and a dynamic generalized linear model evaluating treatment risk in a pragmatic pretest/posttest design under field conditions. This demonstration study is part of a Danish common learning project that ran from March 2020 to May 2021 within the framework of veterinary herd health consultancy in relation to reducing antimicrobial use and improving herd health. Specific interventions for 2 commercial herds were suggested by 4 visiting farmers and were implemented during the project period. The intervention for herd 1 was the application of teat sealers, implemented in August 2020. For herd 2, the intervention was an adjustment of cubicles for cows of parity 2 and above, implemented from November 2020. A shift to an automatic milking system in October 2020 was also modeled as an intervention for herd 1 because the 2 interventions coincided. Data available from the Danish Cattle Database on obligatory registrations for individual cow movements and treatments, as well as test day information on milk yield, were used for model building and testing. Data from a 3-yr period before the project were used to calibrate the SSM to herd conditions, and data from the study period (March 2020 to May 2021) were used for monitoring and intervention testing based on application of the SSM. Herd bulk tank milk recordings were added to the data set during the study period to increase the precision of the estimates in the DLM. The developed SSM monitored herd-level milk yield and the overall probability of treatment throughout the study period in both herds. Furthermore, at the time of intervention, the SSM estimated the effect on herd-level milk yield and treatment risk associated with the implemented intervention in each herd. The SSM were used because they can be calibrated to herd conditions and they take into account herd dynamics and autocorrelation and provide standard deviations of estimates. For herd 1, the intervention effect of applying teat sealers was inconclusive with the current SSM application. For herd 2, no statistically significant changes in cow treatment risk or milk production were identified following the adjustment of cubicles. The use of SSM on observational data under field conditions shows that in this case, the interventions had a nonspecific onset of effect, were implemented during unstable times, and had varying coherence with the measured outcomes, making fully automated SSM analysis difficult. However, similar or expanded SSM with both monitoring and effect estimation functions could, if applied under the right conditions, serve as improved data-based decision support tools for farmers (and veterinarians) to minimize the risk of misinterpreting data due to confounding bias related to dynamics in dairy herds.

Identifying Risk Factors for Low Piglet Birth Weight, High Within-Litter Variation and Occurrence of Intrauterine Growth-Restricted Piglets in Hyperprolific Sows.

This study aimed to identify risk factors affecting PBW, high CVPBW and the occurrence of IUGR piglets in 12 commercial Danish herds with hyperprolific sows using free-access stalls, floor or electronic sow feeding systems in the gestation unit. The following factors were investigated: the duration of previous lactation, the length of the interval from weaning to insemination, the length of gestation, litter size, parity, sow backfat thickness in late gestation and the type of feeding system in the gestation unit. The study included newborn piglets from 452 litters with the following production indicator averages: 21.3 piglets/L, 1235 g PBW, 22.9% CVPBW and 10.9% and 11.8% within-litter occurrence of severe and mild IUGR piglets, respectively. Increasing length of weaning-to-insemination interval decreased PBW by 25.8 g/day. For 2nd to 9th parity sows, each additional piglet in the litter increased CVPBW by 0.38%, the occurrence of severe IUGR piglets by 0.68% and mild IUGR piglets by 0.50%. Sows of 5th parity and older had a 1.39% higher CVPBW and 49.1 g lighter piglets compared with sows of 2nd to 4th parity. PBW was lower in one ESF herd, suggesting complex interactions that need to be further elucidated. The main critical risk factor observed was litter size.

The Effect of Different Feeding Systems on Salivary Cortisol Levels during Gestation in Sows on Herd Level.

The aim of this study was to investigate herd cortisol levels as an indicator of stress during gestation in three different feeding systems. Twelve commercial Danish herds with 800 to 3050 sows were included, with either free-access feeding stall (Stall), floor feeding (Floor), or electronic sow feeding (ESF; n = 4 herds per system). Saliva samples were collected from 30 sows/herd in the gestation unit for cortisol analysis with an average of 67.2 gestation days for ESF, 72.4 days for Floor, and 68.6 days for Stall. Data on piglet birth weight (PBW) and the percentage of intrauterine growth restricted (IUGR) piglets from 452 litters (9652 piglets, 8677 liveborn) from all 12 herds were obtained on the saliva collection days. The cortisol levels in saliva increased throughout gestation (p < 0.01), and lower concentrations were observed among sows belonging to Stall (4.80 nmol/L), compared to Floor (7.03 nmol/L) and ESF (7.87 nmol/L), and that difference was significant as an independent effect in the case of ESF (p < 0.01). There was no difference between Floor and ESF or Stall and Floor (p > 0.05). An interaction was observed between parity and feeding system, with parities 4-5 in ESF herds having lower levels than other parities within the ESF system (p = 0.02).

Combining Salmonella Dublin genome information and contact-tracing to substantiate a new approach for improved detection of infectious transmission routes in cattle populations.

This study presents a new method for detection of between-herd livestock movements to facilitate disease tracing and more accurately describe network behaviour of relevance for spread of infectious diseases, including within-livestock business risk-carrying contacts that are not necessarily recorded anywhere. The study introduces and substantiates the concept of grouping livestock herds into business-units based on ownership and location in the tracing analysis of animal movement-based contact networks. To test the utility of this approach, whole core genome sequencing of 196 Salmonella Dublin isolates stored from previous surveillance and project activities was combined with information on cattle movements recorded in the Danish Cattle Database between 1997 and 2017. The aim was to investigate alternative explanations for S. Dublin circulation in groups of herds connected by ownership, but without complete records of livestock movements. The EpiContactTrace R-package was used to trace the contact networks between businesses and compare the network characteristics of businesses sharing strains of S. Dublin with different levels of genetic relatedness. The ownership-only definition proved to be an unreliable grouping approach for large businesses, which could have internal distances larger than 250 km and therefore do not represent useful epidemiological units. Therefore, the grouping was refined using spatial analysis. More than 90% of final business units formed were composed of one single cattle property, whereas multi-property businesses could reach up to eight properties in a given year, with up to 15 cattle herds having been part of the same business through the study period. Results showed markedly higher probabilities of introduction of infectious animals between proposed businesses from which the same clone of S. Dublin had been isolated, when compared to businesses with non-related strains, thus substantiating the business-unit as an important epidemiological feature to consider in contact network analysis and tracing of infection routes. However, this approach may overestimate real-life contacts between cattle properties and putatively overestimate the degree of risk-contacts within each business, since it is based solely on information about property ownership and location. This does not consider administrative and individual farmers behaviours that essentially keep two properties separated. Despite this, we conclude that defining epidemiological units based on businesses is a promising approach for future disease tracing tasks.

Epidemiology of Salmonella enterica Serovar Dublin in Cattle and Humans in Denmark, 1996 to 2016: a Retrospective Whole-Genome-Based Study.

Salmonella enterica serovar Dublin is a cattle-adapted S. enterica serovar causing both intestinal and systemic infection in its bovine host, and it is also a serious threat to human health. The present study aimed to determine the population structure of S Dublin isolates obtained from Danish cattle herds and to investigate how cattle isolates relate to Danish human isolates, as well as to non-Danish human and bovine isolates. Phylogenetic analysis of 197 Danish cattle isolates from 1996 to 2016 identified three major clades corresponding to distinct geographical regions of cattle herds. Persistence of closely related isolates within the same herd and their circulation between epidemiologically linked herds for a period of more than 20 years were demonstrated. These findings suggest that a lack of internal biosecurity and, to some extent, also a lack of external biosecurity in the herds have played an important role in the long-term persistence of S Dublin in Danish cattle herds in the period investigated. Global population analysis revealed that Danish cattle isolates clustered separately from bovine isolates from other countries, whereas human isolates were geographically spread. Resistance genes were not commonly demonstrated in Danish bovine isolates; only the isolates within one Danish clade were found to often harbor two plasmids of IncFII/IncFIB and IncN types, the latter plasmid carrying blaTEM-1, tetA, strA, and strB antibiotic resistance genes.IMPORTANCES Dublin causes economic losses in cattle production, and the bacterium is a public health concern. A surveillance and control program has been in place in Denmark since 2002 with the ultimate goal to eradicate S Dublin from Danish cattle herds; however, a small proportion of herds have remained positive for many years. In this study, we demonstrate that herds with persistent infection often were infected with the same strain for many years, indicating that internal biosecurity has to be improved to curb the infection. Further, domestic cases of S Dublin infection in humans were found to be caused both by Danish cattle isolates and by isolates acquired abroad. This study shows the strength of whole-genome sequencing to obtain detailed information on epidemiology of S Dublin and allows us to suggest internal biosecurity as a main way to control this bacterium in Danish cattle herds.

A sampling and metagenomic sequencing-based methodology for monitoring antimicrobial resistance in swine herds.

OBJECTIVES: Reliable methods for monitoring antimicrobial resistance (AMR) in livestock and other reservoirs are essential to understand the trends, transmission and importance of agricultural resistance. Quantification of AMR is mostly done using culture-based techniques, but metagenomic read mapping shows promise for quantitative resistance monitoring. METHODS: We evaluated the ability of: (i) MIC determination for Escherichia coli; (ii) cfu counting of E. coli; (iii) cfu counting of aerobic bacteria; and (iv) metagenomic shotgun sequencing to predict expected tetracycline resistance based on known antimicrobial consumption in 10 Danish integrated slaughter pig herds. In addition, we evaluated whether fresh or manure floor samples constitute suitable proxies for intestinal sampling, using cfu counting, qPCR and metagenomic shotgun sequencing. RESULTS: Metagenomic read-mapping outperformed cultivation-based techniques in terms of predicting expected tetracycline resistance based on antimicrobial consumption. Our metagenomic approach had sufficient resolution to detect antimicrobial-induced changes to individual resistance gene abundances. Pen floor manure samples were found to represent rectal samples well when analysed using metagenomics, as they contain the same DNA with the exception of a few contaminating taxa that proliferate in the extraintestinal environment. CONCLUSIONS: We present a workflow, from sampling to interpretation, showing how resistance monitoring can be carried out in swine herds using a metagenomic approach. We propose metagenomic sequencing should be part of routine livestock resistance monitoring programmes and potentially of integrated One Health monitoring in all reservoirs.

Application of Molecular Typing Results in Source Attribution Models: The Case of Multiple Locus Variable Number Tandem Repeat Analysis (MLVA) of Salmonella Isolates Obtained from Integrated Surveillance in Denmark.

Salmonella is an important cause of bacterial foodborne infections in Denmark. To identify the main animal-food sources of human salmonellosis, risk managers have relied on a routine application of a microbial subtyping-based source attribution model since 1995. In 2013, multiple locus variable number tandem repeat analysis (MLVA) substituted phage typing as the subtyping method for surveillance of S. Enteritidis and S. Typhimurium isolated from animals, food, and humans in Denmark. The purpose of this study was to develop a modeling approach applying a combination of serovars, MLVA types, and antibiotic resistance profiles for the Salmonella source attribution, and assess the utility of the results for the food safety decisionmakers. Full and simplified MLVA schemes from surveillance data were tested, and model fit and consistency of results were assessed using statistical measures. We conclude that loci schemes STTR5/STTR10/STTR3 for S. Typhimurium and SE9/SE5/SE2/SE1/SE3 for S. Enteritidis can be used in microbial subtyping-based source attribution models. Based on the results, we discuss that an adjustment of the discriminatory level of the subtyping method applied often will be required to fit the purpose of the study and the available data. The issues discussed are also considered highly relevant when applying, e.g., extended multi-locus sequence typing or next-generation sequencing techniques.

No Clear Effect of Initiating Vaccination against Common Endemic Infections on the Amounts of Prescribed Antimicrobials for Danish Weaner and Finishing Pigs during 2007-2013.

It is often stated that vaccines may help reduce antimicrobial use in swine production. However, limited evidence is available outside clinical trials. We studied the change in amounts of antimicrobials prescribed for weaners and finishers in herds following initiation of vaccination against five common endemic infections: Mycoplasma hyopneumoniae, Actinobacillus pleuropneumoniae, porcine circovirus type II, porcine reproductive and respiratory syndrome virus, and Lawsonia intracellularis. Comparison was made to the change after a randomly selected date in herds not vaccinating against each of the infections. Danish sow herds initiating vaccination during 2007-2013 were included (69-334 herds, depending on the analysis). Danish sow herds with no use of the vaccine in question were included as non-exposed herds (130-570 herds, depending on the analysis). Antimicrobial prescriptions for weaners in sow herds and for finishers in receiving herds were extracted from the VetStat database for a period of 12 months before and 6-18 months after the first purchase of vaccine, or random date and quantified as average animal daily doses (ADDs) per 100 animals per day. The herd-level difference between ADD in the period after and before vaccination was the outcome in linear regression models for weaner pigs, and linear mixed-effects models for finishing pigs, taking into account sow herds delivering pigs to two or more finisher herds. Three plausible risk factors (Baseline ADD, purchase of specific vaccine, purchase of other vaccines) and five confounders (herd size, export and herd health status, year and season) were initially considered in all 10 models. The main significant effect in all models was the Baseline ADD; the higher the Baseline ADD was for weaner and finishing pigs, the larger the decrease in ADD was following vaccination (or random date for non-vaccinating herds). Regardless of vaccination status, almost equal proportions of herds experienced a decrease and an increase in ADD resulting in no overall Change in ADD. Furthermore, only minor effects were found, when vaccinations were used in combination. In conclusion, this study provided little support for the hypothesis that vaccination against five common endemic diseases provides a plausible general strategy to reduce antimicrobial use in Danish pig herds.

The impact of screening-test negative samples not enumerated by MPN.

In microbiological surveys, false negative results in detection tests precluding the enumeration by MPN may occur. The objective of this study was to illustrate the impact of screening test failure on the probability distribution of Salmonella concentrations in pork using a Bayesian method. A total of 276 swab samples in four slaughter steps (69 samples in each slaughter step: after dehairing, after singeing, after evisceration, and before chilling) were screened for Salmonella and enumerated by the MPN method. Salmonella contamination data were fitted to a lognormal distribution by using a Bayesian model that uses the number of positive tubes at each dilution in an MPN analysis to estimate the parameters of the concentration distribution. With Salmonella paired data, three data sets were used for each slaughter step: one that includes the positives in the screening test only, a second one that includes false negative results from the screening, and a third that considers the entire data set. The relative sensitivity of the screening test was also calculated assuming as gold standard samples with confirmed Salmonella. Salmonella was confirmed by a reference laboratory in 29 samples either by screening or MPN method. The relative sensitivity of the screening test was 69% (CI 95%: 52%-85%). The data set that included enumerations from screen-negative samples (false negative results) tended to have higher µÌ‚ and smaller σ̂ in comparison with the data set that discards false negative results, suggesting that the lack of sensitivity of the screening test affects the distribution that describes the contamination across the population. Numerous surveys on fitting distribution methods of microbial censored data have been published and discuss source of bias due to fitting method. Results of this survey contribute with that discussion by illustrating another possible source of bias due to failure of the screening methods preceding the MPN.