The aim of this study was to evaluate the potential use of microalgae extract (MAE) as a feed ingredient in nursery pig diets.
300 weaned pigs were selected, blocked by initial body weight and allotted to 60 pens, with five pigs per pen. Ratio of gilts and barrows was balanced evenly. Pens within blocks were assigned randomly to one of five dietary treatments.
Dietary treatments included:
corn and soybean meal (CON),
CON with 1% MAE,
CON with 5% MAE,
CON with 10% MAE
CON with 20% MAE.
Diets were formulated to meet the nutrient requirements of nursery pigs and fed using a 3-phase program, where each phase consisted of a 2-wk period.
Average Daily Gain (ADG), Average Daily Feed Intake (ADFI) and Gain to Feed (G:F) were measured weekly.
After 42 days, 30 pigs were harvested and intestinal samples were collected to measure mucosal length and goblet cell quantifications.
Final body weight of pigs among pens consuming MAE was greatest when consuming 1, 5, or 10% MAE compared with those fed the control diet, but feeding 20% MAE was not different from the control diet. The greater final body weight appeared to be the result of greater ADG from days 1 and 7, due to a higher ADFI.
There was no effect of feeding MAE on G:F during most weigh periods except during days 15 to 21 when G:F increased in pigs fed MAE.
Feeding diets with MAE did not result in changes in intestinal architecture measured by the height of the intestinal mucosal or presence of mucus-producing cells in the jejunum. In contrast, the ileum of pigs fed the 5% MAE diet tended to have reduced mucosal height compared with that of pigs fed 20% MAE diet. Goblet cell area of the ileum was not affected by dietary treatments.
Although microalgae can be used as a source of energy and macronutrients in pig diets, there is limited information on the use of partially de-oiled microalgae co-products in swine feeding programs. The objectives of this study were to evaluate the effects of a partially de-oiled microalgae extract (MAE) in nursery pig diets on growth performance and health status. A total of 300 pigs (initial BW = 6.3 ± 2.1 kg) were used in a 42-d experiment. Treatments included a standard corn-soybean meal control diet, and diets containing 1, 5, 10, or 20% MAE replacing primarily corn. The ME content of MAE was calculated from the chemical composition, and diets were formulated to meet or exceed nutrient requirements for nursery pigs. Pigs were stratified by weaning BW into 12 blocks in a randomized complete block design, with sex distributed evenly among blocks. Pens of pigs (5 pigs/pen) were assigned randomly within block to one of 5 dietary treatments. Pig BW and feed disappearance were recorded weekly. On d 42, thirty pigs were harvested and sections of the jejunum and ileum were collected for gut morphology analysis, and a liver sample was collected for metabolomic analysis using liquid chromatography-mass spectroscopy. Data were analyzed by ANOVA with diet as treatment effect, and contrasts were used to test linear or quadratic effects of dietary MAE inclusion level. Overall, pigs fed 1 and 5% MAE had the greatest (quadratic P < 0.05) ADG, resulting from greater (quadratic P < 0.05) ADFI. There was a tendency for a greater number of pigs requiring injectable treatments (P = 0.16) and a greater mortality (P = 0.14) in pigs fed the control diet than pigs in any of the diets with the MAE. Final BW increased (P < 0.05) for pigs fed 1 and 5% MAE diets. The improvements in ADG were not explained by differences in mucosa height or goblet cell count among dietary treatments. Pigs fed diets containing 1 or 5% MAE had relatively less concentration (P < 0.05) of ammonia in the liver and had changes in metabolites associated with the urea cycle. In conclusion, feeding MAE resulted in increased growth responses and may have beneficial health effects when fed to nursery pigs.
A production system’s vulnerability to disease spread can be greatly reduced when selectively identifying a subset of farms as disease control targets.
What was done:
In this study, we used a network approach to describe annual movement patterns between swine farms in three multi-site production systems (1,063 farms) in the United States.
degree: number of farms to which a farm ships or receives pigs
farm’s individual contribution to disease spread via its movements
mean infection potential (MIP), which measures potential incoming and outgoing infection chains
What was found:
Removing farms based on their mean infection potential substantially reduced the potential for transmission of an infectious pathogen through the network when compared to removing farms at random, as shown by a reduction in the magnitude of R0 attributable to contact pattern.
The MIP was more efficient at identifying targets for disease control compared to degree and farm’s contribution to disease spread.
What does this mean?
By targeting disease interventions towards farms based on their mean infection potential, we can substantially reduce the potential for transmission of an infectious pathogen in the contact network, and performed consistently well across production systems.
Fine-scale temporal movement data is important and is necessary for in-depth understanding of the contact structure in developing more efficient disease
Pooling oral fluid samples seems to be a good strategy to determine the status of a farm (positive/negative) for influenza A virus (IAV) and PRRSV.
Sampling water cups using environmental Swiffer™ samples appears to be a sensitive approach to detect IAV at the pen level.
However, sample size has been limited to one farm.
The objective of this project was to compare the sensitivity of pooled pen oral fluids (OF) and environmental samples (Swiffer™ kits on water cups) using individual pen oral fluids as the standard.
Fifteen paired environmental and individual pen OF were collected at days 3, 7, 10, 17, 24 and 31 post placement in two different nursery farms. Environmental samples (ES) were taken using Swiffer™ cloths to sample the bottom of water cups (both pans and bowls), focusing around nipples. After individual samples were collected, pen OF were pooled by 3.
There was an overall sensitivity of 71% (IAV) and 14% (PRRS) for the ES samples compared to individual OF. Pooled oral fluids samples had an overall sensitivity of 50%(IAV)and 80%(PRRSV)relative to individual pen OF.
In summary, ES appears to be a good strategy when sampling for IAV and not a reliable option when trying to diagnose PRRSV.
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In the last 9 years, on average 10.2% (Range 3.7% – 22%) of status 4 farms have had a PRRS outbreak during the MSHMP season and in the 2017-2018 season, the cumulative incidence (July to April) is 9.6%.
The lowest PRRS incidence was observed during the 2013/2014 PRRS season; the year that PED entered the US.
PRRS incidence in status 4 farms during the current MSHMP season is not higher than the ones observed in the previous MSHMP seasons.
Reminder: Status 4 sow farms are the farms that considered negative both in shedding and exposure status in the classification document published by the AASV.
Has there been an increase in PRRS outbreaks incidence in status 4 sow farms?
PRRS incidence in status 4 farms from 2009 to April 2018 was compiled and compared with the current MSHMP year using Fisher’s Exact test.
During the current MSHMP year (July 2017- April 2018), 27 status 4 farms have had a PRRS outbreak (6.9% incidence). The average incidence of status 4 farms from 2009 to April 2018 was 9.6%. However, PRRS incidence have varied greatly among years (figure 1). PRRS incidence had its minimum value during the 2013/2014 MSHMP season with a 3.4%. This coincides with the year that porcine epidemic diarrhea virus (PEDv) entered the US.
When comparing the incidence during the 2017/2018 MSHMP year with the incidence observed during the 2015/2016 MSHMP year, a borderline significant difference (p=0.06) was observed.
PRRS incidence in status 4 farms (July 2017 –April 2018) was overall similar to previous years, although slightly higher than July 2016-April 2017, and significantly lower than July 2015-April 2016. Other factors, such as region, may be contributing to the
perception of increased PRRS incidence in status 4 farms.Exploring these factors may help explain the perception of increased