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Iowa Pork Industry Center

Understanding the basis of sow mortality

and strategies to maximize productivity

Jason Ross

Vita Plus Swine Summit

March 21st, 2018

College of Veterinary

Medicine

Objectives for today…

1) Discuss ongoing project on sow mortality.◦ -What's been done and where its going.

2) Discuss NPB funded projects on gilt development. ◦ -Utilization of vulva size during development as a predictor of age of puberty and sow productivity.

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Background

Sow mortality, especially due to prolapses, has increased the past 5 years in the US swine industry.

It has become a significant welfare and production issue.

No good understanding of root causes are known at this time.

National Pork Board Released an RFP in October, 2017.

ISU Investigators: Amanda Chipman, Colin Johnson, Anna Johnson, Kent Schwartz, Chris Rademacher, Suzanne

Millman, Aileen Keating, Ken Stalder, John Patience, Nick Gabler, Daniel Linhares, Jason Ross

Timeline for Sow Prolapse Study

9-25-2017: Received the Request for Proposals.

10-13-17: Submitted Proposal.

10-20-17: Notification of funding.

11-28-17: Interviews for Extension Program Specialist.

12-18-17: Amanda Chipman start date-Project Leader.

12-19-17: Visited first integrated production company to discuss project.

1-3-18: Conference calls with collaborators to enlist sow farms.

1-15-18: On farm data collection begins.

1-25-18: ~50 farms committed to being on the project. Open forum at Iowa Pork Congress.

2-13-18: 88 Sow Farms enlisted on the project.

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Objectives of the Project

Identification of risk factors associated with Pelvic Organ Prolapse in the US sow herd. 1. Establish network of industry partners and Sow Farm Managers (target was 60-80 sow farms).

2. Develop herd and individual sow survey tool and use it on farm.

3. Establish communication and advisory network of producers, allied industry, university faculty and staff.

4. Establish an accessible repository of data, samples and information.

This is a hypothesis generating project. ◦ It is expected to provide data used to justify pursuing future research studies that test specific hypotheses.

Types of Data Collection

1. Off Farm Data collection in coordination with additional farm management individuals.◦ Nutrition and other management decisions.

◦ Production and mortality records for the project period (Jan through May).

2. Historical data (prior to 2018) extracted from production databases.

3. On Farm Data collection in collaboration with Sow Farm Manager.◦ Continuous communication with SFM regarding mortalities.

◦ 1 day visit to sow farm.

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Off Farm DataGenetics

Health history and current status

Management factors

Diet formulations (changes during the project period)

Prior history of mortality and prolapses

Examples of data being collected

Herd factors: Sow farm inventory, gestation and lactation diet parameters, distillers dry grain usage, feed type (i.e. pellet or mash), mycotoxin binder usage, bump feeding, prior mortality and prolapse incidence at the farm, disease history, gilt size at breeding.

Facility factors: Water and feed delivery systems, sow housing type (i.e. pen or stall), gestation pen or stall hygiene, environmental conditions.

Management factors: Artificial insemination hygiene/cleanliness, farrowing assistance strategies, sow feedback and vaccinations, protocols on gestation pen/stall management, culling criteria and strategies.

Animal based measures: Data will be collected on sows that are at specific stages of production, assistance on previous farrowing, genetic background, lameness score, perineal region score, tail dock length, genital-anal distance, body condition score.

Records and data integrity: Prior year sow production and mortality records will be extracted and communication on how records were created with farm staff to ensure causes of mortality are accurately defined.

Sample Banking: We will collect representative fecal samples, feed samples, water samples, and swabs of gestation pens/stalls for future distribution and analysis if warranted.

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Enrolling a farm on the study…Who will be the main contact within the production system?

Considerations for farms that are good candidates for inclusion in the study… Location

Sow inventory

Genetics

Recent mortality and POP/1000 sows/week

Biosecurity and down time requirements

Sow Farm Managers that want to proactively be involved in the process.

1 Day Visit to Sow FarmGeneral questions

◦ Sow housing.

◦ Management practices.

◦ Nutrition.

Data collection on individual sows

Taking samples◦ Feed.

◦ Some environmental swabs and blood samples have been collected.

◦ Intend to take ‘targeted’ sampling as project progresses.

Iwasawa (2004)

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Individual Animal Measurements

Perineal Scoring: Score 1

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Perineal Scoring: Score 2

Perineal Scoring: Score 3

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Mortality and Prolapse Record Sheet

Current Status of Farms Involved

87 Sow Farms representing about 320, 000 sows are submitting mortality data.

13-Larger systems/groups involved that manage sows.

Between total sows managed by the systems involved, independent sow farm managers and consultants, we should have an estimated 40-50% of industry involvement.

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Causes of Mortality by Week (Weeks 4-10)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

week 4 week 5 week 6 week 7 week 8 week 9 week 10

Unknown/Other

Lame/Injured/Downer

Intestinal (Ulcer) Complications

Disease

Difficulty Farrowing/RetainedPig(s)Both Rectal and Vaginal/UterineProlapseRectal/Anal Prolapse

Vaginal/Uterine Prolapse

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Week 4 to 10 Trends-All Farms

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

Wk4 Wk5 Wk6 Wk7 Wk8 Wk9 Wk10

Total Mortality

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

Wk4 Wk5 Wk6 Wk7 Wk8 Wk9 Wk10

Mortality Due to Prolapse

An

nu

aliz

ed M

ort

alit

y (%

)

An

nu

aliz

ed M

ort

alit

y (%

)

Looking Ahead…Extracting all the “off-farm” data will take some time.

Will conduct analysis to identify individual and cumulative risk factors of pelvic organ prolapse specifically and mortality in general.

This project is laying the ground work for a very large, industry wide collaboration to continuing addressing mortality in the swine industry.

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Strategies for Improving Reproductive Performance in Gilts

Sow Farm Expectations

Maximize the total number of quality pigs a female weans from the time she becomes breeding eligible until she leaves the herd – Sow Lifetime Productivity.1

Profitability comes after 3rd Parity.2

Insufficient reproduction reduces the opportunity for replacement to offset her initial investment.

1National Pork Board, 2010, 2Stalder et al., 2003

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Annual sow turnover rate for U.S. swine industry is 40-50%.1

Younger sows make up greatest percent of the sow herd.

Lower parity females make up disproportionate percentage of

females culled.2

Reproductive Failure - #1 reason for removal from the herd.3

1PigChamp Year-End Review 2000-2015 2Lucia et. al 2000 3Mote et al., 2009

Sow Lifetime Productivity

How do we Improve SLP? Selection for SLP is a challenge – lowly heritable trait

Gilt Development

Disease

Environment

Age at which a gilt reaches reproductive maturity has predictive value of SLP – age at first estrus.

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Inducing Cyclicity in Gilts

Exposure to Mature Boars 1,2

Commercially available gonadotropins (P.G. 600)

Transportation/mixing stress

1Brooks and Cole, 1970 2Kirkwood and Hughes, 1982

Purdue University Extension

Early Puberty Onset is Predictive of Sow Retention

Patterson et al. 2010

EP– Early Puberty (140 – 153d)

IP – Intermediate Puberty (154 – 167d)

LP– Late Puberty (168 – 180d)

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Later Boar Exposure Improves Synchrony of Gilt Population

Age at Boar

Exposure

Age at Puberty Days to Estrus % Estrus by

day 10

160 d 179 18.9 24%

180 d 191 10.4 67%

200 d 210 8.3 70%

Adapted from Van Wettere et al., 2006

Can Gilts with Greater Reproductive Potential be Selected Prior to Puberty?

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Variation in Follicular Development Exists Prepubertally in Gilts

0

2

4

6

8

10

12

75 85 95 105 115

Fre

qu

en

cyDay of Age

No Follicle develoment< 10 small follicles10->100 small follicles

Graves et al., 2015

Day 98 ± 4 days

No Follicular Development = 21

Follicular Development = 27

Ross, Keating and Baumgard, unpublished

0

200

400

600

800

1000

1200

1400

75 85 95 105 115Day of Age

Mil

lim

eter

s2

Change in Vulva Area during Prepubertal Development

Graves et al., 2015

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Correlation between Vulva Width at Day 105 to Age at First Estrus

20

25

30

35

40

45

140 160 180 200

r = -0.20

P = 0.07

Age of First Estrus

Da

y 1

05

Vu

lva

Wid

th (

mm

)

Vulva Area association with Puberty by 200 days of age

0%

10%

20%

30%

40%

50%

60%

70%

80%

75 85 95 105 115

% A

chie

vin

g P

ub

ert

y

Day

< 1 St. Dev. Of Mean

Within or > 1 St. Dev of Mean

Total

Graves et al., 2015

(Smallest 15%)

(Remaining gilts)

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Methods for Reproductive Tract Scoring as a Tool for Improving Sow Productivity

M.R. Romoser, B. Hale, J. Seibert, K. Bidne, M. Dickson, T. Gall, C.J. Rademacher, L.H. Baumgard, A.F. Keating, J.W. Ross

Study Objectives

Objective: Test the effectiveness of vulva scoring gilts at an age

prior to reaching puberty as a way to identify replacement or

culls candidates in a commercial swine farm.

Hypothesis: Vulva score differences at approximately 15 weeks

(~105d) of age during gilt development is associated with

differences in reproductive performance.

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Experimental Design

Designated Sow Farm

-Farrowing Records

-Litter Losses

-Culling Records

Designated GDU

- Boar Exposure

- Heat Detection

- Culling Records

- Breeding

At ~15 weeks of age

- Body Weight recorded

- Vulva Width (mm) measured

- Three Methods used to score vulva size

- Vulva Score Method A (S, M, L)

- Vulva Score Method B (1-5)

- Farm Personnel Score (1-3)

Gilt Development

Unit (n=958)

Sow Farm Specific GDU

(n=230)

Sow Farm A

Sow Farm Specific GDU

(n=501)

Sow Farm B

Body Weight is Poorly Correlated to VulvaWidth at Approximately 15 Weeks of Age

R² = 0.0617

80

100

120

140

160

180

200

10 20 30 40 50

Bo

dy W

eight

(lb

s.)

Vulva Width (mm)

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Distribution of Gilts for each Scoring System

Farm Personnel Score

Score n %

1 162 22.8

2 496 69.7

3 54 7.6

VSB

Score n %

1 272 22.7

2 305 25.5

3 410 34.3

4 147 12.3

5 63 5.3

VSA

Score n %

S 281 23.5

M 842 70.3

L 74 6.2

Variation of scoring system classification according to Vulva Width (mm)

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Gilt Inclusion RateVulva Score Method A

P = 0.02

64.7%a

73.2%b

84.4%b

35.3%26.8%

15.6%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

S M L

% A

chie

ve P

arit

y 1

Farrowed Removed

44.2% 49.6% 55.6%

55.8% 50.4% 44.4%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

S M L

% A

chie

ve P

arit

y 2

Farrowed Removed

P = 0.32

a-b Differences in means denoted with different letter are statistically significant (P < 0.05)

Gilt Inclusion RateVulva Score Method B

66.0%a

71.7%ab

79.2%b

76.4%ab

84.2%b

34.0% 28.3% 20.8% 23.6% 15.8%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 2 3 4 5

% A

chie

ve P

airt

y 1

Farrowed Removed

44.0% 44.5% 52.3% 51.9% 55.3%

56.0% 55.5% 47.7% 48.1% 44.7%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 2 3 4 5

% A

chie

ve P

arit

y 2

Farrowed Removed

P = 0.02 P = 0.29

a-b Differences in means denoted with different letter are statistically significant (P < 0.05)

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Parity 1 and 2 Performance for Gilts Classified using Vulva Score Method A

1 Classification assigned using Vulva Score Method A (VSA).a-b Differences in means denoted with different letter are statistically significant (P < 0.05)

Parity 1 and 2 Performance for Gilts Classified using Vulva Score Method B

1 Classification assigned using Vulva Score Method B (VSB).a-b Differences in means denoted with different letter are statistically significant (P < 0.05)

4242

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SummaryGilts with accelerated reproductive tract development prior to puberty appear to have reproductive advantages compared to their cohorts.

A positive relationship exists between prepubertal vulva size and Parity 1 inclusion rate and litter size through 2 parities.

Total Born was consistently increased through 2 parities across for all scoring systems (~2 additional pigs)

Summary and ConclusionsVariation in reproductive tract development prior to puberty appears to be associated with reproductive potential as a sow.

Gilts average or above for vulva size at approximately 100 d of age have reproductive advantages for litter performance, inclusion rate and age at which they enter the herd.

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Acknowledgements

Ross Lab Baumgard Lab

Matt Romoser Keating Lab

Kody Graves Undergraduates

Beth Hines Cole Banta

Jake Seibert Zoe Kiefer

Dr. Ben Hale Christy Calderwood

Dr. Malavika Adur Jennie Greene

Dr. Yunsheng Li Megan Jackson

Adrianne Kaiser-Vry Abbie Miller

Samantha Ehrlich

TriOak Foods Tyler Hawbeck

Tom Gall Yvonne White