Prepartum Behaviour as a Predictor of Postpartum Disease

Question 1

What is Parity

Answer 1

refers to how many calves a cow has had

e.g. a first parity cow = has had one calf

Question 2

What is a fresh cow

Answer 2

cow who has recently calved

Question 3

What is the transition period

Answer 3

• aprox 3 weeks pre to 3 weeks post calving

- transition from late preg (dry period = no milk production) to early lactation

Question 4

What physiological changes happen during the transition period

Answer 4

• depressed immune funtion
• opening of teat canals
• changes in hormone expression (e.g. to relax pelvic ligaments)
• body condition loss after calving

Question 5

Ketosis

Answer 5

• negative energy balance = caloric requirements for fresh cow are so high that many dont consume enough feed to compensate for calories they burn
• subclinical ketosis affects = 11-49% fresh cows (high serum ketone conc but no clinical signs)
• hyperketonaemia = abnormally high ketone bodies in blood

Question 6

Metritis

Answer 6

= inflammation of the uterus usually caused by bacterial infection

• enlarged uterus
• watery brown discharge
• reduced milk yield, dullness, toxaemia, high fever
• most common in first 10 days post calving
• 21-40% cows affected
• Risk factors = heifer cows that have experienced dystocia, retained placenta (failure to expel fetal membrane w/in 24 hours) or other calving problems (e.g. milk fever, ketosis)

Question 7

Huzzy 2007 prepartum behaviour study - method

Answer 7

• collected feeding/ drinking behaviour measurements from 101 dairy cows
• from 2 weeks before calving up until 3 weeks post calving
• feed intake data included
• electronic monitoring system
• collected social behaviour data assessed from video recordings
• metritis diagnosed based upon body temperature and vaginal discharge until 21 days post partum

Question 8

Huzzy 2007 prepartum behaviour study - findings week before calving

Answer 8

• for every 10 min decrease in daily feeding time = odds of severe metritis after calving increased by 1.7x
• for every 1kg decrease in dry matter intake = odds metritis after calving increased by 3x
• cows later diagnosed with severe metritis = engaged in fewer aggressive (agonistic) interactions
• first research showing social behaviour plays role in transition cow health

Question 9

Goldhawk 2009 prepartum feeding behaviour study - findings week before calving

Answer 9

• indicator for subclinical ketosis
• for every 10 min decrease in daily feeding time = risk sub clinical ketosis increased by 1.9x
• for every 1kg decrease in daily DMI = risk of SCK increased by 2.2x
• animals later diagnosed with SCK = initiated fewer displacements at feed bunk

Question 10

How automation can help

Answer 10

• Insentec food bins able to record individual feed intake and feeding behaviour
• an electronic monitoring system
• depend on RFID system
  ~ cows wear radio frequency identification ear tags
  ~ bin records which cow is eating and for how long and how much each cow consuming
  ~

Question 11

Can electronic feed system be used to identify competitive interactions at the feed bin? (Huzzy 2014)

Answer 11

Yes

• competitive interactions can be quantified using data from electronic feeding system
• optimal interval for predicting replacements at feed bunk = 26 seconds (specificity = 82%, sensitivity = 86%)
• validate results to feeding video recordings

Question 12

Sensitivity (and in relation to Huzzy study)

Answer 12

= proportion of positives correctly identified as being positive

(e. g. proportion of sick animals correctly identified as being sick
- 86% replacemens at feedbunk (as identified in video) were correctly identified as replacements by the electronic feed bin algorithm

Question 13

Specificity (and in relation to Huzzy study)

Answer 13

= proportion of negatives correctly identified as being negative

(e. g. proportion of healthy animals correctly identified as being healthy)
- 82% of times cows switched places at feedbunks NON-aggressively (without displacing and replacing another cow) were correctly identified as non-aggressive

Question 14

Using electronic drinking systems as well to identify competition in dairy cows

Answer 14

• Mcdonald, von Keyserlingk and Weary 2019
• optimal interval to identify replacement = 29 seconds (82% sensitivity, 83% specificity
• Foris et al 2019 validated a replacement detection algorithm using combined data from electronic water and feed bins
• recal and precision of algorithm very high (average >0.8) comparable to human trained observers

Question 15

What did the previous studies have in common and are these factors realistic for normal dairy farmers

Answer 15

• conducted on single farms designated for research purposes = how can they be generalised to the commercial context? need to be used on several commercial farms
• considered full day data on feeding and agonistic behaviours = farmers wont have time to analyse days worth of data
• considered either ketosis or metritis, not both = do cows later diagnosed with both behave differently to those with one disease and healthy animals

Question 16

Sahar, Beaver et al 2020 study - aim

Answer 16

• assess if measures of feeding and competitive behaviour prepartum were associated with hyperketonaemia and metritis on commercial farms
• 5 commercial farms
• specifically looked at first 90 mins after fresh feed delivery to evaluate feeding behaviour and agonistic interactions
• actor (bully) and reactor (bullied) interactions

Question 17

Sahar, Beaver et al 2020 study - results actor/reactor interactions

Answer 17

• cows with both postpartum diseases had significantly less interactions than health and one condition cows
• very small difference between healthy and one condition cows for the no. interactions
• not much pattern in prepartum interactions and whether or not the cow remained health in reactor cows
• ## actor = healthy more likely to be involved in more agonistic interactions than one condition and 2 condition cows

Question 18

Sahar, Beaver et al 2020 study - results time spent eating

Answer 18

• animals that did not eat during observation period (90 mins after fresh feed delivery) = 89% chance of becoming sick with at least one condition after calving
• cows that spent only 30 mins eating = >82% chance of being sick with at least one condition post calving
• drop of feeding time could indicate development of at least one condition

Question 19

prediction vs association studies

Answer 19

Prediction:
- aims to predict future events by analysising patterns likely to forecast future results
- based upon past behaviour, what is likely to happen in the future
Association:
- understanding a phenomenon
- simple relationships between variables and outcomes

Question 20

Developing a predictive model - data spliting

Answer 20

• most of the data are used to develop the model = training data
• remainder of data used to test the model = test data
• typical split 60:40 (training:testing) more training than testing

Question 21

Why is predictive modelling so important for dairy science

Answer 21

• incidence of transition cow disease has remained relatively unchanged over time, despite efforts to improve monitoring and adjust management to reduce disease risk
• risk factors can be assessed using a variety of sources (e.g. health records, feed intake, BCS, milk production data) ~ bring together most important variables and their interactions

Question 22

What is statistical interaction (using example)

Answer 22

• try to determine relationship between BCS and post partum disease status
• But what if the effect of BCS on postpartum disease status depends on cows parity
  = interaction ( 2 variables but relationship between them depends upon the influence of third variable
• cows with fisrst parity dont see much of a difference on probability of disease for low or high BCS
• But 2nd or above parity = cows with higher BCS far more likely to become sick
• cross over interaction = first parity w/low BCS more likely to get sick but 2nd parity less likely to be sick if low BCS

Question 23

Sahar, Beaver et al 2020 study - develop predictive model which cows sick after calving study

Answer 23

• recorded behaviour of 318 cows using electronic feeding system
• after calving, cows monitored for signs of metritis hyperketonaemia and mastitis
• split data using stratified random method: 70:30
• model showed that animals at risk of becoming sick postpartum can be identified with reasonable success = se=73% sp=80%
• found a no. of interactions between number of visits to the feed bins, time spent feeding & kg feed consumed on probability of becoming sick post partum

Question 24

Potential application of predictive models on farms

Answer 24

• cost per case of hyperketonemia = £88
• cost per case of metritis = £80
• according to model: the 60% cows with highest probability of becoming ill postpartum, will include 97% of cows that will actually become sick
• if model can be automated for farm use = used to predict which cows are at highest risk of becoming sick
• offers opportunity for farmers to prevent illness from occurring = allow intervention and save money on treating sick animals
• allow quick data input from farmers and get a result instantly
  (may lead to healthy animals being treated as no model is perfect representation of reality)
• need a cost analysis to see if worth cost for future studies

Question 25

What is temporality

Answer 25

= we dont know what causes what
- does participation in a lower no. aggressive interactions contribute to disease (through resulting decrease in intake)
OR does onset of disease cause the reduction in agonistic interactions

Question 26

Foris et al 2020 - study aim and purpose

Answer 26

• characterise social competition strategies in transition cows and determine how they vary with health status
• competition for feed is a social stressor and associated with increased risk of illness
• some argue that increasing feed synchronicity, reduces competitiveness and increases positive welfare esp for lower rank cows
• BUT for indoor systems, agonistic interactions are common as feed space in limited
• individual variation in feeding behaviour = some cows feed at peak times risking agonistic interactions to gain feed access, others chose to wait to avoid interactions and feed at non-peak time
• changes in feeding behaviour may

Question 27

Foris et al 2020 - study results

Answer 27

• no change in strategies between healthy and metritic cows
• metritic cows changed strategies more betweeen PRE (d -6 to -1) and POST1 (d 1-3) and between POST1 and POST2 (d 4-6)#- indictaed that strategies change in association with parturition and metritis
• metritic changed strategies in first 3 day entering the social group after calving and in the 3 days around diagnosis (possibly due to rise in sickness/illness)
• high competiveness score = longer feeding times and more agonistic interactions (actor and reactor)
• feeding synchrony (mean no. of occupied feeding in bins when cow feeding) may have been affected by milking during post partum period as cows were away from pen
• social bonds can affect competitiveness as known to influence physical proximity and behavioural synchrony
• unable to find differnece in component scores between healthy and metritic cows = social comp strategy not risk factor/indicatior of metritis
• group composition changed dynamically, limit establishment of social heirachy = more agonistic interactions