Management support by drinking pattern modeling

Transcription

1 Management support by drinking pattern modeling CPHpig 2018 Katarina Nielsen Dominiak Postdoc, IVH This research was funded by the Danish Council for Strategic Research (The PigIT project, Grant number )

2 CPHpig 30/01/ Spatial modeling of water data PhD thesis Modeled simultaneously monitored water consumption across multiple pens in multiple sections of a weaner herd and a finisher herd Correlations between drinking patterns in pens and sections were included The detection model predicted outbreaks of diarrhea or pen fouling And pointed out specific pens or sections with abnormal drinking patterns leading to outbreaks Pointed areas are FOCUS AREAS for management

3 CPHpig 30/01/ Modern pig production is centralized Sow herd(s) More animals per herd less time per animal during daily check Weaners (7-30 kg) Early signs of outbreaks might be missed during a busy day Sensor-based monitoring around the clock Finishers ( kg) Real-time notifications of early signs of outbreaks Timely interventions may prevent actual outbreaks

4 CPHpig 30/01/ Sensor-based detection models - concept Data observed by sensors Mathematical model(s) Modeled data exceeds threshold Alarm Decision support for interventions and managerial focus Prevention or reduction of outbreaks of diseases

5 CPHpig 30/01/ All-In-All-Out strategy highly systematic management Pigs in Pigs in Pigs in Pigs in Pigs in 2 weeks 2 weeks 2 weeks 2 weeks Connecting corridor Section 1 Section 2 Section 3 Section 4 Section 5 2 weeks 2 weeks 2 weeks 2 weeks Cleaning Cleaning Cleaning Cleaning Cleaning Batch 1 Batch 1 Batch 1 Batch 1 Batch 1 Batch 2 Batch 2 Batch 2 Batch 2 Batch 2 Batch 3 Batch 3 Batch 3 Batch 3 Batch 3

6 CPHpig 30/01/ All-In-All-Out strategy herd-specific knowledge Connecting corridor Section 1 Section 2 Section 3 Section 4 Section 5 Age/size of pigs in a given section Risk of diarrhea or pen fouling at a given age Risk of other conditions at a given age

7 CPHpig 30/01/ Simultaneous deviations across the herd AUC (48 hours) = 0.92 Simultaneous deviations in pens within the same section AUC (48 hours) = 0.87 Deviations in an individual pen AUC (48 hours) = 0.87 Area-specific alarms Herd Central water supply Central feeding system Central electricity Section Pigs of same age Feed mixture Climate control Pen Pigs of same gender/size

8 CPHpig 30/01/ Weaners (7-30 kg) In High risk periods Pen fouling during warm summers Out Weeks Diarrhea (coli) New feed Tail bites Diarrhea (lawsonia/coli) Respiratory diseases Finishers ( kg) Pen fouling during warm summers In Out Weeks Diarrhea (coli) New feed

9 CPHpig 30/01/ Weaners (7-30 kg) Pen fouling In Out Weeks Diarrhea (coli) New feed Diarrhea (lawsonia/coli) Herd-specific periods Alarms for specific pens can be added as additional information Time after insertion 0-1 week 2-3 weeks 4-5 weeks 6-7 weeks

10 CPHpig 30/01/ Water data reflects multiple conditions General wellbeing (1) Tail bite? Stress behaviour? Respiratory diseases? Other causes? (1) Madsen (2005), Dominiak (2017)

11 CPHpig 30/01/ Health & welfare Sick Change in water data Binary conditions Subclinical stages Sick Healthy Other stressors Progressive conditions Reflected in Water consumption

12 CPHpig 30/01/ Management Climate Ventilation settings/draft Temperature settings Feeding system Change in feed composition Water system Blocked drinking nipple Leaking drinking nipple Sufficient water supply? Reflected in Water consumption

13 CPHpig 30/01/ How to respond to area-specific alarms Check smart-phone interface Go to specific areas where alarms are generated If high risk of known condition choose preventive intervention Otherwise check: Climate/ventilation Feeding system Water system

14 CPHpig 30/01/ Take-home messages Alarms for specific pens and sections point out high-risk areas with high accuracy Changes in drinking patterns tends to be related to multiple causes Productivity and animal welfare can be improved through automatic monitoring of water data THANK YOU