in culling decisions in seasonal dairy herds M.M. Kelleher, D.P. - PowerPoint PPT Presentation

Cow Own Worth – synergising data to provide a new tool to aid in culling decisions in seasonal dairy herds M.M. Kelleher, D.P. Berry, P.R. Amer, A. Cromie, R. Evans Speaker: Margaret Kelleher

ICBF Database Farmers Bord Bia Irish Food Abattoirs Board Vet Dept. labs Agri ICBF AI HerdPlus companies Database Milk Marts recording Teagasc Milk Research Co-ops Breed Societies

Cow’s Own Worth (COW) Designed to represent more closely the future phenotypic performance of dairy females A new system to rank females on predicted profit potential • Spring-calving system • EBI – Economic Breeding Index (national breeding index) • Centralised database • Reward data recording herds with an added value service 3

Question – who would you cull????? EBI € 100 EBI € 200

Question – who would you cull????? EBI € 200 Parity 5 EBI € 100 Parity 2

Question – who would you cull????? EBI € 100 Parity 2 EBI € 200 Calved Feb Parity 5 Calved April

Question – who would you cull????? EBI € 100 Parity 2 Calved Feb Av SCC 210 EBI € 200 Parity 5 Calved April Av SCC 120

Cow’s Own Worth (COW) 8

Expected profit from: Current Lactation • Milk • Management • Health • Maintenance • Fertility (calving date) Future Lactations Net Culling Cost • Milk • Management • Cull cow value • Health • Maintenance • Replacement cost • Beef • Fertility • Calving • Descendants + predictions on fertility, survival and SCC performance 9

Current lactation profit Actual calving date Current Lactation • Milk • Management • Health • Maintenance • Fertility (calving date) Current milk price Costs per calving month MDSM 10

Expected profit from: Current Lactation • Milk • Management • Health • Maintenance • Fertility (calving date) Future Lactations Net Culling Cost • Milk • Management • Cull cow value • Health • Maintenance • Replacement cost • Beef • Fertility • Calving • Descendants + predictions on fertility, survival and SCC performance 11

Future lactations profit Future Lactations • Milk • Management • Cull cow value • Health • Maintenance • Replacement cost • Beef • Fertility • Calving • Descendants + predictions on fertility, survival and SCC performance 12

Future lactations profit Future Lactations • Milk • Management • Cull cow value • Health • Maintenance • Replacement cost • Beef • Calving Future milk price MDSM 13

Future lactations profit EBI times Cumulative Discounted Expression Future Lactations • Cull cow value • Replacement cost • Descendants 14

Future lactations profit Actual calving date Genetic effects Next calving date Future Lactations • Cull cow value • Replacement cost • Fertility + predictions on fertility, survival and SCC performance 15

Future fertility performance Transition matrices Jan Feb Mar Apr May Jan Feb Mar Apr May Best Proportion 0.14 0.53 0.22 0.08 0.03 1 Genetics 2 Cost ( € ) 0.00 0.00 -151.00 -210.00 -437.00 3 ∑Cost ( € ) -63.13 4 Jan Feb Mar Apr May 5 Proportion 0.13 0.39 0.25 0.15 0.07 6 Cost ( € ) 7 0.00 0.00 -151.00 -210.00 -437.00 8 ∑Cost ( € ) -99.84 9 Worst 10 Difference of € 36.71 Genetics 16

Expected profit from: Current Lactation • Milk • Management • Health • Maintenance • Fertility (calving date) Future Lactations Net Culling Cost • Milk • Management • Cull cow value • Health • Maintenance • Replacement cost • Beef • Fertility • Calving • Descendants + predictions on fertility, survival and SCC performance 17

Net culling cost Salvage value Cull value + Genetics CWT Long term replacement requirement Net Culling Cost • Cull cow value Replacement • Replacement cost cost 18

Results: Milk production € 360 more value per cow per lactation for cows in top 25% versus bottom 25% Milk (kg) Fat (g/100g) Protein (g/100g) Group COW EBI COW EBI COW EBI 6965 6674 4.07 4.11 3.57 3.57 Best (6.17) (6.32) (0.003) (0.003) (0.001) (0.003) (Top 25%) € 9000 6695 6580 4.03 4.04 3.52 3.52 Good (6.45) (6.38) (0.003) (0.003) (0.001) (0.003) 6512 6530 4.01 4.00 3.49 3.49 Poor (6.18) (6.27) (0.003) (0.003) (0.001) (0.003) 6164 6467 3.97 3.93 3.44 3.44 Worst (6.08) (6.24) (0.003) (0.003) (0.001) (0.003) (Bottom 25%) 19

Survey results 2016 pilot 1. 1. COW was as able able to o ide dentify ify cows 100% per perfor ormin ing well ell wi within in my y her herd. 90% 2. 2. COW was as abl able to o ide dentify fy cows for or cul ulli ling g wi within in my y her herd. 80% 3. 3. I wou ould ld use use the the COW to o help help 70% infor orm my y cul ullin ing g deci decisio ions if f it t 60% 80% 86% wer ere to o be become a a rou outin tine ser ervic ice Percentage 88% 91% 91% 93% 93% fr from om ICBF CBF. 95% 98% 50% 4. 4. I fou ound nd the the rep epor ort ea easy to o read ead. 40% Agree 5. 5. The Th e sum ummary ry tab able les wer ere use useful l 30% Neither to o hi high ghlig ight spe pecifi ific ar areas of of Disagree 20% pr prod oductio ion (E (EG: Top op 10 and and 10% bottom 10 on bo on COW, Top op 10 an and 10% 10% 7% bottom 10 on bo on mi milk lk soli olids, High High 5% 10% 5% 9% 7% 2% 5% 5% 5% SC SCC C cows). ). 2% 2% 2% 0% 0% 0% 0% COW was able COW was able I would use The report easy The summary The colour My milk I would like I would to identify cows to identify cows COW to help to read tables were coding of the recording has COW to be recommend the 6. 6. The he colo olour cod odin ing g of of the the top op 10% % performaing for culling inform culling useful to top and bottom more value now generated for national well decisions if it highlight 10% on traits that I can my herd from extension of the and bo and bottom 10% % on on imp mportant were available specific areas of was useful receive COW now on COW in 2017 tr trait its use usefu ful. l. from ICBF production Question 7. 7. My mi My milk lk recor ordin ing g infor ormatio ion ha has s mor more valu lue no now w th that I ca can rece ceiv ive a COW irepor ort. 8. 8. I wou ould like the the COW to o be be gen enerated for or my y her herd fr from om no now w on. on. 9. 9. I wou ould ld rec ecommend the the na natio ional l extensio ion of of the the COW to o al all dairy dairy mi milk lk recor ordin ing g her herds in n 2017. 2017.

Profile development 2017  Development underway  Pilot phase scheduled July  Farmers testing screens and accuracy of COW rank  Potential to encourage more data recording with data completeness dash bars

Current data recording

Conclusions  Complimentary to the EBI (national breeding index)  Added value service  Prospects to improve herd profitability  Multiple sources of data available  Live system  Maximise COW accuracy by;  Recording MORE data  Recording ACCURATE data  Pilot phase of on-line service July 2017  Commercial roll-out September pending results of pilot phase

Questions?