Advances in natural heat detection. Claire Ponsart, Pascal Salvetti

Transcription

1 Advances in natural heat detection Claire Ponsart, Pascal Salvetti

2 Physiological background 1 oocyte ± 21 days Viability: 6 hours only Kölle (AETE, 2010) When to inseminate? Kölle (AETE, 2010) 6 to 10 hours to reach the oocyte Viability: 24 hours

3 How to detect ovulations? Estrous Oestrous P 4 concentrations monitoring Estrus monitoring

4 P 4 monitoring: Herd Navigator On field measurements in milk (automatic sampling according to animal status): LDH, BHB, Urea and Progesterone. Friggens et al. (2008) cited by Martin et al. (in press) -93.3% Se and 93.7% Sp (over passing the problem of silent ovulations), - early alerts (12h before estrus), - no manipulation needed What about costs?

5 P 4 monitoring: other on farm tools Mini labs for on farm P 4 assays: Concordance rate between ELISA inlab assay (UNCEIA) and eprocheck : 76.7% in milk (Gatien et al., 2012) 87.5% in serum Cost, time-consuming Individual P4 assays: LFIA, colorimetric Efficient? Time-consuming ++

6 Heat detection Det estrus ( ) 1 aim : to improve heat detection practices in cattle 3 workpackages: Description of behavioural changes during estrus in beef cattle On field interviews of farmers and technicians about estrus detection Development of a predictive model to assess heat detection quality

7 Behavioural changes during estrus 118 estrus analyzed - 83 in Charolais (CH) - 15 in Limousine (LI) - 20 in Blonde d Aquitaine (BA) Continous video recording, P4 monitoring (blood) For each estrus 36h estrus video versus 36h control video Frequency Hours from the beginning of estrus Standing estrus Agonistic social signs Affinity social signs Secondary sexual signs Mounting signs + time spent standing up

8 Behavioural changes: which signs to detect? Not specific Behaviours type Race Estrous phase luteal phase Social signs (%) Repetition of SS signs is specific Secondary sexual signs (%) Mounting signs (without StE) (%) Standing Estrus(%) Rare CH L 59 ± ± 9 CH B 47 ± ± 10 LI 37 ± ± 11 BA 47 ± 8 84 ± 10 CH L 30 ± 10 8 ± 9 CH B 33 ± 7 10 ± 10 LI 45 ± 8 9 ± 12 BA 40 ± 7 16 ± 10 CH L 9 ± 5 0 ± 0 CH B 15 ± 7 0 ± 0 LI 14 ± 4 0 ± 0 BA 11 ± 3 0 ± 0 CH L 2 ± 2 0 ± 0 CH B 5 ± 5 0 ± 0 LI 4 ± 3 0 ± 0 BA 2 ± 1 0 ± 0 Specific

9 Behavioural changes: less lying time periods Race % of time spent «standing-up» Œstral phase Luteal phase CH L 88 ± 11 % 48 ± 25 % CH B 82 ± 12 % 53 ± 11 % LI 84 ± 11 % 61 ± 20 % BA 91 ± 8 % 59 ± 23 % + 30 %

10 Heat detection difficulties: highly variable expression «Easy» cow «Discreet» cow 8 to 15 % of silent ovulations! (disenhaus, 2004; Ranasinghe et al., 2010)

11 Logistic regressions using 587 ovulations in Normande & Holstein cows (including effects of breed, other cows in heat and milk production) Cutullic et al. (2010) Heat detection difficulties and milk production All sexual signs Probability of detection (ovulation) Mounting signs only (except StE) Standing estrus only (StE) Milk production (Kg/day)

12 Heat detection difficulties: a decreased estrus duration In beef cattle Race Standing estrus (StE) Secondary sexual signs (SSS) CH A 7,6 ± 4,6 h 12,4 ± 3,9 h CH B 9,9 ± 3,7 h 12,1 ± 4,1 h LI 8,2 ± 6,3 h 11,1 ± 4,0 h BA 6,2 ± 3,4 h 11,0 ± 2,4 h In dairy cattle 4 to 8 h (StE) 14 h (SSS) Estrus duration Durée (StE-StE) AC-AC Cutullic et al. (2010)? Year of publication Année de publication

13 Heat detection difficulties: frequent cyclicity abnormalities Race nb Normal Inactivity Prolonged Luteal Phase Abondance (80 %) 1 (4 %) 1 (4 %) Charolaise (56 %) 42 (44 %) 0 Motbéliarde (67 %) 9 (25 %) 0 Normande (81 %) 8 (8 %) 8 (8 %) Prim Holstein (55 %) 26 (19 %) 32 (23 %) (65 %) 86 (12 %) 41 (10 %) Disenhaus et al. (2008) Cyclicity profiles of 63 holstein cows (Trinottières 2012, in press): Normal profiles 60.3 % PLP profiles 17.5 % Inactivity profiles 6.4 % Chanvallon et al. (2012)

14 Heat detection difficulties: Changes in estrus cycle length Race nb Mean Median S.D. Abondance Charolaise Montbéliarde Normande Prim Holstein Disenhaus et al. (2008)

15 Visual detection: what is expected? Field study in French dairy farms: % of insemination during the luteal phase is varying according to the estrus signs used by breeders to inseminate cows Higher % when unspecific signs (mucus discharge, nervosity, ) are used Lower % when standing /mounting signs are used Salvetti et al. (2012)

16 Visual detection: what is expected? Field study in French dairy farms: Conception rate depending on estrus signs used by breeders to inseminate cows Decreased when only one unspecific sign is used to inseminate Lowered when standing/mounting signs are used Salvetti et al. (2012)

17 Visual detection: Timing of AI Field study in French dairy farms: Time interval between estrus detection and insemination should be shorter than 24 hours Salvetti et al. (2012)

18 Visual detection: expected efficiency Observation (15 min per seq.) % of cows detected 1 time (midday, Mi) 24 1 time (afternoon, A) 42 1 time (morning, Mo) 50 2 times (Mo & A) 81 3 times (Mo, Mi & A) 86 0 Lacerte (2003) % of cows not detected in estrus Key figures : Ducrot et al.(1999) > 60 min/day min/day < 30 min/day Months in milk - 50 % of sensitivity (Se) - 95 % of accuracy (Ac)

19 Estrus detection aids Different tools, automated or not Cameras Standing estrus detector Podometer Neck collar activimeter For review see Saint Dizier and Chastant- Maillard (RDA, 2012)

20 Estrus detection by cameras: Results from one single farm Study Protocols Method Frequency/duration Signs Sensibility (Se) Accuracy (Ac) Hetreau et al. (2010) Visual detection 4 x 10 min StE 76 / Camera in continue 60 min StE 86 / «Camera-icons» 20 min StE 77 / Bruyère et al. (2011) Visual detection 4 x 10 min StE 69 a 94 «Camera-icons» 20 min StE 80 ab 93 «Camera-icons» + visual detection 20 min + 4 x 10 min StE 89 b 93 Good performances but time-consuming

21 Automated activity monitoring Our experience in dairy cattle: 85 Holstein cows (Derval, 2008, not published) Heatime neck collar: 65.8% Se and 81.2% Ac 41 Holstein cows (Philipot et al., 2010) Heatime neck collar: 76.0% «Se»* and 93.0% Ac Visual detection: 86.0% «Se»* and 96.0% Ac * P 4 assays only when a detection occurred not a real Se 62 Holstein cows (Trinottières, 2012, not published) Heatime neck collar: 62.6% Se and 84.2% Ac Afimilk pedometer: 73.0% Se and 71.6% Ac

22 Automated activity monitoring Few study, great variability in results... Effects of breeding system? Breed? Health?... Comparison of 4 methods of detection Methods Se (%) Ac (%) Scrathcard Holman et al. (2011) 67 Holstein cows Kamar Farmer Neck collar Pedometer Neck collar + farmer Optimal combination

23 Monitored heat detection aids: what can we expect? Further studies are needed to improve heat detection algorithms in relation with the breeding / management system (race, housing, health, calving dates, ) Necessity to cross observations and to take into account animal history

24 How to help farmers? Assessment of heat detection quality Det estrus tool Simple informatic software (under Excel ) allowing to assess the quality of heat detection in the herd, using basic reproduction results

25 Detœstrus approach (1) Assessment of risk factors associated with low cyclicity rates and discrete estrus behavioural signs --> estimation of heat expression level Characteristics of the farm and breeding Risk factors management MILK PRODUCTION AND ENERGY DEFICIT % of high producing cows 1 <15% Number of milkings per day 2 % of cows with low protein ratio at the start of lactation 2 <15% HEALTH STATUS Evaluation of heat expression level Level and penalties associated % of cows with placenta retention and/or chronic metritis <15% % of cows showing lameness between 15 & 30% % of cows having other acute pathologies 3 <15% ANIMAL HOUSING (main type of housing at time of reproduction) Estimation of heat expression level (score/100) 55 Score (/100) with green/orange/red code

26 Detœstrus approach (2) Basic reproduction results including heat expression level Characteristics of the farm and breeding management Level of production by cow and year (kg) 7,800 Level of heat expression High Time indicator between calvings (d) 95 Average interval calving AI 1 (d) 85 Minimal postpartum delay for AI 1 (d) 50 Evaluation of heat expression level by cows Evaluation of heat detection quality Rate of success for AI 1 36 Rate of success for all AIs 1 38 % of intervals between AIs < 18 d 0 % of intervals between AIs d 39 % of intervals between AIs d 16 Estimation of heat detection efficiency at 1 st AI and on returns + % of heat detection up to the 1 st AI included % of recurrent heats detected % of inseminations outside of heat period Estimation of heat detection accuracy (green/orange/red code)

27 Detœstrus approach (3) Characteristics of the farm and breeding management Evaluation of heat expression level by cows Evaluation of heat detection quality Efficiency Accuracy Risk factors analysis

28 Detœstrus approach (3) RESULTS This file automatically shows all risk factors from files and the level of associated Characteristics of the farm and breeding risk. Factors are management not in order of importance. Estimation of resumption of cyclicity and expression of heat Note: 78 /100 Evaluation of heat Evaluation Risk: High of Medium heat Low MILK PRODUCTION AND ENERGY DEFICIT % high producing expression cows level by cows detection quality X Number of milkings per day X % of cows with low protein ratio at the start of lactation X HEALTH STATUS Efficiency Accuracy Risk factors analysis % of cows with placenta retention and/or chronic metritis X % of cows showing lameness X % of cows having other acute pathologies 3 X ANIMAL HOUSING (main type of housing at time of reproduction) Type of housing X Type of building X

29 Detœstrus approach (3) RESULTS This file automatically shows all risk factors from files and the Sum-up level of associated of the Characteristics of the farm and breeding risk. Factors are management not in order of importance. Risk factors list situation Estimation of resumption of cyclicity and expression of heat Note: 78 /100 Evaluation of heat Evaluation Risk: High of Medium heat Low MILK PRODUCTION AND ENERGY DEFICIT % high producing expression cows level by cows detection quality X Number of milkings per day X % of cows with low protein ratio at the start of lactation X HEALTH STATUS Efficiency Accuracy Risk factors analysis % of cows with placenta retention and/or chronic metritis X % of cows showing lameness X % of cows having other acute pathologies 3 X ANIMAL HOUSING (main type of housing at time of reproduction) Type of housing X Type of building X

30 Detœstrus approach (3) Characteristics of the farm and breeding management Evaluation of heat expression level by cows Evaluation of heat detection quality Efficiency Accuracy Risk factors analysis Summary and advices to farmer Actions plan

31 How to help breeders? Increasing breeder s awareness regarding economic losses involved by a default of heat detection Simulation of economic losses involved by a decrease in heat detection performances compared with a reference situation (50 cows producing 9500 Kg of milk per year, 70% of Se, 99% of Ac) with low (25%) or high (50%) fertility Heat detection quality Costs ( ) per cow and per year High fertility Low Fertility Se1 reduced by 33% Se2 reduced by 33% Ac reduced by 12% Sum of the 3 problems Seegers et al.(2010)

32 Important costs related to estrus detection deficiency Inchaisri et al.(2010)

33 Futures Improvement of automated detection aids Promising genomic selection: towards identification of estrus expression QTLs Kommadath et al. (2011) OXT and AVP genes and estrus behaviour expression