Consequences of poor reproductive performance

Table 2 Effect of milk yield, parity, calving season, and disease on conception in 13,307 New York Holsteins a Risk factor Hazard ratio First 60-day cumulatiÕe milk yield kg F1582 1.0 1583–1891 0.99 1892–2195 1.01 2196–2541 1.01 2541 0.92 Parity 1 1.0 2 0.98 UU G 3 0.92 CalÕing season Dec–Feb 1.0 U Mar–May 0.93 Jun–Aug 1.06 Sep–Nov 1.01 Disease UU Retained Placenta 0.86 UU Metritis 0.85 UU Ovarian Cysts 0.79 a Hazard ratios for factors in proportional hazards model. The hazard ratio is the ratio between two relative Ž . Ž . risks of an event e.g., conception . For example, if a cow has a hazard ratio of 0.92 parity G 3 , then she has an 8 reduced likelihood of conceiving than a first parity cow. U p- 0.05. UU p- 0.01. conception rate than their herdmates. Older cows and sick cows were less likely to conceive. In contrast, the rate of being bred increased with 60-day milk. These findings demonstrate that farmers are making rational decisions by breeding young, healthy, high yielding cows. Among 30,036 multiparous Finnish Ayrshires, the lowest yielders were less likely to Ž . conceive than were average yielders Harman et al.,1996a . Among 11,761 heifers, the highest yielders were less likely to conceive than were average yielders. A number of disorders decreased conception probability in both multiparous and primiparous cows: anestrus, ovulatory dysfunction, other infertility, late metritis, and clinical ketosis Ž . Harman et al., 1996b .

3. Consequences of poor reproductive performance

3.1. Lowered milk yield due to reproductiÕe disorders It seems obvious that disease causes milk loss, but surprisingly, some studies have found that increased milk yield is associated with disease. How milk yield is expressed Ž in the analysis is important; a single summary measure of milk yield e.g., 305-day . Ž yield may give a completely different answer than monthly milk yields Detilleux et al., . 1994 . Ž . In one of our studies Rajala and Grohn, 1998b , we estimated the effects of dystocia, ¨ retained placenta, and metritis on milk yield using repeated, monthly test day milk yields taken on 37,776 Finnish Ayrshire cows. All three disorders had a significant effect on milk yield. Their impact varied across parities. Milk losses were greatest immediately following diagnosis. For instance, in parity 2, daily losses from dystocia, retained placenta, and early metritis during the 2 weeks following diagnosis were 2.2, 1.4, and 1.3 kgrday, respectively. There will probably always be some loss of milk yield after a disease. It is important to use proper methodology when quantifying the loss, i.e., it is more accurate to use monthly measurements of milk yield rather than a single, summary lactational measure. Only in this way can true losses be observed. The measurement of loss of milk yield following disease is important. Knowing whether the milk loss due to disease is small and temporary or larger and more sustained helps a farmer decide whether it is worth keeping the cow in the milking herd. 3.2. Shortened productiÕe life Culling is a complex issue: many factors are involved. Dairy cows are culled for Ž . Ž . involuntary i.e., death, acute disease and infertility and voluntary i.e., low yield reasons. Both biology and management affect the culling decision. Reproductive failure Ž . is a major reason for involuntary culling Fetrow, 1988 . However, when making a decision, the dairy farmer considers at least five major reasons: parity, milk yield, stage of lactation, diseases, and conception status. Using survival analysis with time-dependent covariates, we studied the effect of seven diseases on culling in New York Holsteins. The effects of milk yield and conception status on culling were also studied, and the interactions between these Ž . covariates and stage of lactation were accounted for Grohn et al., 1998 . Cows that had ¨ not yet conceived, as well as older cows and cows with certain diseases, had a higher Ž . risk of culling. For instance, open cows i.e., before conception were seven-and-a-half times more likely to be culled than pregnant cows. We have also conducted a series of studies on Finnish Ayrshires, of increasing complexity, starting with only disease effects on culling in the model, then adding Ž pregnancy status effects, and finally adding milk yield effects Rajala-Schultz and . Grohn, 1999a,b,c . All models also included parity, calving season, and herd as ¨ covariates. Pregnancy status was the most influential factor affecting culling decisions, followed by milk yield. Several diseases also significantly affected culling. The effects of all these factors varied with the stage of lactation. Dystocia and metritis increased the risk of culling at the time of their occurrence, but also at the end of lactation. Ovarian cysts and anestrus also affected culling decisions. For instance, if a cow had been diagnosed with ovarian cysts or anestrus within 150 days after calving, she was less likely to be culled than a cow without these disorders. Here, it is important to remember that in Finland diagnoses are made by veterinarians and by calling a veterinarian to a farm, the farmer has already made a preliminary decision to treat and keep the cow. Of Table 3 Effects of pregnancy status and number of inseminations on culling in 39,727 Finnish Ayrshire cows calving in 1993. The model also included parity, season, and herd Pregnancy status a Ž . Ž . Lactational stage of culling day Lactational stage of conception day Risk ratio 0–150 0–150 1.0 UUU 25.8 151–240 0–150 1.0 UUU 151–240 1.3 UUU 1.6 241–305 0–150 1.0 UUU 151–240 2.1 UUU 241–305 2.6 UUU 4.9 305 0–150 1.0 UUU 151–240 1.7 UUU 241–305 2.9 UUU 305 3.8 UUU 23.9 Number of inseminations UUU 10.0 1 1.0 UUU 2 0.9 U 3 0.9 UU 3 0.9 a Stage of lactation when the farmer was assumed to know when a cow was pregnant; 0 refers to open cows Ž . i.e., cows that did not conceive at all . U p- 0.05. UU p- 0.01. UUU p- 0.001. the 15 diseases studied, retained placenta was the only disorder without an effect on culling. Effects of pregnancy status and number of inseminations on culling of Finnish Ayrshires are in Table 3. The data are expressed as risk ratios, which measure the risk of a cow being culled depending on the time when she was known to be pregnant Ž . compared with a reference level i.e., pregnant by day 150 after calving, RR s 1.0 . The knowledge about a cow’s pregnancy status had a different effect on culling at different stages of lactation. The later the cow conceived, the higher was the risk of her being culled. Cows not inseminated at all were at 10 times higher risk of being culled than cows inseminated only once. Cows inseminated more than once were slightly less likely to be culled than cows inseminated only once.

4. Economic optimization of reproductive performance