The aim of the reproductive management of dairy farms is to keep low the days in milk (DIM). Milk production can be profitable only in that case. Calvings make only low DIM. From the economic point of view, to evaluate the amount of the calving is not simple because in many cases the insemination and the calving are not in the same year. We wanted to find a reproduction parameter, which is easy to record, available real time, and corrrelate well with other parameters. We collected reproduction data from 21 farms from 2016. Average numbers of cows, number of the ai (artificial insemination) in cows, number of cows pregnancies, open days (OD), service period (SP), time of first ai (TFAI), conception rate of first ai (CRFAI), conception rate of all ai (CRSAI) were collected. The number of the pregnant cows were grouped, pregancies under 120 days after calving -U120- and pregnancies above 200 -A200- days after calving. The economical effect of open days are well-known. OD correlated with the rate of the pregnancies under 120 days after calving (r = -0.802; P ≤ 0.001). The open days correlated with the rate of the pregnancis above 200 days after calving (r = 0.889; P ≤ 0.001). If the rate of U120 is high, the rate of pregnant cows (ROPC) will be high too (r = 0.611; P = 0.003). A200 is in negative relation with ROPC (r = -0.525; P = 0.015). OD correlated with TFAI (r = 0.562; P = 0.008). ROPC correlated with TFAI (r = -0.457; P = 0.037). OD correlated with SP (r = 0.778; P ≤ 0.001). SP is in negative correlation with CRFAI and CRSAI (r = - 0.577, P = 0.006; r = - 0.773, P ≤ 0.001). SP correlated with U120 and A200 (r= - 0.572, P = 0.007; r = 0.788 P ≤ 0.001). Our study shows that the rate of the pregnant cows are stasistically correlated with many important reproduction parameters. The measurement of the number of pregnant cows is easy, available real time and it has important economical effect on milk production. In summary, the number of pregnant cows is a useful parameter to evaluate the reproductive performance and current status of the farms.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.