Economic consequences of reproductive performance in dairy cattle

The net economic value of reproductive efficiency in dairy cattle was estimated using a stochastic dynamic simulation model. The objective was to compare the economic consequences of reproductive performance scenarios (“average” and “poor”) of a cow having a good reproductive performance and to explore which reproductive factors have an important impact on economic efficiency. A “good” reproductive performance scenario was defined with 1 ovulation rate (POVUi), 0.7 estrus detection rate (PEst), 0.7 conception rate (PCon), 0.03 incidence rate of postpartum disorders prolonging the ovarian cyclicity (CO), 0.2 incidence rate of postpartum disorders reducing conception (ME), 0.05 embryonic death rate (ED), and voluntary waiting period (VWP) of 9 wks pp (post partum). In the current situation of dairy cows in the Netherlands, an “average” reproductive scenario (0.95 POVUi, 0.5 PEst, 0.5 Pcon, 0.07 CO, 0.27 ME, 0.07 ED and VWP of 12 wks pp) and a “poor” reproductive scenario (0.90 POVUi, 0.3 PEst, 0.3 Pcon, 0.11 CO, 0.33 ME, 0.09 ED and VWP of 15 wks pp) were identified. A sensitivity analysis was performed by comparing changes of single effect of factors in a good and poor scenario with the average scenario. The mean net economic loss (NELi) compared with the good scenario was €34 and €231 per cow per year for the average and poor reproductive performance scenario, respectively. Increasing the calving interval resulted in greater economic loss. The important factors on the cost of reproductive efficiency were the involuntary culling cost and the return of milk production. Variation in PCon, PEst, ME, ED, and VWP had large impacts on economic benefits. Keywords: Dairy cow; Reproductive performance; Simulation model; Economic

Особливості викладання курсу політології у вищих військових навчальних закладах України

Висвітлюються проблеми та специфіка викладання курсу “Політологія” для курсантів та студентів Львівського військового інституту Сухопутних військ Збройних сил України.The problems and specific features of teaching the course “Political Science ” for cadets and students of Lviv Military institute of Infantry Military Forces of Ukraine have been regarded

Bio-economic modeling to support insemination decisions in dairy cows

To achieve the optimal economic profit, the effort to increase milk production in a dairy cow has been generated. As a consequence of an increased milk production, it appears that the conception rate has been reported to decline during the last decade worldwide. For the optimal economics and to avoid effort for the lower conception rate in early lactation, the extension of calving interval has been suggested to be later than 12 to 13 months. However, the complexity of interactions and dynamics of factors influencing reproductive performance do influence seriously the determination of an economically optimal time to start and to stop insemination. The main objective of this thesis was to develop bio-economic models which support decision on inseminating dairy cows. The epidemiological data generated in, empirical, epidemiological studies were integrated in our simulation models. As a consequence, the first simulation model could be used to support decisions for the optimal time to start insmeination with taking more specific cow factors into account. Moreover, using the second simulation model, it was proven that the insemination number has an effect on the optimal time to stop inseminating

A cow-level association of ruminal pH on body condition score, serum beta-hydroxybutyrate and postpartum disorders in Thai dairy cattle

Subacute ruminal acidosis in dairy cows occurs when ruminal pH is below about 5.5. However, the exact threshold level of ruminal pH affecting cow health is still in debate. This investigation was carried out in 505 cows within 31 farms. The postpartum disorders, including dystocia, retained placenta, anestrus, cystic ovary, metritis, clinical mastitis and lameness, were analyzed. Ruminal pH, serum beta-hydroxy butyrate (SBHB), serum urea nitrogen and body condition score (BCS) were measured once during the 3 to 6 weeks postpartum, while BCS was determined once more at 1 week before calving. Ruminal pH was determinded by ruminocentesis technique. The ruminal pH was evaluated to study the association with BCS, SBHB and postpartum disorders using linear regression in a generalized linear mixed model with farm as a random effect. The results show that low ruminal pH was associated with dystocia, metritis and lameness. Moreover, a low ruminal pH can be found in cows with a high loss of BCS after calving and also in cows with low SBHB postpartum. These findings confirmed the feasibility of the ruminocentesis technique and the association of low ruminal pH on various postpartum disorders at the individual cow level. However, the consequences of low ruminal pH on dairy cow health still needs more exploration for a better understanding of the physiological mechanisms

An ex ante analysis on the use of activity meters for automated estrus detection, to invest or not to invest?

The technical performance of activity meters for automated detection of estrus in dairy farming has been studied, and such meters are already used in practice. However, information on the economic consequences of using activity meters is lacking. The current study analyzes the economic benefits of a sensor system for detection of estrus and appraises the feasibility of an investment in such a system. A stochastic dynamic simulation model was used to simulate reproductive performance of a dairy herd. The number of cow places in this herd was fixed at 130. The model started with 130 randomly drawn cows (in a Monte Carlo process) and simulated calvings and replacement of these cows in subsequent years. Default herd characteristics were a conception rate of 50%, an 8-wk dry-off period, and an average milk production level of 8,310 kg per cow per 305 d. Model inputs were derived from real farm data and expertise. For the analysis, visual detection by the farmer (“without” situation) was compared with automated detection with activity meters (“with” situation). For visual estrus detection, an estrus detection rate of 50% and a specificity of 100% were assumed. For automated estrus detection, an estrus detection rate of 80% and a specificity of 95% were assumed. The results of the cow simulation model were used to estimate the difference between the annual net cash flows in the “with” and “without” situations (marginal financial effect) and the internal rate of return (IRR) as profitability indicators. The use of activity meters led to improved estrus detection and, therefore, to a decrease in the average calving interval and subsequent increase in annual milk production. For visual estrus detection, the average calving interval was 419 d and average annual milk production was 1,032,278 kg. For activity meters, the average calving interval was 403 d and the average annual milk production was 1,043,398 kg. It was estimated that the initial investment in activity meters would cost €17,728 for a herd of 130 cows, with an additional cost of €90 per year for the replacement of malfunctioning activity meters. Changes in annual net cash flows arising from using an activity meter included extra revenues from increased milk production and number of calves sold, increased costs from more inseminations, calvings, and feed consumption, and reduced costs from fewer culled cows and less labor for estrus detection. These changes in cash flows were caused mainly by changes in the technical results of the simulated dairy herds, which arose from differences in the estrus detection rate and specificity between the “with” and “without” situations. The average marginal financial effect in the “with” and “without” situations was €2,827 for the baseline scenario, with an average IRR of 11%. The IRR is a measure of the return on invested capital. Investment in activity meters was generally profitable. The most influential assumptions on the profitability of this investment were the assumed culling rules and the increase in sensitivity of estrus detection between the “without” and the “with” situation

Improved Knowledge About Conception Rates Influences the Decision to Stop Insemination in Dairy Cows

The conception rate in dairy cows is dependent on a number of cow factors such as days in milk and insemination number. Unfortunately, some of these factors were not accounted for in optimal insemination and replacement decision models. By using wrong estimates of the conception rate, the calculated optimal insemination and replacement policy might differ from the real optimal insemination and replacement policy. The objective of this study was to evaluate different sets of conception rates with an increasing level of accuracy to determine the insemination policy. An existing dynamic program for optimal insemination and replacement was used to compare three different scenarios in the estimation of conception rates, based on the reproductive performance of Dutch dairy cattle: (i) constant conception rate throughout lactation, (ii) conception rate dependent on parity and months in milk, and (iii) conception rate dependent on parity, months in milk and insemination number. The time step of the model was 30.4 days (1 month). The discounted future cash flow of culling a cow at each time step (replace a heifer immediately) was compared with keeping that cow under optimal future decisions. The difference between immediate culling and optimal decisions is defined as the retention pay-off. The insemination value was calculated as the difference between the future cash flow between immediate insemination of a cow and waiting one time-step. The results show that the difference in the insemination values and the optimal time to stop insemination depend on parity, lactation stage and the relative milk yield. In older cows with equal milk yields and at the same months in milk, the insemination value was lower than in younger cows. Within a parity, the insemination value was higher for cows with a higher milk yield. On individual cow level, using more accurate conception rate as input in the optimal insemination and replacement model might reduce miscalculation of the economic consequences for at least of €20–€38 per cow per year. Basing insemination decisions on less accurate input of the probabilities of conception, however, did not have an economic consequence at the herd level. In conclusion, using the appropriate conception rate as input in the optimal insemination and replacement model would increase the precise decision for the optimal time to stop insemination and hence improve the reproductive management efficacy