C. Inchaisri

Analysis of the economically optimal voluntary waiting period for first insemination

The voluntary waiting period (VWP) is defined as the time between parturition and the time at which the cow is first eligible for insemination. Determining the optimal VWP from field data is difficult and unlikely to happen. Therefore, a Monte-Carlo dynamic-stochastic simulation model was created to calculate the economic effects of different VWP. The model is dynamic and uses time steps of 1 wk to simulate the reproductive cycle (ovulation, estrous detection, and conception), the occurrence of postpartum disorders, and the lactation curve. Inputs of the model were chosen to reflect the situation of Dutch dairy cows. In the model, we initially created a cow of a randomly selected breed, parity, month of calving, calf status of last calving, and expected 305-d milk yield. The randomly varied variables were based upon relevant distributions and adjusted for cow statuses. The lactation curve was modeled by Woods function. The economic input values in the analysis included: cost of milk production (€0.07 to €0.20 per kg), calf price (€35 to €150 per calf), AI cost (€7 to €24 per AI), calving management cost (€137 to €167 per calving), and culling cost, expressed as the retention pay-off (€118 to €1,117). A partial budget approach was used to calculate the economic effect of varying the VWP from 7 to 15 wk postpartum, using a VWP of 6 wk as reference. Per iteration, the VWP with either the lowest economic loss or the maximum profit was determined as the optimal VWP. The optimal VWP of most cows (90%) was less than 10 wk. On average, every VWP longer than 6 wk gave economic losses. Longer VWP were in particular optimal for the first parity of breeds other than Holstein-Friesian, cows calving in winter with low milk production, high milk persistency, delayed peak milk yield time, a delayed time of first ovulation, or occurrence of a postpartum disorder, and while costs of milk production are low and costs for AI are high.

Effect of milk yield characteristics, breed, and parity on success of the first insemination in Dutch dairy cows

The objective of this study was to determine the contribution of cow factors to the probability of a successful first insemination (SFI). The investigation was performed with 51,791 lactations from 1,396 herds obtained from the Dutch dairy cow database of the Cattle Improvement Co-operative (CRV). Cows that had the first insemination (AI) between 40 and 150 d postpartum were selected. The first AI was classified as successful when cows were not reinseminated and either calved between 267 and 295 d later or were culled within 135 to 295 d after first AI. The lactation curve characteristics of individual lactations were estimated by Wilminks curve using the test-day milk records from CRV. The lactation curve characteristics (peak milk yield, milk yield at the first-AI date, time of peak yield (PT), and milk persistency) were calculated. Breed, parity, interval from calving to first AI (CFI), lactation curve characteristics, milk production traits, moment of AI related to PT (before or after PT), calf status, month of AI, and month of calving were selected as independent variables for a model with SFI as a dependent variable. A multivariable logistic regression model was used with farm as a random effect. Overall SFI was 44%. The effect of parity on SFI depended on CFI. The first-parity cows had the greatest SFI (0.43) compared with other parities (0.32-0.39) at the same period of CFI before 60 d in milk (DIM), and cows in parity ≥5 had the least SFI (0.38-0.40) when AI was after 60 DIM. After 60 DIM, extending CFI did not improve SFI in the first-parity cows, but SFI was improved in multiparous cows. Holstein-Friesian cows had lesser SFI (0.37) compared with cross-breed cows (0.39-0.46). Twin and stillbirth calving reduced SFI (0.39) compared with a single female calf (0.45) or a male calf (0.43) calving. The SFI in different months of AI varied and depended on CFI. Cows that received AI before 60 DIM had a lesser SFI, especially in March, June, and July (0.18, 0.35, and 0.34, respectively). Artificial insemination before PT reduced SFI (0.39) in comparison with AI after PT (0.44). The effect of milk yield at the first-AI date on SFI varied depending on CFI. After 60 DIM at the same period of CFI, a high level of milk yield at the first-AI date reduced SFI. In conclusion, knowledge of the contribution of cow factors on SFI can be applied to support decision making on the moment of insemination of an individual cow in estrus.

Cow Effects and Estimation of Success of First and Following Inseminations in Dutch Dairy Cows

The objective of this research was to determine the contribution of cow factors to the probability of successful insemination accounting for the serial number of inseminations in analysis. The investigation was performed with 101,297 insemination records in 51,525 lactations of different cows from 1368 herds obtained from the Dutch milk production recording database. Cows that had a first insemination (AI) between 40 and 150 days post-partum with one or more inseminations (≤6 inseminations) were selected. An insemination was defined successful when not followed by another insemination and when the cow calved between 267 and 295 days after insemination, or when the cow was culled between 135 and 295 days after the last insemination. Breed, parity, days in milk, lactation curve characteristics, milk production traits, moment of AI related to peak milk yield time (before or after peak milk yield), the last calf (female, male, twin or stillbirth) and season of insemination were selected as independent parameters for a model with successful rate of insemination as dependent parameter. A multivariable logistic regression model was used within cow and farm as a random effect. The probability of successful insemination was the highest in the first insemination and decreased in the following inseminations. However, the success rate of all inseminations increased in a later stage of lactation. The improvement in the successful inseminations in a later stage of lactation was better in multiparous cows than in first parity cows. Insemination in summer and before peak milk yield time reduced the success of insemination. The success rate was the lowest in 100% Holstein Friesian cows compared with other breeds and was the highest when the last calf was a female calf compared to a male calf, twin or stillbirth. In conclusion, the success of first and following inseminations depended on parity, breed, season of insemination, last calf status, daily milk yield at insemination date, serial insemination number and days in milk at insemination date.

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.

The effect of a catastrophic flood disaster on livestock farming in Nakhon Sawan province, Thailand

In 2011, a catastrophic flood disaster in Thailand affected not only humans but also took animal lives. Data on livestock losses, including death, loss, and decreased production, were collected in Nakhon Sawan province. The time-series map of the flooded area from August to December 2011 was available online from the Geo-informatics and Space Technology Development Agency. To evaluate the high-density areas of livestock loss, a spatial hot spot analysis was performed. The Getis-Ord Gi statistic with weighted zone of indifference and the Euclidean distance measurement were employed to identify spatial clusters of species that were affected by the flood. The results indicated that the majority of livestock losses were from poultry and swine farms. The density of poultry and swine loss was significantly different between sub-districts with clusters of high-density loss alongside the river, particularly in Chum Saeng and Kao Liew. Using spatial hot spot analysis as a tool to classify and rank the areas with high flood risks provides an informative outline for farmers to be aware of potential flood damage. To avoid unexpected loss from flooding, poultry and swine farms in risk areas should be properly managed, particularly during the flooding season between August and December.