Investigation of Maximizing Profit in Dairy Herds with Production System Optimization Approach

Introduction: In the livestock industry around the world, most decisions are about increasing profitability per head, which is not an independent process and is affected by the interactions of biological functions such as (production, reproduction and health) and prices that are changed by policy. Replacement and breeding affect profitability (Nasre Esfahani, 2018). Issues such as feed price fluctuations and the lack of coherent policies to support the dairy industry in the country have made the profession one of the most risky jobs in the economy. When a producer wants to make the decision to remove or replace a cow, it is best to compare the future benefits and expected benefits of keeping a cow or replacing an animal with another. The most important objective of a livestock unit is to maximize the profit of the herd, one of the issues affecting this profit is the criteria and rate of elimination (Rogers et al,1988). If culling and replacement are not optimal, the cows are removed sooner or later than the optimal deadline, the profitability of the herd decreases. The need to determine the optimal time to remove cows requires simultaneous consideration of several biological and economic variables (De Vries,2006). The removal decision must be based on the anticipated future earnings of the cow. The longer the livestock has a livelihood in the herd, the more profit the livestock earns. The decision to properly, optimally and reasonably eliminate livestock is made by comparing the present value of the future cash flow of the cow present in the herd to the present value of the future cash flow of its replacement heifers, ultimately occupying the most valuable animal in the present (Groenendall et al,2005). The application of dynamic programming in the animal sciences is more on animal substitution issues. The optimal policy at each stage represents the best decision from that stage to the final stage. This method calculates an expected value for each of the situations that can be faced and the decision maker selects the best decision based on the expected value based on the situations ahead. Several dynamic programming models for optimal replacement decision making in dairy herds have been proposed by (De Vries,2004) and (Van Arendonk,1985). (Cardoso et al,1999) reported optimizing replacement and inoculation policies in dairy cows by calculating monthly income, costs and probability of elimination.
Material and methods: In this study, using raw data collected from industrial dairy farms of Ardabil between 2015 and 2018, the biological parameters of the herd, such as the shape of the lactation curve, the risk of forced removal and the possibility of pregnancy in different lactation periods and Different months after calving were estimated. The financial information of the herd was also obtained in the form of an economic questionnaire from the studied units. It was further developed by incorporating biological parameters and financial information into a bio economic model in Dairy Vip software. The feature of this software is that it simulates the livestock over time and also calculates the performance of the herd based on breeding and replacement decisions with the goal of maximizing profitability. Milk production was evaluated using daily milk production records and fitting the incomplete gamma curve (Wood). Dairy Vip software defined average daily milk production levels in the herd by entering lactation data (raw milk quantity, incremental milk slope to peak production and milk slope decrease until peak production). Mean milk yield of 305 days at first to third lactation and peak lactation was reported in Table 1.The mean 21-day inoculation rate and cattle breeding rate were 49.3% and 37%, respectively. By default Dairy Vip software, a maximum livestock can be in the herd 24 months after calving. The risk of fetal loss from the second to the eighth month was 6.24, 4.16, 2.08, 1.11, 0.45, 0.19, and 0.19 percent, respectively. A Dynamic programming model was developed to determine the optimal replacement policy for cows in dairy farms and in economic conditions in Ardabil province. The objective function investigated in this study was to maximize the present value of net income from current cows and alternative heifers. Markov chain simulation was used to estimate the expected statistics under optimal policy.
Results and discussion: The implications of the decision policies for optimum and non-optimum removal using Dairy Vip software are presented in Table 3. With the implementation of optimal policies, the overall annual removal rate increased from 30.11% to 43.8%. However, the forced removal rate fell by 2.3%. Pregnancy rate increased from 18/15 to 18.2% and increased by 2.89%. Based on the above results, it can be inferred that the economic importance of increasing the pregnancy rate is more urgent in herds with poorer reproductive performance. Also, the non-optimal catch rate dropped from 33.9% to 37%, indicating an increased likelihood of livestock being pregnant in different months. The 21-day inoculation rate ranged from 47.6 to 49.3%, indicating appropriate cow inoculation. By reducing the days of gestation in dairy cows can increase milk production, which in this study reduced the optimal days of gestation from 139 days to 132 days, which resulted in a significant 7-day decrease in milk production and finally annual. Open days are the interval from birth to the next gestation period, from 167 days to 161 days. With the decline in pregnancy, the rate of pregnancy increased. Calving distance also decreased from 13.6 to 13.3, which was reduced to 0.3 per month, which in turn increased annual milk production. As shown in Table 3, the optimal daily milk yields were increased from 41.4 to 44.2 by the optimal policies, which increased the daily milk yield by 3 kg per cow. And the annual yield of milk increased from 12548 to 13483 kg per cow. Reducing the average days of lactation increased the daily and annual production of productive cows by 3 and 935 kg, respectively.
Conclusion: Decisions to optimize voluntary removal and estimation of livestock value by computer simulation in Dairy VIP software enable improved economic returns. This improvement is due to the decrease in average lactation days in the herd resulting in increased milk production, cattle sales and calf production. Although the implementation of optimal policies is associated with increased livestock removal and replacement costs and increased feed costs, however, the increased revenue from implementing these policies could well offset the increased costs. In general, it can be concluded that increasing milk production in medium-sized cows is the most important factor in increasing economic profit. The results of this study showed that low-yielding animals showed their least future benefit in early lactation, indicating that they should be eliminated sooner.