Document Type : Research Paper
Authors
1 PhD student, department of Animal Science, College of Agriculture, Isfahan University of Technology, Isfahan 84156-83111. Iran
2 Professor, Department of Animal Science, College of Agriculture, Isfahan University of Technology, Isfahan 84156 - 83111, Iran.
3 Assistant Professor. Department of Animal Science, College of Agriculture , Isfahan University of Technology, Isfahan, I.R. Iran
4 Associate Professor, Department of Animal Science, College of Agriculture , University of Tehran, ،Tehran, I.R. Iran
Abstract
Objective: Production, economic, and nutritional metrics are used in the dairy farming industry to maximize profitability and enhance decision-making. The largest share of herd economics is represented by feed costs and milk income. Milk pricing methods in Iran are challenging due to ignoring milk quality and composition. For analyzing profit margins and optimizing herd management, indices such as income over feed cost, milk corrected money, and income equal to feed cost can be used. This study aims to investigate the profitability of Holstein dairy herds in Isfahan province using technical-economic indices and evaluate the impact of different milk pricing scenarios on profitability based on these indices.
Method: In this study, two datasets were used: The first dataset contains 4,637,629 daily records of milk production, fat percentage, protein percentage, and somatic cell count for 255,804 cows in 120 herds in Isfahan province between 2016 and 2024; a second dataset consists of economic data on five selected herds, including prices for milk and feed. The feed cost was estimated using a regression model based on crude protein and net energy of lactation. NRC (2001) standard equations were used to calculate daily energy and protein requirements. Based on the number and level of milk quality components, four pricing scenarios were considered. For each scenario, technical-economic indices were calculated using SQL SERVER (version 18). The statistical analysis of the indices was conducted by SAS (version 9.4). Furthermore, to evaluate the effect of milk quality on profitability in each pricing scenario, the produced milk was graded based on its quality components. To assess the impact of inputs such as milk production, fat and protein percentages, as well as milk and feed prices on technical-economic indices, a sensitivity analysis was conducted using Microsoft Excel (version 2021).
Results: The average price for each megacalorie of energy and each gram of protein was calculated at 44,215 and 222 Rials, respectively. The income over feed cost per cow per day was estimated at 2,823,520 Rials, with a range of -549,000 to 10,398,000 Rials. Isfahan province dairy farmers spend about 52% of milk income on feed cost, based on an average income equal to feed cost of 21.1 kg. The average milk corrected money (41.1 kg) was about 1% higher than the average milk production (40.8 kg). The average milk-to-feed price ratio was estimated at 1.27 (±0.33), with a range of 0.53 to 4.2. Sensitivity analysis revealed that a 10% decrease in feed prices and a 10% increase in milk prices led to a 13-15% and 22-25% increase in the income over feed cost index, respectively. Grouping based on milk quality showed that improvements in the studied indices occurred only in scenarios with higher baseline levels of milk protein and fat.
Conclusion: Based on the results, advanced pricing scenarios, which account for parameters related to milk hygiene quality and provide higher baseline levels for milk components, significantly improve profitability and encourage the production of higher-quality milk. The sensitivity analysis also revealed that fluctuations in milk production, milk prices, and feed prices have the greatest impact on economic indices. Therefore, revising milk pricing methods and incorporating milk quality components into pricing can motivate dairy farmers to produce higher-quality milk and enhance dairy herd profitability.
Keywords
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