Evaluation of the health status of Holstein dairy cows in terms of the possibility of mastitis and ketosis diseases by biomarkers in milk

Introduction: Mastitis and metabolic diseases, including mastitis and ketosis, are among the most important diseases from an economic point of view in the dairy cattle industry, which cause a decrease in milk production, treatment costs, a decrease in the genetic progress of the herd, and a decrease in milk quality.Today, due to the increasing demand of consumers for healthy products, attention to animal health is of increasing importance. Cows that do not receive an appropriate proportion of energy in their diet are prone to diseases (Akbarpanah 2018). By controlling common diseases, it is possible to reduce the costs of disease, improve animal welfare, and increase the health and quality of livestock products (Bifa et al. 2005). Today, livestock breeding is moving more towards genetic modification for greater relative resistance to diseases and subsequently increasing the economic lifespan of the animal (Altenako et al. 2010). For this purpose, one of the strategies that is more or less recommended as a management tool today is the use of markers to predict the health of cows in the peri-calving period, especially developed for the management and monitoring of cow health (Costa et al. 2019).Objective: This study was to identify environmental factors and fixed effects to predict the development of mastitis and ketosis in Holstein dairy cows. Material and methods: Milk samples were taken from 1020 Holstein dairy cows, and milk parameters were measured by milk analysis devices using FT-MIR spectra, and the data were analyzed by SAS software. Logistic regression was used to examine the effect of factors on the incidence of mastitis and ketosis. Results and discussion: The results of Spearman's correlation between the traits of fat percentage, fat to protein ratio and lactose percentage with mastitis (disease= 1 and healthy = 0) showed a negative and significant correlation (P < 0.05), which were (-0.49), (-0.47) and (-0.33), respectively, and a positive correlation with the number of somatic cells (0.51). Spearman's correlation for the traits of milk urea, beta-hydroxybutyrate, and milk acetone and NEFA and with ketosis showed a positive and significant correlation, which were (0.35), (0.35), (0.37) and (0.38), respectively. Logistic regression coefficients showed that mastitis has a significant relationship with the biomarker parameters of fat percentage and somatic cell count (P < 0.0001). Ketosis have a significant positive relationship with the parameters of fat to protein ratio and beta-hydroxybutyrate and milk quantity (P<0.05). Based on the odds ratio, the main factors affecting ketosis were the ratio of fat to protein, beta-hydroxybutyrate and milk yield. Ketosis has a significant positive relationship with these parameters. Due to the economic consequences of ketosis, determining cows with clinical and subclinical forms of the disease is of great importance, and the results of some diagnostic tests, in addition to clinical examinations, can be used to improve management performance and prevent it; for this purpose, measuring beta-hydroxybutyrate in serum or plasma is used as the golden test for diagnosing this disease (Sakha et al., 2007). On the other hand, this disease will also increase the incidence of other peripartum diseases. Both clinical and subclinical ketosis can be associated with the occurrence of uterine diseases (Sakha et al., 2012). Studies have shown that ketone bodies affect white blood cells and indirectly affect the immune system (Radostis et al. 2007). BHB is used as the ketone body of choice to assess the body's energy status. It is considered a measure of negative energy balance rather than a nutritional indicator. Beta-hydroxybutyrate is increased in cases of negative energy balance, which may be due to a lack of dietary carbohydrates (Herdt 2000). Conclusion: Finding better strategies for prevention and early identification of animals at risk of health and production challenges may significantly prevent the occurrence and spread of disease or help in early treatment of animals. For this purpose, one of the strategies that is more or less recommended today as a management tool is monitoring milk components with the help of devices that examine milk components with the aim of relatively predicting the disease. Therefore, new biomarkers with higher sensitivity are helpful in predicting the diagnosis of subclinical bovine mastitis and ketosis. Without a doubt, mastitis and ketosis are the most important diseases of the dairy cattle industry that can cause significant economic losses. Regardless of the reduction in production and treatment costs, these diseases can lay the groundwork for the occurrence of many other disorders and economic losses caused by them. In such circumstances, the best way to prevent the losses caused by these diseases is to provide practical solutions to prevent the occurrence of diseases. Therefore, by measuring the concentrations of non-esterified fatty acids and beta-hydroxybutyrate, fat parameters and the number of somatic cells, the time of disease occurrence can be predicted. A a general conclusion we propose by adopting management measures, the occurrence of mastitis and ketosis diseases could be prevented.
Introduction: Mastitis and metabolic diseases, including mastitis and ketosis, are among the most important diseases from an economic point of view in the dairy cattle industry, which cause a decrease in milk production, treatment costs, a decrease in the genetic progress of the herd, and a decrease in milk quality.Today, due to the increasing demand of consumers for healthy products, attention to animal health is of increasing importance. Cows that do not receive an appropriate proportion of energy in their diet are prone to diseases (Akbarpanah 2018). By controlling common diseases, it is possible to reduce the costs of disease, improve animal welfare, and increase the health and quality of livestock products (Bifa et al. 2005). Today, livestock breeding is moving more towards genetic modification for greater relative resistance to diseases and subsequently increasing the economic lifespan of the animal (Altenako et al. 2010). For this purpose, one of the strategies that is more or less recommended as a management tool today is the use of markers to predict the health of cows in the peri-calving period, especially developed for the management and monitoring of cow health (Costa et al. 2019).Objective: This study was to identify environmental factors and fixed effects to predict the development of mastitis and ketosis in Holstein dairy cows. Material and methods: Milk samples were taken from 1020 Holstein dairy cows, and milk parameters were measured by milk analysis devices using FT-MIR spectra, and the data were analyzed by SAS software. Logistic regression was used to examine the effect of factors on the incidence of mastitis and ketosis. Results and discussion: The results of Spearman's correlation between the traits of fat percentage, fat to protein ratio and lactose percentage with mastitis (disease= 1 and healthy = 0) showed a negative and significant correlation (P < 0.05), which were (-0.49), (-0.47) and (-0.33), respectively, and a positive correlation with the number of somatic cells (0.51). Spearman's correlation for the traits of milk urea, beta-hydroxybutyrate, and milk acetone and NEFA and with ketosis showed a positive and significant corre