Daily Monitoring of Energy Balance
to Improve Decision-Making on a Dairy Farm
Tal Schcolnik DVM, Alon Arazi DVM, Oded Nir BVSc, Afimilk
In recent decades, genetic advancement has improved milk production and composition but has caused cows’ bodies to direct energy resources to milk at the cost of fertility and life span.At the onset of lactation and especially right after calving, cows have very high energy requirements following the extreme increase in milk production. When a cow is unable to consume enough energy from food, excessive body fat mobilization will occur, resulting in loss of body condition, indicating the cow is in a negative energy balance (NEB). As a result, products of body fat degradation find their way mainly to the udder and the liver. In the udder, these free fatty acids (FFA’s) increase the fat to protein ratio. In the liver, FFA’s accumulation alters metabolism, resulting in increased ketone production and lack of available energy (glucose).
There is a direct relationship between body condition deterioration and conception rates in dairy cows, due to disruption in liver metabolism. NEB and body condition score (BCS) loss are related to reduced serum progesterone concentrations during the breeding period and to lower pregnancy rates (Butler, 2003); in addition, conception rate decreases about 10% per 0.5 unit BCS loss, from calving to insemination (Butler, 2012).
Since the physiological condition of any animal is reflected in the components of its body fluids, a dairy cow’s condition is reflected in the composition of its milk. AfiLab (of afimilk, Afikim) is an optic sensor that measures milk composition (fat, protein, lactose and blood) for each cow during every milking. Proper interpretation of milk composition parameters helps improve the herd’s production and reproduction.
The association between negative energy balance, fat to protein ratio in milk, and ketosis
A shortage of available energy (glucose) followed by excessive fat mobilization in the body results in increased fat and decreased protein content in the milk. The rise in milk fat stems from the increased amount of free fatty acids (FFA’s) in the blood. The reduction in milk protein results from a delay in the protein production processes that require energy when there is shortage of available energy.
Ketosis is another biochemical expression of negative energy balance characterized by an abnormal increase of ketones in the blood. This increase is caused by disturbances in the liver’s glucose production process that result from a shortage of volatile fatty acids (VFA’s) from the rumen and the accumulation of FFA’s in the liver cells. The timing and amount of ketones released to the body tissues and their secretion in the urine or milk depend on the rates of metabolic processes of every cow and are mainly influenced by feeding time and ration composition. Therefore, ketones are not necessarily found in the various body fluids of cows at the same time. Consequently, ketone levels are not always compatible with high fat to protein ratio, i.e. NEB.
In 1986 Grieve et al. suggested that an increased milk fat to protein ratio indicates negative energy balance and ketosis. In a study of 42,355 lactations in 132 cooperative Israeli herds calving in the period 2009-2011, we found that the amounts of fat and protein (in percentages of milk kg/180 days) in the cows’ milk in which the fat to protein ratio (FPR) was above 1.4, were greater than 7.7% and lower than 2.6% respectively, than that of cows with a FPR of 1.4 or less (Figure 1).
As a result of the above, we can confidently assume that the FPR in the milk is a parameter that can differentiate cows in negative energy balance and ketosis from those without ketosis. Therefore, this parameter could be used to identify cows with negative energy balance and ketosis that require treatment.
Damage resulting from negative energy balance and ketosis
Damages from negative energy balance and clinical/sub-clinical ketosis are similar. The damages are expressed in impaired milk production, reduction of fertility and lower chances of survival in the herd. A number of studies have examined the influence of negative energy balance and/or ketosis on cows’ performance. Results are summarized below in Table 1.
Table 1: Damage from Ketosis and Negative Energy Balance
The Distribution of Negative Energy Balance and Ketosis in Different Lactations and Dairy Farms
In cows, the timing and duration of the period after calving in which the FPR is high indicates an increased mobility of body fat. This differs between different lactations, both among herds and within the same herd. To efficiently treat and reduce damages, daily monitoring during the high risk period (to about 60 DIM) is required.
Figure 2 shows an example of a herd in which cows in the first and third or later lactation are in negative energy balance (high FPR) at the beginning of the lactation (until 30 DIM), while cows in the second lactation are influenced mostly at a later stage (30-45 DIM).
Diagnosing and Treating Ketosis
In diagnosing ketosis on the dairy farm, ketone levels in the blood, milk or urine are normally checked. Ketone tests are advantageous in diagnosing ketosis because they consist of direct measurements of ketone concentrations in the body fluids. However, these are discrete measurements conducted at specific times, usually during a veterinarians’ visit. In diagnosing a ketosis event, the day and time of examinations affect test results, as increased ketone concentrations in body fluids depend on their release, in pulses, from the liver. The ketones’ release from the liver is influenced by feeding times and composition of the ration, milking time, and circadian rhythms (duration of day and night).
In a study we conducted at a northern Israeli dairy herd, the blood ketone concentrations of 18 cows (5 to 45 DIM) were measured three times a day (after each milking). According to the acceptable threshold for diagnosing ketosis (levels of BHBA higher than 1.4 mmol/L), we diagnosed two of the cows with ketosis in the morning, while during the afternoon and evening hours, the number of cows with ketosis rose to five and six respectively (Figure 3). On the same day we diagnosed a total of seven ketotic cows. No single measurement timing included all the affected cows together. On another farm, we tested the cows only after morning and afternoon milkings; most ketotic cows were diagnosed during the morning examination. This shows that there is no clear advantage to a specific time for examination and diagnosis of ketosis. We can assume that according to today’s methods of examination, only two of seven cows would have been diagnosed and treated. It appears that discrete measurements, as accurate as they may be, do not suffice in monitoring and diagnosing ketosis and negative energy balance in dairy cows.
Diagnosis of Ketosis with the AfilabTM
Diagnosis of ketosis according to daily FPR values, measured by AfilabTM is a challenge because FPR is a continuous variable (scale) while a clear cut point (threshold) is needed for diagnosis. Moreover, reproducibility and repeatability are not constant due to variations in biologic values. Various thresholds of FPR & BHBA were suggested for the diagnosis of clinical and sub clinical ketosis.
Between 2006 and 2012, we conducted four field studies in different commercial Israeli dairy farms, in order to develop a model for diagnosing ketosis. Diagnosis was based on the FPR as measured by AfiLab at every milking. In these studies, the cows’ blood ketone levels were examined three to four times a week for periods ranging between one to ten weeks (total 4,000 samples of BHBA).
Overcoming the sensitivity/specificity conflict and the biological variations with 2 models (Simultaneous Testing)
We used two models in which the “gold standard” was serum BHBA >1.4 mmol/l in one of the days from day – 1 to day +1 with FPR > 1.4 (default) or a calculated threshold (considering lactation and DIM) in 3 consecutive milking sessions. The final outcome is a daily list of cows, 5 to 60 DIM, to be treated for ketosis.
The combined model that was developed based on these studies enables the diagnosis of ketotic cows at a respective specificity and sensitivity of 85%. In simultaneous testing, sensitivity increases and specificity decreases. Results of additional field trials vary according to biological variations. In the software (AfiFarm, afimilk), sensitivity and specificity can be adjusted to a specific farm needs.
By applying the knowledge gained from the study, along with models developed in AfiFarm dairy management software, dairy herd managers/health supervisors are equipped with a special tool box. These tools improve decision-making regarding the treatment and prevention of energy imbalances in the herd. Every day the system turns out an updated list of cows that require treatment according to the dairy’s protocol.
The main advantage of the system is that it combines highly specific and sensitive parameters (fat to protein ratio) in relation to ketosis, together with continuous control capability (at every milking) of negative energy balance. This enables ongoing monitoring after calving for the early detection and prompt treatment of sick cows. Early treatment helps reduce damages from the disease. This contrasts with diagnoses based on measurements that are not specific to ketosis (such as milk yield, activity habits and eating behavior) which usually show high sensitivity but low specificity. Without additional disease-specific examination these elements cannot indicate the required treatment.
Minimizing Damages from Negative Energy Balance when Correctly Using the System
Loss of profits caused by NEB stems from three main elements: reduction in milk production, poor fertility performance and increased involuntary culling of cows. In an examination of 42,355 lactations in 132 Israeli dairy farms between 2009 and 2011, we found the average annual economic damage to be 100.7 NIS (~US$28) per cow in the herd. Nevertheless, in different dairies, the economic damage may be twice or even three times as great.
In an examination of a dairy that does not have an AfiLab system we found that damage from NEB in 2012 was on average 335 NIS (~US$95) per cow in the herd per year. This was mainly attributed to losses in milk production and fertility. A similar examination over a comparable period of time of a dairy using AfiLab data to diagnose and treat cows with negative energy balance and ketosis, showed very low economic damage: about 15 NIS (~US$4.2) per cow in the herd over a year. This was due only to open days (Figure 4).
The way cows get through the transition period directly and indirectly influences production, fertility and survival in subsequent lactation. As a consequence of the high energy requirements involved in producing milk, many cows suffer from negative energy balance after calving at different times and for varying durations (up to 60 days). Monitoring, diagnosis and the early treatment of cows are critical to the herd’s future and to optimal production and fertility.
The fat to protein ratio in milk is an efficient parameter in diagnosing cows suffering from negative energy balance and ketosis. Automatic daily measurements of milk composition allow for effective monitoring during the risk period, early diagnosis and preemptive treatment.
Based on research conducted in recent years in a number of dairies in Israel, we developed a model that uses AfiLab data (fat and protein) to monitor cows suffering from negative energy balance and ketosis. The use of this model enables diagnosis and early treatment of cows and leads to improved dairy revenues.
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