The production diseases of the dairy cow are manifestation of the cow’s inability to cope with the metabolic demands of high milk production. While traditionally regarded as encompassing the significant metabolic disorders of dairy cows (hypocalcemia, hypomagnesemia, and ketosis), the term “production disease” has been broadened to include conditions such as retained placenta, displacement of abomasums and laminitis. Most production diseases occur during the first weeks of lactation. The aetiology of these diseases can be traced back to insults that occurred during transition period. Grummer (1995) defined the transition period as 3 weeks pre-partum to 3 weeks after parturition. It is a period marked by changes in endocrine status to accommodate parturition and lactogenesis. Over the past 20 years, our understanding of ‘transition cow’ metabolism and its relationship to the pathogenesis of peri-parturient disease has greatly increased. Thirty to fifty percent of dairy cows are affected by some form of metabolic or infectious disease around the time of calving. There is now significant interest in the critical role peri-parturient disease plays in dairy farm profitability, and in how the risks of such disease and attendant animal culling can be predicted. The risk of many peri-partum diseases of dairy cows is influenced considerably by the nutritional and metabolic status of the animal and in particular, poor adaptation to negative energy balance, is associated with an increased risk of subsequent disease. A metabolic profile is defined as a series of specific analytic tests run in combination and used as a herd based, rather than individual based, diagnostic aid. There are two major objectives for metabolic profiling of dairy transition cows. Firstly, to monitor metabolic health of the herd and the success of current management with the goal of early detection of problems or deviation from the management program and secondly, to identify group of cows at high risk for diseases with the goal of intervention to prevent clinical disease, Blood profiles have frequently been used to assess nutritional status of cows in the transition period. Such profiles have also been used to monitor herd health and to find subclinical disease, and to predict risk of production diseases. Different parameters are required when determining the risk of sub-clinical or clinical disease than when making a diagnosis of disease. Some routinely measured biochemical analytes can be used to predict the development of production diseases in dairy cows. Specific analytes that are either high or low relative to defined reference or ‘cut-point’ values before calving or immediately post-partum can predict the risk of specific or collective peri-parturient disease events. It was shown that measurement of nonesterified fatty acids (NEFA), β-hydroxy butyrate and calcium concentrations in the first and second week post-partum may provide useful supplementary information for herd health monitoring and culling risk. Hyperketonemia in the first week of lactation is an important risk factor for the subsequent diagnosis of dispalsed abomasums, clinical ketosis and metritis. Additionally, there was a relationship between the concentrations of NEFA at calving and the incidence of certain periparturient diseases. Researchers detected a greater decrease in serum cholesterol concentration and increase in NEFA concentration during the transition period in cows developed retained placenta. Serum mineral concentrations are highly dynamic around the time of calving as homeostatic mechanisms are altered to facilitate the onset of lactation and as mineral is lost in colostrum formation. If homeostatic control or reserve mobilisation are unable to maintain normal, physiological mineral concentrations, a variety of peri-parturient metabolic diseases may occur. The studies indicated that cows with total serum Ca concentration within the lower half of the normal range (<2.2 mmol/L) in the first 2 weeks post-partum were at greater risk of both developing DA and being culled within 60 DIM. Whole herd interpretation is best made by calculating a proportion of cows above or below a threshold value.

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