GRAPHIC MONITORING OF THE COURSE OF SOME CLINICAL CONDITIONS IN DAIRY COWS USING A COMPUTERIZED DAIRY MANAGEMENT SYSTEM
U. Moallem, P. Gur, N.Shpigel, E. Maltz, N. Livshin, S.Yacoby, A. Antman and E. Aizinbud
Introduction and review of current literature
Twenty years ago it was recognized that in large commercial livestock enterprises, computerized herd reports were desirable to avoid overloading the farmer and his veterinarian with repetitive tasks of data preparation and analysis (1).
Since the middle of the seventies through parallel developments in microcomputer and electronic technology, Computerized Dairy Management Systems (CDMS) are being increasingly used (2).
The computerization of herd management became more and more acceptable by the dairyman as the software used was screened as user friendly. Both farmer and veterinarian are interested in retrieving and using the information generated by CDMS. Many of them are convinced of the benefits provided by the computer as a basis for a disease surveillance system (3).
CDMS record, process and store data on cows’ performances, behavioral pattern and production oriented health indices. One significant advantage of CDMS is in detecting individual or groups of animals that are not performing as expected, or fall outside of normal limits. Reports on improvements in herd performance as a result of using on-farm CDMS have been recently summarized (1).
Computerization of dairy farms is growing rapidly in countries with developed dairy industries. Larger dairy farms can make better use of the CDMS. Already in 1996, computers were used to manage about half of U.S. cows (4). In Israel, almost all kibbutz farms with about 300 milking cows, and some family-type farms with an average of 50 cows, are equipped with CDMS - made locally by S.A.E. Afikim and SCR, and imported Boumatic or Westfalia systems. Israeli farmers are also using a newly developed software program "Noa" that analyzes data of the Management Information System of Israel Cattle Breeders' Association and has direct access to any CDMS.
The following short literature review describes the possible impact of diseases on milk yield, milk composition, locomotion, body weight, and some others health-related indices, which allow monitoring clinical conditions of dairy cows using CDMS.
Milk yield (MY) - The effects of diseases on milk production in dairy cows were described recently in a comprehensive review by Fourichon et al. (5). The authors present the estimates of milk losses consequent to stillbirth, dystocia, milk fever, retained placenta, metritis, cystic ovaries, displaced abomasum and locomotion disorders. Markusfield-Nir et al. (6) estimated these milk losses in Israelis dairy management conditions.
With the discovery of computerized milk-meters, the daily monitoring of milk yield of individual cows became a significant tool for evaluation of the effects of diseases on milk production. At the same time an unexpected milk yield decrease in an individual cow may serve as a warning for sickness. The calculated average milk production of groups of cows during lactation exposes management, especially feeding, failures. The timely elimination of these failures can lead to the prevention of diseases.
Milk production rate is the amount of milk produced per hour between consecutive milking sessions (in kg/h). This parameter is more accurate than daily milk yield parameter, since it reflects the actual milk production changes during milking session intervals. It provides the opportunity to monitor more frequently (2-3 times a day) the performance of the individual cow and of the entire herd and enables early detection of health problems and managerial failures.
Milking time - Milking time - from attaching to removing the teat cups - is influenced by the farm facilities, milker’s skill, lactation number, lactation stage, udder and teat conformation in individual cows (7). The milk somatic cell count of dairy cows with either high or low milking rates was higher than that of cows with moderate milking rate (8). Low milking rate may cause irritation of the udder and the teat, while high milking rate, due to weak teat sphincter, may alleviate penetration of infection into the udder. The association between milkability and susceptibility to mastitis has been reported (7, 9). An udder health index for sire selection, which includes the milking time parameter, has been recently developed (10).
Milk components - The nutritional and clinical aspects of monitoring milk components are reviewed (11, 12) and can be summarized as follows. The protein level is usually influenced by ration energy and carbohydrate content, as well as by dietary fat levels. It is accepted that increasing the by-pass protein in milking cows' diets contributes to an enhanced protein content in milk. Many factors tend to reduce milk fat percent, including illness, excessive agitation, excitement, hot weather, incomplete milking. Milk fat depression is typically associated with acidosis, off-feed problems, and sore feet. It is most commonly related to inadequate dietary fiber (either form or amount), high grain feeding, poor body conditions, high milk production. Factors that raise fat levels are genetics, low production, late lactation, good body condition, cold weather, high roughage feeding. Milk fat to protein ratio reflects the state of cow's energy balance (13, 14). Milk lactose is one of the indicators of the synthetic capacity of the udder epithelial cells. It decreases in mastitis and is influenced by feeding factors, while in comparison to milk fat and protein, lactose is a stable milk component.
Milk Somatic Cell Count (SCC) - Mastitic milk has higher concentration of somatic cells, especially, neutrophils. These cells play a protective role against mastitis-causing bacteria. A cow with over 200,000 cells/ml is more likely to be infected (15, 16). The reporting of SCC data on individual cows, and in a variety of herd summary graphs and tables, has became an important tool in defining udder health status and describing the extent of mastitis infection. SCC data describe the extent of subclinical mastitis and serve as selection criteria for determining which cow should be sampled for bacterial culture (16). Interpreting SCC should be considered, in addition, teat and udder injury, number of quarters infected with mastitis, and inherent biological variations of individual cows. Other factors which affect the SCC level are: age of cow, stage of lactation, season, stress, chemical irritants (as antibiotic therapy), sanitation level, milking equipment facilities (2, 17).
