Invited review: technical solutions for analysis of milk constituents and abnormal milk.
J Dairy Sci
; 93(2): 427-36, 2010 Feb.
Article
in En
| MEDLINE
| ID: mdl-20105515
Information about constituents of milk and visual alterations can be used for management support in improving mastitis detection, monitoring fertility and reproduction, and adapting individual diets. Numerous sensors that gather this information are either currently available or in development. Nevertheless, there is still a need to adapt these sensors to special requirements of on-farm utilization such as robustness, calibration and maintenance, costs, operating cycle duration, and high sensitivity and specificity. This paper provides an overview of available sensors, ongoing research, and areas of application for analysis of milk constituents. Currently, the recognition of abnormal milk and the control of udder health is achieved mainly by recording electrical conductivity and changes in milk color. Further indicators of inflammation were recently investigated either to satisfy the high specificity necessary for automatic separation of milk or to create reliable alarm lists. Likewise, milk composition, especially fat:protein ratio, milk urea nitrogen content, and concentration of ketone bodies, provides suitable information about energy and protein supply, roughage fraction in the diet, and metabolic imbalances in dairy cows. In this regard, future prospects are to use frequent on-farm measurements of milk constituents for short-term automatic nutritional management. Finally, measuring progesterone concentration in milk helps farmers detect ovulation, pregnancy, and infertility. Monitoring systems for on-farm or on-line analysis of milk composition are mostly based on infrared spectroscopy, optical methods, biosensors, or sensor arrays. Their calibration and maintenance requirements have to be checked thoroughly before they can be regularly implemented on dairy farms.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Milk
/
Food Technology
Type of study:
Diagnostic_studies
Limits:
Animals
Language:
En
Journal:
J Dairy Sci
Year:
2010
Document type:
Article
Affiliation country:
Germany
Country of publication:
United States