Estimation of heritability and genetic correlations between milk yield and linear type traits in primiparous Holstein-Friesian cows

Estimation of genetic variability and genetic correlations between production traits (milk yield, fat yield, fat content, protein yield, and protein content) and selected type traits (angularity, fore udder height, rear udder height, front teat placement, teat length, and udder depth) was done using data sets of 10,860 first-calving Holstein-Friesian cows raised in the territory of the Republic of Serbia. Genetic variance and covariance were obtained using the Restricted Maximum Likelihood (REML) method, VCE v6 software, and the multi-trait mixed model. To enable more precise estimates of values for genetic variances and covariance, a relationship matrix was formed for the individual model (animal model), encompassing 21363 animals. The highest heritability values were obtained for milk yield (0.182), fat yield (0.134), and protein yield (0.170). The lowest heritability estimates were for teat length, front teat placement, rear udder height, and udder depth, all being under 0.110. Genetic correlations between production traits and linear type traits were between −0.131 (fat content and front teat length) and 0.307 (protein yield and fore udder attachment). The largest number of traits shows a positive genetic correlation with the traits of milk yield, which thus indicates possibility of genetic improvements of milk yield in cattle without jeopardizing the type traits or vice versa.

Dairy cow monitoring by RFID

Dairy cows identification and monitoring on small cattle farms are usually based on the utilization of barcode technology. This kind of identification technology is unsuitable for dairy cows milking and feeding process automation. Radio Frequency Identification (RFID) technology is a better solution in this case. This paper describes the research and implementation of the milking cycle´s automated monitoring with the use of RFID tags conducted on a small cattle farm in the Republic of Serbia. This solution is based on RFID system which consists of two parts. First part includes control box, two Ultra High Frequency (UHF) RFID readers operating at frequency of 915 MHz and RFID tags glued onto the dairy cow ear labels. Second part includes software modules for acquisition and collecting data from RFID tags to build up an archive due to supervision and analysis of the milking cycle. Reading accuracy of RFID system in the observed period was 99.8 % in average. A group of dairy cows having a settled milking cycle within an interval of 12h ± 5 % had a 1.5 % better yield and a 0.08 better quality in comparison with a group of dairy cows having a milking cycle variance higher than 20 %. RFID system implemented in described way can be easily integrated into a new or existing farm management system in order to have better production results which depend on several factors including settled milking cycles.

Dairy cow monitoring by RFID

Dairy cows identification and monitoring on small cattle farms are usually based on the utilization of barcode technology. This kind of identification technology is unsuitable for dairy cows milking and feeding process automation. Radio Frequency Identification (RFID) technology is a better solution in this case. This paper describes the research and implementation of the milking cycle´s automated monitoring with the use of RFID tags conducted on a small cattle farm in the Republic of Serbia. This solution is based on RFID system which consists of two parts. First part includes control box, two Ultra High Frequency (UHF) RFID readers operating at frequency of 915 MHz and RFID tags glued onto the dairy cow ear labels. Second part includes software modules for acquisition and collecting data from RFID tags to build up an archive due to supervision and analysis of the milking cycle. Reading accuracy of RFID system in the observed period was 99.8 % in average. A group of dairy cows having a settled milking cycle within an interval of 12h ± 5 % had a 1.5 % better yield and a 0.08 better quality in comparison with a group of dairy cows having a milking cycle variance higher than 20 %. RFID system implemented in described way can be easily integrated into a new or existing farm management system in order to have better production results which depend on several factors including settled milking cycles.