@article {3672,
	title = {Milk composition and productive and reproductive performance of cows from A1 and A2 β-casein variants, milked once or twice a day},
	journal = {New Zealand Journal of Animal Science and Production},
	volume = {80},
	year = {2020},
	month = {09/2020},
	pages = {137-142},
	address = {Online},
	abstract = {Protein is an important component of milk and it plays an essential role in all living organisms. β-casomorphins-7 (BCM-7) is
derived from A1 β-casein and has been implicated in some human health issues. This A1 β-casein is produced by cows with the
A1A1 or A1A2 genotype, whilst cows with the A2A2 genotype produce A2 β-casein, which has not been implicated in the same
human health issues. Given the potential importance of A2 milk for public health and its apparent commercial potential, selection
based on the A2 genotype and its impact on production and reproduction traits should be investigated. The objective of the current
study was to compare the productive and reproductive performance of dairy cows based on A2 genotype in two different dairy
farms. From July 2017 to May 2018, 206 cows (including 122 A2A2 genotype; {\textquotedblleft}A2 cows{\textquotedblright}) were milked once a day at Dairy 1
and 451 cows (including 217 A2 cows) were milked twice a day at Dairy 4. Records of lactation yields of milk, fat and protein,
fat percentage, protein percentage, days from start of mating to conception, pregnancy rate to first service, the submission rate
at 21 days and the pregnancy rate at 21 and 42 days (PR42) after the start of mating from 642 cows in two herds were analysed.
The effects of A2 genotype on production and reproduction traits were not significant. The interaction between farm and β-casein
genotype was significant for PR42 (P<0.05) but not for any other traits. The interactions between parity number and genotype
were not significant for any of the traits. The results indicated that cows of different β-casein genotypes have similar production
and reproductive performance.
Keywords: β-casein genotype; A2 milk; protein percentage; pregnancy rate at 42 days},
	issn = {1176-5283},
	author = {Lu Y and Hickson RE and Gedye K and Correa-Luna M and Donaghy DJ and Lopez-villalobos N}
}
@article {3672,
	title = {Persistency and lactation curves modelled using nonlinear random regression in dairy cows milked once a day},
	journal = {New Zealand Journal of Animal Science and Production},
	volume = {80},
	year = {2020},
	month = {09/2020},
	pages = {131-136},
	address = {Online},
	abstract = {Modelling lactation curves of dairy cows is important for improved feed management and breeding decisions. The objectives
of this study were to compare measures of lactation persistency obtained from the modelling of lactation curves for daily yields
of milk, fat and protein using a nonlinear random regression model in dairy cows milked once a day under grazing conditions.
A total of 1,955 monthly herd-test records of milk, fat and protein from 55 Holstein-Friesian (F), 64 Jersey (J), and 123 F{\texttimes}J
crossbreds of different lactations were used to obtain lactation curves for each cow using a random regression model with the
Wood function. Three measures of persistency were calculated based on ratios of yields and compared with persistency calculated
based on parameters of the Wood function. Jersey cows in lactation 3 had the greatest persistency for all persistency measures. In
first-lactation cows, there were no significant breed differences in persistency. Persistency measures were strongly correlated with
each other (r>=0.97; P<0.001). The conclusion from this study is that parameters of the lactation curve (peak yield, day of peak and
persistency) can be precisely estimated using the random regression model with the Wood function.

Keywords: modelling; lactation curve; persistency; once-a-day milking},
	issn = {1176-5283},
	author = {Jiang H and Hickson RE and Woods OT and Morandeau M and Burke JL and Correa-Luna M and Donaghy DJ and Lopez-villalobos N}
}
