TY - JOUR
T1 - International genetic evaluations for feed intake in dairy cattle through the collation of data from multiple sources
AU - Berry, DP
AU - Coffey, MP
AU - Pryce, JE
AU - de Haas, Y
AU - Lovendahl, P
AU - Krattenmacher, N
AU - Crowley, JJ
AU - Wang, Z
AU - Spurlock, D
AU - Weigel, K
AU - Macdonald, K
AU - Veerkamp, RF
N1 - 20101043
PY - 2014/4/13
Y1 - 2014/4/13
N2 - Feed represents a large proportion of the variable
costs in dairy production systems. The omission of
feed intake measures explicitly from national dairy cow
breeding objectives is predominantly due to a lack of
information from which to make selection decisions.
However, individual cow feed intake data are available
in different countries, mostly from research or nucleus
herds. None of these data sets are sufficiently large
enough on their own to generate accurate genetic evaluations.
In the current study, we collate data from 10
populations in 9 countries and estimate genetic parameters
for dry matter intake (DMI). A total of 224,174
test-day records from 10,068 parity 1 to 5 records of
6,957 cows were available, as well as records from 1,784
growing heifers. Random regression models were fit to
the lactating cow test-day records and predicted feed intake
at 70 d postcalving was extracted from these fitted
profiles. The random regression model included a fixed
polynomial regression for each lactation separately, as
well as herd-year-season of calving and experimental
treatment as fixed effects; random effects fit in the
model included individual animal deviation from the
fixed regression for each parity as well as mean herdspecific
deviations from the fixed regression. Predicted
DMI at 70 d postcalving was used as the phenotype
for the subsequent genetic analyses undertaken using
an animal repeatability model. Heritability estimates
of predicted cow feed intake 70 d postcalving was 0.34
across the entire data set and varied, within population,
from 0.08 to 0.52. Repeatability of feed intake across
lactations was 0.66. Heritability of feed intake in the
growing heifers was 0.20 to 0.34 in the 2 populations
with heifer data. The genetic correlation between feed
intake in lactating cows and growing heifers was 0.67.
A combined pedigree and genomic relationship matrix
was used to improve linkages between populations for
the estimation of genetic correlations of DMI in lactating
cows; genotype information was available on 5,429
of the animals. Populations were categorized as North
America, grazing, other low input, and high input European
Union. Albeit associated with large standard
errors, genetic correlation estimates for DMI between
populations varied from 0.14 to 0.84 but were stronger
(0.76 to 0.84) between the populations representative
of high-input production systems. Genetic correlations
with the grazing populations were weak to moderate,
varying from 0.14 to 0.57. Genetic evaluations for DMI
can be undertaken using data collated from international
populations; however, genotype-by-environment
interactions with grazing production systems need to
be considered.
AB - Feed represents a large proportion of the variable
costs in dairy production systems. The omission of
feed intake measures explicitly from national dairy cow
breeding objectives is predominantly due to a lack of
information from which to make selection decisions.
However, individual cow feed intake data are available
in different countries, mostly from research or nucleus
herds. None of these data sets are sufficiently large
enough on their own to generate accurate genetic evaluations.
In the current study, we collate data from 10
populations in 9 countries and estimate genetic parameters
for dry matter intake (DMI). A total of 224,174
test-day records from 10,068 parity 1 to 5 records of
6,957 cows were available, as well as records from 1,784
growing heifers. Random regression models were fit to
the lactating cow test-day records and predicted feed intake
at 70 d postcalving was extracted from these fitted
profiles. The random regression model included a fixed
polynomial regression for each lactation separately, as
well as herd-year-season of calving and experimental
treatment as fixed effects; random effects fit in the
model included individual animal deviation from the
fixed regression for each parity as well as mean herdspecific
deviations from the fixed regression. Predicted
DMI at 70 d postcalving was used as the phenotype
for the subsequent genetic analyses undertaken using
an animal repeatability model. Heritability estimates
of predicted cow feed intake 70 d postcalving was 0.34
across the entire data set and varied, within population,
from 0.08 to 0.52. Repeatability of feed intake across
lactations was 0.66. Heritability of feed intake in the
growing heifers was 0.20 to 0.34 in the 2 populations
with heifer data. The genetic correlation between feed
intake in lactating cows and growing heifers was 0.67.
A combined pedigree and genomic relationship matrix
was used to improve linkages between populations for
the estimation of genetic correlations of DMI in lactating
cows; genotype information was available on 5,429
of the animals. Populations were categorized as North
America, grazing, other low input, and high input European
Union. Albeit associated with large standard
errors, genetic correlation estimates for DMI between
populations varied from 0.14 to 0.84 but were stronger
(0.76 to 0.84) between the populations representative
of high-input production systems. Genetic correlations
with the grazing populations were weak to moderate,
varying from 0.14 to 0.57. Genetic evaluations for DMI
can be undertaken using data collated from international
populations; however, genotype-by-environment
interactions with grazing production systems need to
be considered.
KW - Confinement
KW - Feed intake
KW - Grazing
KW - Heritability
KW - International collaboration
U2 - 10.3168/jds.2013-7548
DO - 10.3168/jds.2013-7548
M3 - Article
SN - 1525-3198
VL - 97
SP - 3894
EP - 3905
JO - Journal of Dairy Science
JF - Journal of Dairy Science
IS - 6
ER -