Prediction of cow fertility based on productivity traits in dairy cattle under different production systems
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Banda, Liveness Jessica
Abstract
A study to examine factors that influence dairy cattle fertility was conducted
in the United Kingdom (UK) and Malawi. Productivity data from the UK
comprising 56,014 records from 574 Holstein cows were retrieved from a
database at Scotland’s Rural College Dairy Research Centre in Dumfries.
The cows were of either high (select) or average (control) genetic merit and
fed total mixed rations with high or low forage. These formed four production
systems - high forage select (HFS), low forage select (LFS), high forage
control (HFC) and low forage control (LFC). Data from Malawi were obtained
through a baseline survey in 67 smallholder farms and monitoring of 28 and
62 dairy cows from smallholder farms and a commercial farm, respectively.
The breeds were Holstein-Friesians and Holstein-Friesian x Malawi Zebu
crosses predominantly fed forages supplemented with concentrates. Some
cows were fitted with accelerometers to enable monitoring of cow activity
which was then related to cow fertility and energy balance. The data were
analysed using descriptive statistics, mixed models and logistic regression
models using SAS 9.3.
The UK data showed that production system significantly (p<0.05) influenced
milk yield, body energy content (BEC) and fertility. BEC is a trait that
indicates absolute level of energy in the body per day regardless of energy
use and intake the previous day. Daily milk yield of LFS cows was 35±0.1
(mean±SEM) litres which was significantly (p<0.05) higher than that of LFC
(30.4±0.1 litres), HFS (27.5±0.1 litres) and HFC (24.3±0.1 litres) cows. LFS
cows also had the highest milk yield acceleration to peak milk yield (0.51
litres/day/day) than (LFC 0.47±0.02 litres/day/day), HFC (0.47±0.03
litres/day/day) and HFS (0.46±0.03 litres/day/day) cows. The interval from
calving to nadir BEC was 68±5, 83±6, 88±5 and 106±6 days for LFC, LFS,
HFC and HFS cows, respectively. Days to first high luteal activity (DFHLA)
and days to successful service (DSS) were significantly different with
production system and genetic merit, respectively. LFC cows had DFHLA of
27±2 days (mean±SEM) which were significantly lower (p<0.05) than those
of HFC (30±3 days), HFS (30±2 days) and LFS (35±3 days) cows. Average
genetic merit cows had significantly lower (p<0.05) DSS (119±5 days,
mean±SEM) than high genetic merit cows (132±5 days). Results from data
collected in Malawi showed variations that reflected differences in
management and other environmental factors. Average daily milk yield per
lactation in Malawi was 13.3±4.9 (mean±SD) litres. Fertility traits in the UK
herd were better than those in Malawi herds. The average DFHLA in Malawi
was 79±29 days while in the UK it was 31±18 days. Cow activity in both the
UK and Malawi farms varied with the feeding system, genetic merit and BEC.
Select cows on home grown feeding system were more active (motion index
=6250±40), stood longer (13.4±0.04 hours/day) and spent more time eating
(5.6±0.32 hours/day, mean±SEM) than select cows on by products feeding
system that had motion index, standing and eating time of 5166±37,
11.9±0.04 hours/day and 4.6±0.16 hours/day, respectively.
Genetic merit, lactation number, days to first observed oestrus, calving BEC,
service BEC and service milk yield were significant predictors of pregnancy
to first insemination (p<0.05) while genetic merit, milk yield, percentage BEC
between calving and service, service milk yield and service BEC were
significant predictors (p<0.05) of pregnancy to the first three inseminations.
Validation of models derived showed C-statistics of the receiver operating
characteristic (ROC) curve of 0.66 (95% confidence interval (CI): 0.57 to
0.75) and 0.65 (CI: 0.55-0.75), respectively. It is concluded that genetic merit,
feeding system, parity, energy status and stage of lactation are the major
factors that determine the likelihood of achieving pregnancy following
insemination. Models developed have a potential to predict the probability of
pregnancy to an insemination at an acceptable level of accuracy.
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