Agriculture Reference
In-Depth Information
Description of the herd
(sows / parity)
INRA-AFZ
database
Feed
composition
Feeding
level
Feeding erformance
Housing
Housing
conditions
Feeding
plan
Sow profile
Calibration
Factorial
calculation
Simulation
Whole herd
Limiting
factors
Excess
Individual sow
Body condition
(BW - BT)
Requirements
Fig. 4.2.
Description of the InraPorc decision support tool for sow nutrition. (From Dourmad
et al
., 2008.)
Sow profile is calibrated from a description of the herd. 'Feeding plan' aggregates feed composition and
feeding strategy. 'Housing conditions' aggregates the description of housing and climate, considering also
the effect of sow's activity. The tool can be used to simulate the response to a feeding strategy or to predict
the requirements according to a factorial approach.
with parity. The energy requirement for lac-
tation also increases up to parity
5.
On average, voluntary energy intake is
sufficient to meet 83% of the energy require-
ment during lactation, with a lower coverage
in primiparous sows (75%). During gestation,
the amino acid requirement per kilogramme
of feed is higher for first and second parity
sows, mainly because of a lower feed intake
and the further accretion of lean body mass.
The effect of different causes of variation
(e.g. housing conditions or level of perform-
ance) on requirements can also be evaluated.
In the previous example, when gestating sows
were housed outdoors at 10°C ambient tem-
perature, their energy requirement would be
approximately 25% higher, while the lysine/
energy requirement would be 20% lower
(Table 4.1
)
. Similarly, if the litter growth rate
during lactation is higher (3.0 vs 2.6 kg/day;
+15%), energy and amino acid requirements
increase by approximately 10%.
Using the factorial calculation of re-
quirements it is also possible to evaluate the
effect of stage of pregnancy or prolificacy on
SID amino acids or digestible phosphorus
fect of litter growth rate and sow appetite on
requirements during lactation
(Table 4.3
).
Short- and Long-term Simulation of
Performance
InraPorc can also be used to evaluate the
short- and long-term effects of different hous-
ing or feeding strategies on nutrient utiliza-
tion and body condition of sows. The infor-
mation required for running such a simulation
and an example of the predicted responses
are given in
Table 4.4
for a first parity sow. In
practice, these simulations can be useful to
predict the risk of an excessive mobilization
or reconstitution of body reserves, which
might impair long-term reproductive per-
formance. The existence of nutrient deficien-
cies or excesses can also be identified.
In the second example, the changes in
body condition of sows for two phenotypes
