Agriculture Reference
In-Depth Information
a different source of genetics. This was a
significant investment for the producer and
he wanted to be reasonably certain that the
improvement in animal performance would,
in the long term, cover the costs and help to
justify the decision. Simulations were per-
formed to illustrate the expected outcomes.
Table 11.4
summarizes the comparison
between predicted and actual performance
before and after the changes.
It was evident that the predictions were
within ±5% of actual results, and the model
was effective in estimating the changes in
performance when genotype and health sta-
tus were improved.
changing market conditions. It has been re-
ported to have saved producers up to $1.50/
pig (Perron, 2011).
Sustainability
Most animal nutrition service providers are
stakeholders in the pig industry and there-
fore need to support producers in their com-
pliance with nutrient management regulations,
as well as encourage responsible pork pro-
duction. Models are an excellent tool to
facilitate the reduction of their carbon foot-
print, and nutrient excretion, especially ni-
trogen (N) and phosphorus (P). This includes:
(i) meticulous assessment of total and digest-
ible protein (Nx6.25) and P content of feed
ingredients in order to eliminate unneces-
sary safety margins; (ii) using Watson
®
to
determine the optimal ideal protein and P
requirement for each phase of feeding; (iii)
optimizing the feed formulations to minim-
ize N and P losses; and (iv) monitoring the
magnitude of change associated with new
feeding strategies. In addition, the power of
optimization allows producers to decide be-
tween reducing their environmental impact
(e.g. CO
2
per kg pork, N and P excretion) or
continuing to use financial and perform-
ance orientated objectives. For example, by
allocating a CO
2
output value for each ingre-
dient and therefore for the complete feed it
is possible to formulate diets that will opti-
mize financial gains while at the same time
reducing the CO
2
per kg pork of the produc-
tion system.
Changing market environment
One of the biggest challenges for pig produ-
cers is to manage effectively the volatility
in the market, especially when pig prices
are fluctuating and feed costs are high. In
these situations it is critical to know what
the optimum shipping live weight should
be for a specific slaughter plant. Watson
®
was used to derive a reference guide for
producers to help in their decision making
process
(Table 11.5)
.
The guide is a quick and easy reference
for the producer to identify the target ship-
ping live weight that will provide the high-
est gross profit per pig under different
pig price and feed cost scenarios. It is read-
ily used by sales teams because it is simple,
easy to read and provides a more objective
assessment when dealing with rapidly
Table 11.4.
Summary of the predicted (Watson) and actual (on-farm) performances before and after
changing the health status and genotype. (From Shur-Gain field trial, 2007.)
Before changes
After changes
Watson
On-farm
% Difference
Watson
On-farm
% Difference
ADG (g/day)
847
866
+2.2
970
934
+3.7
Feed conversion
2.70
2.64
-2.2
2.44
2.42
-1.0
Days to market
94.5
95.0
+0.5
98.0
99.0
+1.0
ADFI (kg/day)
2.50
2.60
+4.0
2.36
2.26
-4.3
Market weight (kg)
112.7
113.7
+0.9
114.4
113.5
-1.0
Carcass weight (kg)
90.2
91.1
+1.0
92.6
92.5
-0.1
Lean yield (%)
60.6
59.8
-1.3
60.9
61.1
+0.3
Backfat (mm)
18.6
18.9
+1.6
18.4
18.1
-1.6
ADG = average daily gain; ADFI = average daily feed intake.
