Agriculture Reference
In-Depth Information
consequences; and repeat the cycle. The
concept of optimization is succinctly de-
scribed by Ruby (2003):
Producers exist to convert inputs into
desired goods and services in an efficient
manner. Given that output prices and
factor prices are determined in competitive
markets, efficiency means exploiting
existing production technology to the
greatest extent possible. Profits earned by
the entrepreneur represent the reward for
taking risks (facing an uncertain demand
for the output) and achieving efficiency in
production (relative to competing producers).
A producer optimum represents a solution
to a problem facing all business firms -
maximizing the profits from the production
and sales of goods and services subject to
the constraint of market prices, technology
and market size.
In order to achieve this goal effectively, we
need to be able to predict the consequences
of the alternative courses of action.
There is a common belief that experi-
ence and/or experiments are an accurate
means of predicting these consequences,
but this is not the case. It is necessary to have
an accurate theory in order to make the right
decisions. Experience is a relatively poor
predictor of performance in broiler produc-
tion, simply because the broiler genotypes
with which we work change each year. In
Table 13.1,
the time that it has taken a broiler
to reach 1.8 kg in live weight, and the amount
of food that has been needed per kilogramme
of gain, are given for each decade over the past
five decades. There can be little doubt that ex-
perience of rearing broilers even
10
years ago
is not the best way of knowing how to maxi-
mize profitability in the industry today.
The performance characteristics given
in
Table 13.1
are easily measured, and clearly
show the remarkable rate of improvement
in broiler performance in the past
60
years.
But genetic changes have also taken place as
a result of selection by the primary breeding
companies for improved food conversion
efficiency, reduction in body lipid content
and increase in breast meat yield. These se-
lection criteria have changed the broiler in
subtle ways that are difficult to measure,
and the effects are almost impossible to sep-
arate from the general improvement in per-
formance, yet they have a profound effect
on the way in which the broiler should be
fed to maximize performance and efficiency.
Most broiler producers would largely be un-
aware that such changes have taken place,
especially if they have continued to make
use of technology that suited the perform-
ance of broilers one to three decades ago.
More importantly, commercial breeders in-
variably aim for different selection targets,
with the result that the response to nutrition
or the environment may differ between geno-
types, as the example by Kemp
et al
. (2005)
commercial broiler were subjected to changes
in the ideal dietary protein content, one
strain responded to a decrease in protein by
consuming more feed, while the other strain
did the opposite. Clearly the optimum feeds
and feeding programme for the two strains
would not be the same.
The results of past experiments with
broiler chickens have been invaluable in
providing information about their responses
to nutrients and to the environment, but the
major problem with the use of experiments
in attempting to predict performance is that
there are so many variables that influence
this performance. Each time an experiment
is conducted different conditions prevail in
the research facility. Because we are inter-
ested in the interaction between the bird,
the environment and the feed and feeding
programme used, extremely complex experi-
ments would be needed to test all combinations
of these factors. And then, because of the
changes that take place in the genotypes
Table 13.1.
Changes over the past six decades in
the length of time taken by broilers to reach 1.8 kg
and the amount of food required per unit gain.
Food per unit gain
g/g
Period
Days to 1.8 kg
1950
84
3.25
1960
70
2.50
1970
59
2.20
1980
51
2.10
1990
42
1.93
2000
36
1.55
2010
32
1.50
