Agriculture Reference
In-Depth Information
varied in the model to determine the conse-
quence of differences in this relationship.
In determining nutrient requirements,
rules must be applied to account, for example,
for the size of amino acid pools for potential
albumen formation (which must be filled be-
fore ovulation can proceed), and for the rates at
which lipid can be deposited in, or withdrawn
from, body reserves as a means of accounting
for differences in energy balance. If it is as-
sumed that birds and animals have an inherent
ratio of body lipid to protein, which they at-
tempt to maintain at all times (Emmans, 1981,
1989), where possible, the bird will make use
of excess lipid reserves as an energy source.
This has an impact on the voluntary food in-
take of hens, with energy being stored on non-
laying days and being utilized on laying days,
which would tend to buffer the changes in
food intake required on these days. Presum-
ably there is a minimum amount of body lipid
that needs to be maintained (Gous
et al
., 1990)
that will be unavailable as an energy source.
determining how to maximize or minimize
the objective function chosen for any given
commercial operation. In the models of
commercial laying hens and broiler breed-
ers described here, the theory is applied
to an individual and then a population is
simulated using appropriate means and
standard errors for the variables concerned.
The responses thus obtained are acceptable
representations of reality, and are thus ideal
for determining the optimum method of
feeding these simulated flocks.
Optimizing the feed and feeding pro-
gramme for a flock of laying hens can be
achieved with three components, namely, a
feed formulation program, an egg production
model and an optimization routine. The flow
of information for such a procedure bears
similarities to the continuous quality improve-
ment model of Deming (1986), which consists
of four repetitive steps (Plan, Do, Check, Act),
this continuous feedback loop being designed
to assist managers to identify and then reduce
or eliminate sources of variation. In the case of
the nutritionist, the optimizer defines nutri-
tional constraints for practical layer or breeder
feeds, which are passed to the feed formula-
tion program where the least-cost feed that
meets these constraints is determined. The
characteristics of this formulated feed are
then passed, as input, to the laying hen model.
The performance expected from this feed
when given to a defined flock of hens in a
given environment is predicted by the model,
and this predicted performance is then
passed to the optimizer to complete the
cycle. The next cycle starts with the opti-
mizer modifying the feed specifications,
moving, according to some in-built rules, to
an optimum point. A single feed could be
fed throughout the laying period, or differ-
ent feeds might be more beneficial as the
flock ages. In the case of broiler breeders,
both the composition of the food and the
amount to be supplied may be altered dur-
ing the laying period. The objective function
to be maximized or minimized can be defined
in terms of any output from the simulation
model, but realistically would be an economic
index of some sort. Examples are maximiz-
ing the margin, based on the value of egg
Optimization
Until recently, mechanistic models devel-
oped for poultry have dealt with the simula-
tion of responses in a single bird. Such
responses are usually linear to the point
where the genetic potential is reached (Fisher
et al
.,
1973). Poultry nutritionists are inter-
ested in responses to nutrients in economic-
ally important outputs such as body weight
(or protein) gain, breast meat yield, egg out-
put, numbers of chicks produced per hen,
etc. Because such responses are usually
measured using groups of birds, they are in-
variably curvilinear, being the result of inte-
grating the responses of individuals making
up that population (Fisher
et al
.,
1973).
Populations of birds therefore cannot have
'requirements' for nutrients: what nutrition-
ists seek are the optimum economic dietary
contents of each nutrient, and for this they
need to know how populations respond to
increasing dietary contents of the essential
nutrients. Descriptions of such responses,
whilst taking account of marginal costs
and revenues, are therefore invaluable in
