Agriculture Reference
In-Depth Information
Clapperton
et al
. (2009) observed substan-
tial genetic variation in immunity traits in
pigs and therefore it can be assumed that in-
dividual pigs in a population will have differ-
ent abilities to respond to a health challenge.
To accommodate this phenotypic variation
in health, it is assumed that the variation in
health status (or score) will not be constant,
but in a population of very healthy pigs (e.g.
population mean health score = Optimal)
there will be less variation than in a popula-
tion that has a health challenge. In a popu-
lation with a mean low health status there is
likely to be more individual variation with
some pigs with a strong immune-competency
effectively having a higher health status. Flori
et al
. (2011) observed a range of phenotypic
variation (CV) values in immune traits be-
tween 0.01 and 0.039, therefore it can be as-
sumed that the CV of an 'Average' health
status herd will be somewhere in between
(0.017-0.020). Within a significantly health-
challenged herd the CV for health will in-
crease to 0.04, whereas under 'Optimal' health
conditions the CV will be close to 0. There
is also likely to be some interaction between
A2C and health status, as healthier individ-
uals are better able to cope with stress than
challenged pigs.
illustrates an example of such an optimiza-
tion process and the potential to improve
gross profit by selecting the optimum weekly
shipping pattern. The actual levels of im-
provement will depend on the grading sys-
tem used for determining payment per pig.
Commercial Applications
When models are used to drive significant
policy, nutritional, production and/or manu-
facturing changes with potentially large eco-
nomic consequences, this process can be
defined as strategic model utilization. The
other commercial application of models is
more incremental by nature, where attention
is given at the local (producer-specific) level
to improve performance or profitability or
assist in the day-to-day decision making
processes. Typically there will be an external
stimulus that will trigger a response for
change. The magnitude of the expected re-
sponse will define whether the model is
used strategically or incrementally. For ex-
ample, if there is an increase in the price of
one or more important ingredients that will
have a significant effect on feed costs either
for the feed manufacturer and/or the pig pro-
ducer, this will invoke a strategic response
such as running multiple optimizations to
determine the formulation change, notifying
manufacturing of the pending changes and
then communicating to the relevant stake-
holders (sales team, producers, etc.). Typical
incremental use of the model would be to
optimize performance or profit for a specific
producer, e.g. to determine the optimum
slaughter weight when the price per kilo-
gramme of hot carcass changes.
Shipping Strategies
When considering economic optimization
(e.g. maximize MOFC), one of the most im-
portant factors is the revenue per pig carcass
and therefore the higher and less variable
the revenue generated per batch of pigs, the
more profitable the operation. For this rea-
son it is important to know when individual
pigs should be shipped to maximize their
revenue based on the method of payment
the producer receives (e.g. index or bonus/
discount systems).
Table 11.1
illustrates the
potential opportunity of models to predict
the outcomes of different shipping strategies.
The data were from pigs shipped over a
5-
week period based on a shipping weight of
close to 119 kg (Nutreco Canada, 2012, un-
published data). Using a modified differen-
tial evolutionary algorithm the optimum
shipping strategies can be defined.
Table 11.2
Strategic use
The following are some commercial examples
of strategic model usage.
High feed costs and associated changes to
the nursery feeding programme
In 2012 most of the main cereal grains and
high protein ingredients exhibited significant
