Agriculture Reference
In-Depth Information
Conclusions
tools for decision making. Mechanistic
models, although well known to be more
accurate and helpful in gaining knowledge,
are indeed less appreciated in the poultry
industry than the ones developed based on
empirical methodologies. The main limita-
tion to model adoption is knowledge of
mathematical methods, growth and devel-
opment concepts, and understanding of
model structure and outputs. The value of
these tools is accepted by the industry, but
the interest in investing in more mechanis-
tic biological tools is still low. In order to
resolve the issues that are limiting applica-
tion of models in poultry, it is necessary to
enhance the interest of the academic com-
munity in these approaches and to train fu-
ture professionals in these techniques and
this way of thinking. This may require the
collaboration of the private industry that ac-
tually owns, develops and uses such models.
Mathematical models are indeed tools ne-
cessary to understand the complex problems
common in poultry enterprise management,
processing, live production, nutrition and
research. Many models have been proposed
for the poultry industry and most have been
abandoned. Currently, models that have the
capability to link live performance with
econometric business analyses are still used
or being developed in the industry. The
interest in poultry modelling is greater in
the industry than in academic institutions.
Poultry companies invest heavily in tools
that allow them to observe transactions,
carry out planning, forecasting, estimate
optimal production levels and evaluate busi-
ness strategies. Very few biological models
have broad application in the poultry busi-
ness or are linked to more complex modelling
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