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are thinking.”
Targeting average performance
by group feeding tends to over-
feed the most efficient animals and
underfeed others. The work has
required improved understanding
about the metabolism of growing
pigs and particularly of their use of
calcium and
phosphorus.
That knowledge, added to
mathematical models which inter-
act with feeding equipment, allows
for automated feeding of finisher
pigs. Similar calculations have yet
to be done for sows, Pomar said.
“For sows . . . we are going to
have to do some research on the
differences because when you are
interested in just the group re-
sponse . . . we are not encouraged
to know why there are pigs that
are performing better,” Pomar said.
“When you are moving to
individuals, you have to know why
one pig is performing better than
the others,” he said.
Software used in Pomar’s finish-
ing experiments identifies each
animal, measures feed intake and
body weight and then automati-
cally calculates and adjusts the
“concentration of nutrients.”
“All this is done automatically so
the farmer has not to decide every
day how and what he will feed,”
Pomar said. “The impact is going
to be important,” he said, predict-
ing a broad shift within 10 years
toward precision feeding.
“Soon corn and soybeans will be
in competition between animals
and humans, so that means we
should be expecting feed costs
will increase. We cannot continue
using five kg of feed protein to
produce one kg of animal protein,”
he said.
Pomar’s techniques not only cut
feed costs, but also permit close
monitoring of disease and more
accurate timing for
calculating finished weight.
“The interest for me is not just
because we’re improving nutri-
ent efficiency but because (we)
have a lot of information,” Pomar
said. “You know in real time what
is happening on your farm, so
when a disease is getting in you
are going to identify very quickly
that something is happening . . .
You are going to be able to make
interventions really quickly.”
BP
Better Pork
December 2016
11
COMPUTERIZED
HOG
BARN