Agriculture Reference
In-Depth Information
Do we need to be more accurate and predictive? Logic would suggest that increasing the
accuracy and predictive power of targets will increase the proportion of gilts going on
to successfully and consistently reproduce. This will decrease costs of gilt development
and keep females in the herd through their most prolific parities. If one can refine body
condition targets then it may be possible to prevent the metabolic states that cause
reproductive, locomotive and infectious sow in removal too early in life. Gilts with
specific body condition status and developmental histories in terms of tissue stores may
theoretically go through the metabolic rigors of youthful reproductive cycles, having the
right balance of accretion and catabolism of body tissues during the female's first and
second parity.
Do we have the wrong targets? Those pursuing near-perfect efficiency in pork production
continue to think that if all factors are precisely controlled then sows will raise large litters
in a timely fashion and there will be no sow loss before old age. Perfect efficiency includes
efficient incorporation of gilts into the breeding herd through the use of breeding targets
for body condition.
The British Pig Executive (2010b) currently recommends these 'typical service targets'
for replacement gilts:
•
220 to 270 d of age;
•
135 to 170 kg live body weight;
•
Body condition score of 3 to 3.5.
Note that absent are targets for backfat depth or longissimus thoracis muscle depth or
muscle. One reason for that may be that body condition score is inclusive of both fat and
protein stores. It is in fact a better indicator of the 'fitness' of the gilt which is thought to be
more holistic than fat or protein stores considered individually (Gill, 2007). The definition
of fitness presently includes feeding and management of gilts and young sows for body
condition, and soundness of legs and feet. In the future, it may include some target which
is a combination or model of amounts or rates of accretion of all body tissues.
Exact targets that produce discernible results evade us to varying degrees for various
reasons. First, there is 'confounding' or 'relationships' among targets (age, weight, growth
rate, body fatness, body protein mass and skeletal development). Second, targets are
empirical predictors which have inherent error (Rozeboom
et al.
, 1994). Backfat depth
and body weight may not accurately predict total body protein. Prediction equations
should not be used for predicting the body composition of different populations of
females. The accuracy of body composition estimates from independent variables or
measurements diminish as age, physiological status, genotype, and nutritional history
diverge from those of the population in which the prediction equations were derived.
Thirdly, we must be mindful of errors in methodology. Backfat depth may be measured
differently in different studies. The location on the body (P2, last rib, 2 cm of of the
midline) may vary. Likewise, researchers may be measuring two layers or three layers of
fat. The measurement of longissimus thoracis muscle diameter or area requires technical
experience to insure accuracy and consistency. Fourthly, time periods vary between
reports and cause confusion. Johnston
et al.
(2007) included all gilts from weaning in
