At the present time, Canada's swine genetic
improvement is based on three main components : adjusted
backfat at 100 kg, age at 100 kg and total number piglets born.
However, to stay more competitive and to adjust the selection
to the market and consumers demands, new traits must be included
into the Canadian genetic evaluation program. Meat quality and
quantity are some of tomorrow's battle fields. One can use different
parameters to measure meat quality and quantity. Some of them
are the lean meat yield, loin eye area and marbling.
Lean meat yield can be evaluated from carcass
measurements at the slaughterhouse or can be obtained indirectly
from the measure of the backfat on live animals (Sather et al.,
1987), while loin eye area and marbling are mainly obtained on
When you wish to make selection on a specific
trait, it is always more efficient when the measure is taken on
the animal itself and not sibs. Furthermore, the selection is
more accurate when you measure the trait itself and not another
trait (except if the correlation between the two is very high).
Since the pigs are leaner than before, it should be considered
that the correlation between fat thickness and lean meat yield
for these leaner pigs may be not the same as for fatter ones.
Thus, it is important to look at other ways of predicting lean
Even though ultrasound has been used for evaluating
live animals for many years (Stouffer et al., 1961) its main use
in hogs is still to measure the backfat of live animals. However,
new technologies and more knowledge will increase the use of ultrasound
equipment to measure other traits on live pigs and will improve
the prediction of lean meat yield.
MATERIAL AND METHODS
At the CDPQ test station, 324 hogs were probed
prior to slaughter at an average weight of 105 kg. The first
ultrasound equipment used was a B-mode type. It consisted of
an Aloka model 500 with a 126 mm-3.5MHz transducer. Two scans
have been taken on the left side of each hog : one cross
sectional between the third and fourth last ribs (CROSS) and one
longitudinal over the last four or five ribs at 5 cm off the
back midline (LONG).
The images were stored on a computer and a
VCR for subsequent analysis. The longitudinal images have been
analysed for lean meat yield and loin eye area predictions from
fat and loin depth measurements with AUSKey AUTOD (LIN, 1994).
The cross sectional images have been manually analysed to determine
the lean meat yield and loin eye area. The AUSKey AUTOQ has been
used to determine the loin marbling from cross sectional and longitudinal
The second ultrasound equipment used was An
A-mode type. It consisted of a Krautkramer USM2. Three different
sites have been probed : behind the last rib, 5 cm off the
back midline, average of the fat of both sides of the animal (ANT)
; 3.5 cm in front of the ischion, 5 cm off the back midline, average
of the fat of both sides of the animal (POST) ; between the third
and fourth last ribs, 5 cm off the back midline, average of the
fat of both sides of the animal (FAT34) and average of the loin
depths of both sides of the animal (MUSC34). The ANT and POST
are the usual fat measures that are currently used in the Canadian
genetic evaluation program. They have been pooled together to
have only one fat measurement (FAT).
All the animals have been slaughtered and the
loin and fat depth measured with a Hennessy probe on the carcass
have been recorded and the lean meat yield has been calculated
according to the equation currently used in Quebec plants using
a Hennessy probe :
Lean meat yield (%) = 67.2327 - 0.7877 fat
+ 0.1086 loin depth + 0.0087 fat2 - 0.0004 loin depth2
- 0.0002 fat*loin depth
A loin eye trace was done at the plant to calculate
the loin eye area and visual marbling score has been determined
for each animal on a cut of the loin between the third and fourth
last ribs. Scoring of the marbling was done using the Agriculture
Canada standard on a 5 point scale with 1 = trace, 2 = slight,
3 = small, 4 = moderate and 5 = abundant.
Forty-eight animals had a full cutout to determine
their precise contents in lean, fat, bone and skin. A cutout
lean meat yield has been determined using the following equation (Jones
et al., 1994A):
% lean yield = (boneless loin + tenderloin
+ boneless and defated ham + boneless and defated shoulder + skinned
belly + side ribs) / weight of the half carcass x 100
The data have been analysed with procedures
CORR and GLM from SAS (SAS Institute, 1988). The effects used
in the analysis model were sex (gilts and barrows) and crossbred
types. Animal weight and prober were not considered since all
animals have been probed at about the same weight by the same
technician. Probing date was non-significant.
RESULTS AND DISCUSSION
1. Descriptive statistics
Descriptive statistics of the measurements
of the different traits are shown in table 1. As expected, Hennessy
fat was higher than fat measured on live animals. This has already
been reported by other authors such as Sather et al. (1982).
Fat measured on the live animal with the longitudinal B-mode was
higher than measured with the A-mode or the cross sectional B-mode
(non-significant). While loin depth measured on the live animal
with the longitudinal B-mode was lower than measured with the
An overestimation of fat and underestimation
of loin depth was expected with the B-mode equipment compared
to the A-mode. Longitudinal measure is the average of the depth
over 4 to 5 ribs. Furthermore, the measures taken with ultrasound
equipment depend on the velocity of the ultrasound in the measured
materials, and calibration of the ultrasound equipment must be
made to take into consideration the velocity differences.
Ultrasound velocity in fat is 1 480 m/s and
is 1 620 m/s in the muscle. The B-mode equipment used was calibrated
to 1 550 m/s. This calibration causes underestimation of the
loin depth and overestimation of fat. So if these measures are
to be used directly, this fact should be considered and the measurements
corrected with a constant factor.
The A-mode equipment used could be manually
calibrated to the chosen velocity. We have calibrated it to 1
480 m/s to measure the fat with accuracy. When we have measured
the loin depth, calibration was set up to 1 480 m/s also, because
when the measure of loin depth is done, it includes fat and muscle
depth. The fat depth was subtracted from the total and a correction
factor (10 %) was added to give the loin depth. The technique
used to measure the loin depth was adapted from previous trials
done at CDPQ.
2. Lean meat yield and loin eye area
Prediction of the lean yield from the A-mode,
B-mode, slaughterhouse and cutout measures have been compared
to each others (table 2). Live measures were more accurate than
the Hennessy probe to predict lean yield as obtained from the
As already reported (Jones et al., 1994b ;
Stouffer, 1996), mode B ultrasound equipment usually predicts
more accurately the lean yield than the probes used in the slaughterhouses
(Hennessy or Destron). The relation between the prediction from
the Hennessy probe and the cutout was the same as in the 1992
national cutout (R2=0.64) while A-mode, B-mode (LONG) and B-mode
(CROSS) had accuracy of 0.70, 0.65 and 0.55 respectively.
Thus, from this trial, the best measurements
to predict lean meat yield were the measures taken with A-mode
ultrasound equipment between the 3rd and 4th
For the loin eye area, the two machines gave
almost the same accuracy at around 0.59 and 0.60.
3. Marbling prediction
Marbling has been predicted from the B-mode
cross sectional and longitudinal scans. It has been compared
with visual evaluation on the loin of the carcass as previously
explained (table 3). The accuracy of prediction is essentially
However, when the distribution of the frequency
of the number of observations is plotted with the marbling score,
we can note that CROSS and LONG scores follow about the same distributions
(figure 1). However, these measures overestimate the number of
animals in score 1 and underestimate the number of animals in
score 2 as determined by the visual observation at the slaughterhouse.
The marbling cannot be predicted by live scans,
but even if the correlations are quite low, it seems possible,
with more work, to be able to determine it.
It is now possible to measure with accuracy
the loin depth of the live animal. This should permit direct
selection of the loin muscle instead of using backfat alone.
Loin eye area should be another selection trait because lean yield
is no longer the only researched trait by the markets. Specificly
loin eye area. distribution of the meat in the different parts
of economical interest of the animal (loin, ham, etc.) and meat
quality traits such as marbling are more and more in demand.
Selection must be done considering the needs of all the swine industry and consumers needs. A better link is required between all aspects of the production. This is the tomorrow's biggest challenge !
|Aloka (B-mode ultrasounds)|
|CROSS fat mm|
|CROSS loin eye area cm2|
|LONG fat mm|
|LONG loin depth mm|
|LONG loin eye area cm2|
|Krautkramer (A-mode ultrasounds)|
|Hennessy fat mm|
|Hennessy muscle mm|
|Loin eye area cm2|
|Aloka (B-mode ultrasounds)|
|Krautkramer (A-mode ultrasounds)|
|FAT34 and MUSC34|
Jones, S.D.M., A.K.W. Tong, W.M. Robertson and P. Skoczylas. 1994a. National pork carcass cutout project (1992) part 1 : a comparison of the 1978 and 1992 cut outs. Canadian Pork Council, Ottawa, Canada. Pp. 1-20.
Jones, S.D.M., A.K.W. Tong, A.F. Fortin, C. Campbell and W.M. Robertson. 1994b. National pork carcass cutout project (1992) part 3 : Evaluation of new technology for grading pork carcasses. Canadian Pork Council, Ottawa, Canada. Pp. 39-46.
Lin, Y. 1994. Userís Manual for AUSkey system, version 2.0. Animal Ultrasound Services, inc. Ithaca, New York. 151 p.
SAS Institute. 1988. SAS/STAT User's guide. Release 6.03 Edition. Cary, North Carolina. 1028 pp.
Sather, A.P., H.T. Fredeen and A.H. Martin. 1982. Live animal evaluation of two ultrasonic probes as estimators of subcutaneous backfat and carcass composition in pigs. Can. J. Anim. Sci., 62 :943-949.
Sather, A.P., A.K.W. Tong and D.S. Harbison. 1987. A study of ultrasonic probing techniques for swine. II. Prediction of carcass yield from the live pig. Can. J. Anim. Sci., 67 :381-389.
Stouffer, J.R. 1996. Ultrasound grading of carcasses. In New technologies for carcass grade and quality assessment, Proceedings of the 11th Annual Symposium of the Canadian Meat Science Association. February 7, 1996, Toronto, Ontario. Pp. 1-8.
Stouffer, J.R., M.V. Wallentine, G.H. Wellington and A. Diekmann. 1961. Development and application of ultrasonic methods for measuring fat thickness and rib-eye area in cattle and hogs. J. Anim. Sci., 20 :759-767.