TITLE:
In vivo prediction of intramuscular fat in pigs using computed tomography
AUTHORS:
Jørgen Kongsro, Eli Gjerlaug-Enger
KEYWORDS:
Intramuscular Fat; Computed Tomography; PLS Regression; Calibration; Validation
JOURNAL NAME:
Open Journal of Animal Sciences,
Vol.3 No.4,
October
29,
2013
ABSTRACT: One hundred and four pure-bred Norwegian
Duroc boars were CT (computed tomography) scanned to predict the in vivo intramuscular
fat percentage in the loin. The animals were slaughtered and the loin was cut
commercially. A muscle sample of the m. Longissimus dorsi was sampled and
analyzed by the use of near-infrared spectroscopy. Data from CT images were
collected using an in-house MATLAB script. Calibration models were made using
PLS (partial least square) regression, containing independent data from CT
images and dependent data from near-infrared spectroscopy. The data set used
for calibration was a subset of 72 animals. The calibration models were
validated using a subset of 32 animals. Scaling of independent data and
filtering using median filtering were tested to improve predictions. The
results showed that CT is not a feasible method for in vivo prediction
of intramuscular content in swine.