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.
Highlights
Intramuscular fat (IMF) in meat is an important trait due to the impact on sensory quality and acceptance of pork meat [1]
In order to select for meat quality traits in breeding, development of in vivo methods is of great importance
The results showed that computed tomography (CT) can be used to predict salt content of processed meat samples, especially when including scans at several different energy levels [7]
Summary
Intramuscular fat (IMF) in meat is an important trait due to the impact on sensory quality and acceptance of pork meat [1]. IMF is generally determined by extracting IMF from muscle [2] or by spectroscopic methods [3] These methods require meat samples collected post mortem. In order to select for meat quality traits in breeding, development of in vivo methods is of great importance. Several studies have examined the use of CT to predict intramuscular fat and fatty acid composition using CT [1,6]. Both studies concluded that CT could be used to predict the IMF content post mortem in carcasses or meat samples. In order to remove noise, some filtering techniques like median filtering [10] have shown to reduce “salt and pepper” noise which may be observed by in vivo CT images [11]
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