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In vivo prediction of intramuscular fat in pigs using computed tomography 被引量:1

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摘要 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. 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.
机构地区 Norsvin
出处 《Open Journal of Animal Sciences》 2013年第4期321-325,共5页 动物科学期刊(英文)
基金 support from the Norwegian Research Council,project no 210637/O10 and the Nortura meat cooperative
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