2013
DOI: 10.1016/j.foodcont.2012.09.034
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Prediction of pork marbling scores using pattern analysis techniques

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Cited by 32 publications
(22 citation statements)
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“…Marbling, is another important determinant of pork quality grade associated with sensory attributes such as flavor and texture, thus plays a key role in evaluating pork. The moderately and evenly distributed marbling in muscle facilitates the acceptability and palatability of pork in the market (Huang, Liu, Ngadi, & Gariepy, ). The superior marbling found in LM from DBJBP in our research could be ascribed to their higher heterosis than DJBP and DLJBP.…”
Section: Discussionmentioning
confidence: 99%
“…Marbling, is another important determinant of pork quality grade associated with sensory attributes such as flavor and texture, thus plays a key role in evaluating pork. The moderately and evenly distributed marbling in muscle facilitates the acceptability and palatability of pork in the market (Huang, Liu, Ngadi, & Gariepy, ). The superior marbling found in LM from DBJBP in our research could be ascribed to their higher heterosis than DJBP and DLJBP.…”
Section: Discussionmentioning
confidence: 99%
“…However, these 2 methods have disadvantages of being subjective and time‐consuming (Arneth ; Ferguson ). What's more, in order to overcome these disadvantages and realize rapid online grading of marbling degree, several instrumental techniques (mainly spectroscopic and imaging techniques) have been developed, such as near‐infrared reflectance (NIR) spectroscopy (Barlocco and others ; Zamora‐Rojas and others ; Su and others ), bioelectrical impedance (BI) spectroscopy (Marchello and others ; Altmann and Pliquett ), nuclear magnetic resonance (NMR) spectroscopy (Corrêa and others ; Pereira and others ), computer image analysis (CIA) (Du and others ; Jackman and others ; Pang and others ), ultrasonic imaging (UI) (Fukuda and others ; Lakshmanan and others ), X‐ray computed tomography (CT) (Frisullo and others ; Font‐i‐Furnols and others ; Clelland and others ), and hyperspectral imaging (HSI) (Qiao and others ; Huang and others , ; Liu and Ngadi, ). However, up to now, no comprehensive review is available on the methods and techniques for marbling analysis.…”
Section: Introductionmentioning
confidence: 99%
“…In contrast to previous works (Liu et al, 2012;Huang et al, 2013) in which the proportion of the segmented intramuscular fat area was regarded as the best feature to measure quantitative marbling in meat products, in this work, the features which produced the best performance belong to the Haralick textural features: autocorrelation (35), cluster shade (37), entropy (38) and sum of variance (42). Although, it is difficult to have a clear physical interpretation of these parameters, they are all related to distribution of fat in the slices.…”
Section: Classification Techniques Performance and Marbling Featuresmentioning
confidence: 85%
“…18 Haralick textural features (Haralick, 1979) were extracted from the IMF segmented ROI in order to obtain information regarding the pixel distribution in the image. Textural features have been widely used in previous works for evaluation of quality in different foodstuffs (ElMasry et al, 2007;Huang et al, 2013). To calculate the features a co-occurrence matrix C must be calculated (Eq.…”
Section: Feature Extractionmentioning
confidence: 99%