Analyzing magnetic resonance images of Iberian pork loin to predict its sensorial characteristics

Modeling salt diffusion in Iberian ham by applying MRI and data mining

“…And it is also proved that the MRI analysis by active contours and computational texture feature is appropriate for classification hams as a function of salt diffusion during the post-salting stage. In fact, others studies have also proved the capability of computational texture features to classify fresh and dry-cured Iberian hams as affected by pig feeding background (P erezPalacios et al, 2010a;2011b) and Iberian dry-cured loins depending on their quality categories (Cernadas et al, 2005). Table 3 shows the prediction equations, as a function of computational textures features of each method individually (GLCM, GLRLM and NGLDM), and all together (GLCM þ GLRLM þ NGLDM), and their correlation coefficient (R 2 ) and MAE for the percentage of salt expressed in wet matter and the percentage of salt expressed in dry matter in B (2.10e3.05 and 6.50e9.87, ranges for wet matter and dry matter, respectively) and S (2.83e3.95 and 7.83e10.90, ranges for wet matter and dry matter, respectively) muscles at EPS.…”

MRI-based analysis of feeding background effect on fresh Iberian ham

“…The third and last module included the analysis of the ROIs by applying the three most common methods in computational texture analysis, which require the use of rectangular images. All three methods integrated matrices based on second order statistics (Antequera et al, 2003;Cernadas, Rodríguez, Muriel, & Antequera, 2005): The first one, Grey Level Cooccurrence Matrix (GLCM), was constructed with information of the complete ROI, and presents five features: Energy, Entropy, Haralicks Correlation, Inverse Difference Moment and Inertia. Second, the so-called Neighbouring Grey Level Dependence Matrix (NGLDM) gathered information from square neighbourhoods inside the ROI, providing five features: Small Number Emphasis, SNE; Long Number Emphasis, LNE; Number Nonuniformity, NNU; Second Moment, SM; Entropy, ENT.…”

Meat quality and ultrastructure of muscle tissue from fatteners of Wild Boar, Pulawska and its crossbreed Pulawska × (Hamshire × Wild Boar)

“…Therefore, muscle fibre properties are recognized as the extra criterion for meat quality evaluation. Recently, the consumers' perception of pork has appeared to relate to its nutritional value which seems to drive purchase intent (CERNADAS et al 2005, DRANSFIELD 1999, DRANSFIELD 2001, FIEDLER et al 1998, TYSZKIEWICZ 1995, ŻOCHOWSKA-KUJAWSKA et al 2006). However, the survey studies indicate that consumer acceptability of pork and its products is significantly influenced by the sensory assessment of meat, among others, tenderness being the top rank.…”