Tavitchasri, Piyada

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Tavitchasri, Piyada
Alternative Name
Tavitchasri, P.
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Email
piyada.ta@kmitl.ac.th

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    Effect of different aging methods and periods on physical and chemical beef qualities from Longissimus thoracis
    (2026-05-01)
    Pilasombut, K.
    ;
    Paitheanchai, W.
    ;
    Prachom, N.
    ;
    Rakmae, S.
    ;
    Tavitchasri, P.
    The results showed that the aging method and aging period significantly (p<0.05) affected aging loss, trimming loss, and cooking loss. Aging loss and trimming loss of DA and DB beef were higher than those of WV and WS beef (p<0.05). However, cooking loss in WV and WS beef was higher than DA and DB beef. No significant differences (p>0.05) were observed among aging methods in pH, colour (L*, a*, and b*), Warner-Bratzler shear force (WBSF), lipid oxidation (TBARS). Prolonged aging time (up to 4 weeks) resulted in more tender meat, while lipid oxidation increased (p<0.05). Additionally, beef colour changed significantly with increasing aging time (p<0.05). There were not different in percentage of fat, dry matter, ash, or moisture among aging method. However, DA and AB beef showed higher percentage of protein than WV and WS beef (p<0.05). These findings can be applied to develop for beef industry, particularly small-scale beef retailers and restaurants businesses, could be enhance value of premium grade beef in Thailand.
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    A nonintrusive beef grading evaluation based on marbling fat imaging by using K-Means Clustering Technique
    (2024-03-01)
    Pilasombut, K.
    ;
    Tavitchasri, P.
    ;
    Manop, C.
    ;
    Jirasuwankul, N.
    An alternative technique of beef quality assessment and grading was proposed using image analysis based on the K-means clustering algorithm as a semi-automated and nonintrusive approach. An input image of the rib-eye meat area was converted into L*a*b* color space, followed by classifying groups of features over the spatial domain. By performing a search and cluster, iterating the features of the target image in a*b* axes resulted in several distinct image zones categorized by different K-groups of features. Marbling fat was estimated in conjunction with quality assessment as an arbitrary grading system. Experimental testing on both synthetic and real image data suggested accuracy better than 95% of averaged. As comparison to conventional methods, this technique is nonintrusive, nondestructive, fast and economic for application and implementation as a measuring tool in the meat research industry.