کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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5767623 | 1413202 | 2017 | 7 صفحه PDF | دانلود رایگان |
- Novel immunohistochemical method detecting muscle fibre degradation in comminuted chicken meat.
- High correlation between measured and expected relative amount of intact muscle fibre in meat samples.
- Grading of muscle products based on degree of degradation is now possible.
The potential of a novel immunohistochemical method detecting the muscle protein meromyosin and the basement membrane protein laminin to objectively and accurately determine the degree of degradation of muscle tissue in comminuted chicken meat was investigated in comparison to three different conventional methods, two slightly different toluidine blue (TB) staining procedures and a haematoxylin-eosin (HE) staining. All samples were evaluated for degree of muscle degradation, one method by image analysis system and three by visual assessment of degree of degradation. Analyses were carried out on reference samples consisting of mixtures of emulsified and minced meat in steps of 10%. The immunohistochemical approach (LAM) showed better selectivity and good image quality. The correlation (R) between the amount of minced meat in mixtures and degree of degradation were higher and consistent by this approach (0.94 compared with 0.62, 0.61, and 0.85 for thigh muscles by LAM, HE, TB-Max Rubner-Institute (MRI) and TB-Leatherhead Food Research (LFR), respectively, and 0.91 compared with 0.73, 0.73 and 0.98 for breast muscle by LAM, HE, TB-MRI and TB-LFR, respectively). When applied to industrial samples, the results showed that it is possible by all methods to separate at least two different groups based on degree of degradation. In conclusion, the good image contrast, specificity of the staining and objectivity and transparency of the measurement speaks in favor of the LAM method as optimal to quantify degree of degradation of muscle structure in comminuted and fragmented chicken meat and obviously a likely candidate for a standard method.
Journal: Food Control - Volume 73, Part B, March 2017, Pages 133-139