食品科学 ›› 2011, Vol. 32 ›› Issue (17): 194-198.doi: 10.7506/spkx1002-6630-201117040

• 基础研究 • 上一篇    下一篇

热处理单宁酸对冷鲜猪肉中微生物生长的抑制作用

刘超群,王宏勋*,林 睿,赵国娇   

  1. 武汉工业学院食品科学与工程学院
  • 发布日期:2011-08-30
  • 基金资助:
    武汉市科技攻关计划项目(200920322146);卫生部卫生行业科研专项(200902009);      武汉市科技局十大科技专项配套平台建设项目(201021037379)

Inhibitory Effect of Thermally Processed Tannic Acid on Bacteria in Chilled Fresh Pork

LIU Chao-qun,WANG Hong-xun*,LIN Rui,ZHAO Guo-jiao   

  1. (College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China)
  • Published:2011-08-30

摘要: 用平皿扩散法测定热处理单宁酸对假单胞菌、热死环丝菌、金黄色葡萄球菌和大肠杆菌的抑制效果,结果表明:热处理单宁酸对热死环丝菌和金黄色葡萄球菌有明显的抑制作用,质量浓度为2.50g/100mL时抑菌圈可达到22mm。比较热处理单宁酸、乳酸、75%酒精对冷鲜猪肉中微生物生长的抑制作用,结果表明:热处理单宁酸能有效抑制冷鲜猪肉中菌落总数的增加,较相同质量浓度的乳酸抑菌效果更为明显。建立4℃储藏条件下不同质量浓度热处理单宁酸处理的冷鲜猪肉中微生物的生长动力学模型,通过模型参数判断不同质量浓度的热处理单宁酸对冷鲜猪肉中微生物的抑制效果,结果表明:在实验范围内热处理单宁酸质量浓度越高,抑菌效果越好,当热处理单宁酸质量浓度高于0.63g/100mL后,抑菌效果增加不明显。

关键词: 冷鲜猪肉, 热处理单宁酸, 抑菌作用, 预测模型, 延滞期

Abstract: The inhibitory effect of thermally processed tannic acid against Pseudomonas, B. thermosphact, Staphylococcus and Enterobacteriaceae was explored by disc diffusion method. The results indicated that thermally processed tannic acid at the concentration of 2.50% could inhibit B. thermosphact and Staphylococcus with an inhibitory zone of 22 mm. The inhibitory effects of thermally processed tannic acid, lactic acid and 75% aqueous ethanol against bacterial growth in chilled fresh pork were comparatively observed. Compared with lactic acid, thermally processed tannic acid at the same concentration exhibited better inhibitory effect against bacterial growth in chilled fresh pork. The Gompertz model was employed to describe growth parameters such as specific growth rate and lag time of microorganisms in fresh pork stored at 4℃. Increasing concentration of tannic acid revealed better antibacterial activity. However, when the concentration of tannic acid was higher than 0.63%, the increase of lag time was not obvious.

Key words: chilled fresh pork, thermally processed tannic acid, antibacterial activity, prediction model, lag time

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