| 猪肉新鲜度智能检测分级系统研究 |
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| 引用本文： | 郭培源,毕 松,袁 芳. 猪肉新鲜度智能检测分级系统研究[J]. 食品科学, 2010, 31(15): 68-72. DOI: 10.7506/spkx1002-6630-201015015 |
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| 作者姓名： | 郭培源 毕 松 袁 芳 |
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| 作者单位： | 北京工商大学信息工程学院 |
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| 基金项目： | 北京市自然科学基金资助项目(4092012) |
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| 摘 要： | 对表征猪肉新鲜度的氨气和硫化氢气味、图像颜色值、脂肪细胞数和细菌菌斑信息特征量进行检测，通过神经网络技术研究非相干微量参数的多数据融合检测方法，以总挥发性盐基氮(TVB-N)值序列作为SOM网络的输入，利用SOM 神经网络对TVB-N 值序列进行聚类研究，将新鲜度细分为5 个等级，实现了新鲜度等级划分与国家标准和感官检验相一致的结果，从而实现对猪肉新鲜度检测分级辨识。
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| 关 键 词： | 细斑面积 数字图像处理 神经网络 新鲜度等级划分 |
| 收稿时间： | 2009-12-30 |
An Intellectual Rating System for Pork Freshness |
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| GUO Pei-yuan,BI Song,YUAN Fang. An Intellectual Rating System for Pork Freshness[J]. Food Science, 2010, 31(15): 68-72. DOI: 10.7506/spkx1002-6630-201015015 |
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| Authors: | GUO Pei-yuan BI Song YUAN Fang |
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| Affiliation: | (College of Information Engineering, Beijing Technology and Business University, Beijing 100037, China) |
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| Abstract: | Ammoniacal odor, hydrogen sulphide odor, hue, saturation and brightness in the collected image, the number of adipocytes and bacterial plaque of pork reflecting its freshness were measured. A backpropagation (BP) neural network structure, in which TVB-N value was the output and the above 7 non-coherent parameters composed the input was established. Based on this, a SOM network structure, in which TVB-N value was the input, was established for the cluster analysis of TVB-N values collected during pork spoilage and 5 TVB-N value based pork freshness rates were obtained. The rating results were in accordance with the national standard and those from sensory evaluation. This demonstrates high reliability of this rating method. |
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| Keywords: | plaque area digital image processing neural network freshness rating |
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