食品科学

• 基础研究 • 上一篇    下一篇

基于图像分析的丹贝发酵终点判定方法

梁敬东1,孙吉祥1,樊 娟2,李 伟2,董明盛2,*   

  1. 1.南京农业大学信息科技学院,江苏 南京 210095;2.南京农业大学食品科技学院,江苏 南京 210095
  • 出版日期:2013-09-15 发布日期:2013-09-27
  • 通讯作者: 董明盛
  • 基金资助:

    国家“863”计划项目(2011AA100903;2013BAD18B01-4);国家自然科学青年基金项目(31201422);
    江苏省自然科学基金项目(BK2011651);教育部博士点基金项目(新教师类)(20110097120028);
    江苏省科技攻关计划项目(BE2006301);江苏高校优势学科建设工程资助项目(PAPD)

Determination of Fermentation End-point of Tempeh by Image Analysis

LIANG Jing-dong1,SUN Ji-xiang1,FAN Juan2,LI Wei2,DONG Ming-sheng2,*   

  1. 1. College of Information Science and Technology, Nanjing Agricultural University, Nanjing 210095, China;
    2. College of Food Science and Technology, Nanjing Agricultural University, Nanjing 210095, China
  • Online:2013-09-15 Published:2013-09-27
  • Contact: DONG Ming-sheng

摘要:

丹贝是一种发源于印尼的发酵食品,其品质主要取决于表面菌丝的生长情况。为了快捷、可靠、无损的自动化判定丹贝的发酵终点,提出了基于图像分析的判定方法。在丹贝发酵过程中使用数码相机定时获取其表面图像,通过分析图像的纹理特征,将图像的梯度信息与亮度信息相结合,制定了新的丹贝表面图像的均匀性评价指标。结果表明:该指标在丹贝发酵终点(由人工感官判定为22h)取得最小值,且在发酵终点附近时段内(21~23h)变化明显,对于像素为2592×3314的丹贝表面图像,分别为0.054(21h)、0.044(22h)、0.055(23h);而传统的丹贝表面图像的均匀性评价指标(亮度标准差)则无显著变化,分别为8.3(21h)、8.2(22h)、8.2(23h)。提示该方法对于多种像素的丹贝表面图像均能快速、准确的判定出丹贝的发酵终点,具有良好的稳定性且与人工的感官评价一致。

关键词: 图像分析, 梯度, 亮度, 丹贝, 发酵终点

Abstract:

Tempeh is a fermented food originated in Indonesia. Its nutritional quality depends on the extent of mycelial
growth on its surface. A method based on image analysis was proposed to determine the fermentation end-point
automatically, quickly, reliably and non-destructively. Tempeh's surface images were collected by using a digital camera
during its fermentation process and a new uniformity evaluation of tempeh’s surface image was formulated through analysis
of texture features and combination of gradient and luminance information. The indicator reached the minimum value at the
fermentation end-point (22 h, determined by sensory evaluation) and showed a significant change near the fermentation endpoint.
When the pixel of tempeh’s surface image was 2592 × 3314, the indicator's value was 0.054 at 21 h, 0.044 at 22 h
and 0.055 at 23 h. However, no significant change was observed in the traditional uniformity evaluation of tempeh’s surface
image (standard deviation of luminance) in which the values were 8.3 at 21 h, 8.2 at 22 h and 8.2 at 23 h. The experimental
results showed that the method could quickly and accurately determine tempeh’s fermentation end-point based on surface
images with different pixels, had a good stability and was consistent with artificial sensory evaluation.

Key words: image analysis, gradient, luminance, tempeh, fermentation end-point

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