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Application of computer vision and electronic nose technologies for quality assessment of color and odor of shrimp and salmon.

机译：计算机视觉和电子鼻技术在虾和鲑鱼颜色和气味质量评估中的应用。

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Current techniques for shrimp and salmon quality evaluations rely on sensory methods. These procedures are subjective, prone to error, and difficult to quantify. Chemical analyses are seldom used by the seafood industry due to the complexity and length of time these methods require. Automated evaluation of color and odor is desirable to reduce subjectivity and discrepancies and assist with the creation of standards for inspectors worldwide. The objectives of this study were to develop color machine vision techniques for visual evaluation and to test electronic nose sensors for odor assessment of raw and cooked shrimp and fresh raw salmon.; A color machine vision system was developed to analyze the color of seafood samples. Hardware consisted of a light box, a video camera, and a frame grabber. Software developed for the Windows environment was able to determine the color of food samples by discretizing the RGB (red, green, blue) color system into 64, 512, or 4096 colors, and by giving color information in different color scales (RGB, L*a*b*, XYZ, or Munsell). The system was able to analyze the color of samples with non-uniform color surfaces, to predict the amount of melanosis (black spots) in shrimp, and to measure color changes of shrimp and salmon during storage.; An electronic nose with twelve conducting polymer sensors was used to measure odors of shrimp and salmon stored at different temperatures, with different levels of spoilage, and treated with Merent chemicals. Discriminant function analysis was used as the pattern recognition technique to differentiate samples based on odors. Results showed that the electronic nose could discriminate differences in odor due to storage time and spoilage levels for shrimp and salmon, and species and food additives in shrimp. Results also showed good correlation of sensor readings with sensory scores and chemical concentrations. Overall, the electronic nose showed good sensitivity and accuracy.; Results from this work could lead to methodologies that will assist in the objective and repeatable quality evaluation of shrimp and salmon. These methods have potential in industrial and regulatory applications where rapid response, no sample preparation, and no need for chemicals are required. Furthermore, expertise in sensory evaluation may be captured and used by instruments.
机译：目前用于虾和鲑鱼质量评估的技术依赖于感官方法。这些过程是主观的，容易出错，并且难以量化。由于这些方法所需的复杂性和时间长短，海鲜行业很少使用化学分析。需要自动评估颜色和气味，以减少主观性和差异，并协助制定全球检查员的标准。这项研究的目的是开发用于视觉评估的彩色机器视觉技术，并测试电子鼻传感器以评估生虾和熟虾以及新鲜生鲑鱼的气味。开发了彩色机器视觉系统来分析海鲜样品的颜色。硬件包括一个灯箱，一个摄像机和一个图像采集卡。为Windows环境开发的软件能够通过将RGB（红色，绿色，蓝色）颜色系统离散为64、512或4096种颜色，并通过提供不同色阶（RGB，L和L）来确定食物样品的颜色。 * a * b *，XYZ或Munsell）。该系统能够分析颜色表面不均匀的样品的颜色，预测虾中黑素病（黑斑）的数量，并测量虾和鲑鱼在储存过程中的颜色变化。一个带有十二个导电聚合物传感器的电子鼻被用来测量在不同温度，不同腐败水平下储藏的虾和鲑鱼的气味，并用Merent化学药品进行处理。判别函数分析用作模式识别技术，可根据气味区分样品。结果表明，电子鼻可以区分由于虾和鲑鱼的储藏时间和腐败程度以及虾的种类和食品添加剂引起的气味差异。结果还显示传感器读数与感官评分和化学浓度有良好的相关性。总体而言，电子鼻显示出良好的灵敏度和准确性。这项工作的结果可能会导致有助于对虾和鲑鱼进行客观和可重复的质量评估的方法。这些方法在工业和法规应用中具有潜力，在这些应用中，快速响应，无需样品制备且不需要化学物质。此外，在感觉评估方面的专业知识可以被仪器捕获和使用。

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