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An Advanced Colour Calibration Method for Fish Freshness Assessment: a Comparison Between Standard and Passive Refrigeration Modalities

机译:鱼类新鲜度评估的高级颜色校准方法:标准制冷方式与被动制冷方式之间的比较

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摘要

Freshness represents a pivotal aspect in fish product for both security and quality. Its evaluation still represents the key factor driving the consumer' choices. Fish appearance is affected by many different factors that demand the contribution of different disciplines to be understood: from the physical and optical properties to the slaughtering and post-slaughtering conditions. An innovative preservation system is represented by the Passive Refrigeration PRS (TM) developed for the preservation and transport of perishable food products. Scientific methods for product freshness evaluation may be conveniently divided into two categories: sensorial and instrumental. In this study, an instrumental method of colour calibration and discrimination is proposed at pilot scale for automatic evaluation of gilthead seabream (Sparus aurata) freshness. We propose a non-destructive method based on the colorimetric imaging of the whole external body of seabreams to evaluate through multivariate partial least squares which approach the differences in the freshness preservation under four refrigeration modalities. The matrix of the independent variables is represented by RGB values for each pixel belonging to an extracted region of interest (129,633 values). The dependent variable is composed by two dummy variable corresponding to fresh (T-0) or non-fresh (T-2) individuals. T-1 individuals were used as external test. The results quantified significant colorimetric differences between fresh and non-fresh fish. All fish used to create the model (T-0 and T-2) were correctly classified as fresh or non-fresh, while external test individuals (T-1) were all classified as fresh. The proposed imaging method merges different image analysis techniques: (a) colorimetric calibration, (b) morphometric superimposition and (c) partial least square discriminant analysis modelling. This innovative and non-destructive approach allows the automatic assessment of fish freshness.
机译:新鲜度是鱼产品安全性和质量的关键方面。它的评估仍然代表了驱动消费者选择的关键因素。鱼的外观受到许多不同因素的影响,这些因素需要了解不同学科的贡献:从物理和光学特性到屠宰和屠宰后状况。创新的保鲜系统以被动保鲜PRS(TM)为代表,该保鲜系统是为易腐食品的保鲜和运输而开发的。产品新鲜度评估的科学方法可以方便地分为两类:感官和工具。在这项研究中,提出了一种中试规模的颜色校准和辨别的仪器方法,用于自动评估金头鲷(Sparus aurata)的新鲜度。我们提出了一种基于整个鲷鱼比色成像的非破坏性方法,以通过多元偏最小二乘方法进行评估,该方法在四种制冷方式下均能接近新鲜度的差异。自变量矩阵由属于所提取的感兴趣区域的每个像素的RGB值表示(129,633个值)。因变量由对应于新鲜(T-0)或不新鲜(T-2)个体的两个虚拟变量组成。将T-1个人用作外部测试。结果量化了新鲜鱼和非新鲜鱼之间显着的比色差异。用于创建模型的所有鱼类(T-0和T-2)均正确分类为新鲜或不新鲜,而外部测试人员(T-1)均分类为新鲜。拟议的成像方法合并了不同的图像分析技术:(a)比色校准,(b)形态叠加和(c)偏最小二乘判别分析建模。这种创新且无损的方法可以自动评估鱼类的新鲜度。

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