Centre Agriculture Food Environment, University of Trento, San Michele all'Adige, Italy.
Department of Agricultural and Food Sciences, University of Bologna, Cesena, Italy.
J Food Sci. 2023 Jun;88(6):2557-2570. doi: 10.1111/1750-3841.16584. Epub 2023 May 2.
In the present work, a nondestructive device set up for a rapid and reliable freshness assessment of rainbow trout during 10 days of storage in ice was evaluated. The device was characterized by a vector network analyzer interfaced with an open coaxial probe to be placed in contact with the fish eye. The acquisition of the reflected scattering parameter (S11), which is the ratio between the amplitude of the reflected and the incident signal, was assessed in the 50 kHz-3 GHz spectral range. S11 is composed of a real part and an imaginary part, and both parts were used to predict quality index method for freshness evaluations. Partial least squares regression predictive models of the demerit scores related to fish eye attributes (eye pupil and eye shape) and the day of storage were set up. The main results showed that both the real and imaginary parts of the S11 decrease as a function of storage time. The combination with multivariate analysis allowed to set up predictive models of the storage time and the demerit scores with R values up to 0.946 (root mean square error [RMSE] = 0.88 days) and 0.942 (RMSE = 3.17 demerit scores related to the fish eyes attributes), respectively (external validation). According to our results, the proposed cheap solution appears a useful tool for the freshness assessment of rainbow trout. PRACTICAL APPLICATION: This work shows that dielectric properties have the potential to discriminate stored fish according to their freshness quality. A device based on this principle can play a significant role in the postharvest processes, contributing to higher product quality and safety and supporting producers and retailers during the qualitative inspections.
在本工作中，评估了一种用于在冰中储存 10 天期间快速可靠地评估彩虹鳟鱼新鲜度的无损设备。该设备的特点是采用矢量网络分析仪与开放式同轴探头接口，探头与鱼眼接触。在 50 kHz-3 GHz 频谱范围内评估反射散射参数（S11）的幅度，S11 是反射信号和入射信号幅度的比值。S11 由实部和虚部组成，两者都用于预测新鲜度评估的质量指数方法。建立了与鱼眼属性（瞳孔和眼形）和储存天数相关的劣点分数的偏最小二乘回归预测模型。主要结果表明，随着储存时间的增加，S11 的实部和虚部均减小。结合多元分析，可以建立储存时间和劣点分数的预测模型，其 R 值分别高达 0.946（均方根误差 [RMSE] = 0.88 天）和 0.942（RMSE = 3.17 与鱼眼属性相关的劣点分数）（外部验证）。根据我们的结果，提出的廉价解决方案似乎是评估彩虹鳟鱼新鲜度的有用工具。实际应用：这项工作表明，介电特性有可能根据鱼类的新鲜度质量来区分储存的鱼类。基于这一原理的设备可以在收获后过程中发挥重要作用，有助于提高产品质量和安全性，并在质量检查期间为生产者和零售商提供支持。
