Kim Sang Seop, Yun Dae-Yong, Lee Gyuseok, Park Seul-Ki, Lim Jeong-Ho, Choi Jeong-Hee, Park Kee-Jai, Cho Jeong-Seok
Food Safety and Distribution Research Group, Korea Food Research Institute, Wanju 55365, Republic of Korea.
Smart Food Manufacturing Project Group, Korea Food Research Institute, Wanju 55365, Republic of Korea.
Foods. 2024 Oct 11;13(20):3228. doi: 10.3390/foods13203228.
In the present investigation, we have devised a hyperspectral imaging (HSI) apparatus to assess the chemical characteristics and freshness of the yellow croaker () throughout its storage period. This system operates within the shortwave infrared spectrum, specifically ranging from 900 to 1700 nm. A variety of spectral pre-processing techniques, including standard normal variate (SNV), multiple scatter correction, and Savitzky-Golay (SG) derivatives, were employed to augment the predictive accuracy of total volatile basic nitrogen (TVB-N)-which serves as a critical freshness parameter. Among the assessed methodologies, SG-1 pre-processing demonstrated superior predictive accuracy (R = 0.8166). Furthermore, this investigation visualized freshness indicators as concentration images to elucidate the spatial distribution of TVB-N across the samples. These results indicate that HSI, in conjunction with chemometric analysis, constitutes an efficacious instrument for the surveillance of quality and safety in yellow croakers during its storage phase. Moreover, this methodology guarantees the freshness and safety of seafood products within the aquatic food sector.
在本研究中,我们设计了一种高光谱成像(HSI)设备,用于评估黄鱼在整个储存期间的化学特性和新鲜度。该系统在短波红外光谱范围内运行,具体为900至1700纳米。采用了多种光谱预处理技术,包括标准正态变量变换(SNV)、多元散射校正和Savitzky-Golay(SG)导数,以提高作为关键新鲜度参数的总挥发性盐基氮(TVB-N)的预测准确性。在所评估的方法中,SG-1预处理显示出卓越的预测准确性(R = 0.8166)。此外,本研究将新鲜度指标可视化为浓度图像,以阐明TVB-N在样品中的空间分布。这些结果表明,HSI结合化学计量分析,构成了一种在黄鱼储存阶段监测其质量和安全的有效工具。此外,该方法确保了水产食品行业中海鲜产品的新鲜度和安全性。