Xie Anguo, Zhang Yu, Wu Han, Chen Meng
Zhang Zhongjing School of Chinese Medicine, Nanyang Institute of Technology, Nanyang 473000, China.
School of Intelligent Manufacturing, Nanyang Institute of Technology, Nanyang 473000, China.
Foods. 2024 Jun 17;13(12):1903. doi: 10.3390/foods13121903.
The process of meat postmortem aging is a complex one, in which improved tenderness and aroma coincide with negative effects such as water loss and microbial growth. Determining the optimal postmortem storage time for meat is crucial but also challenging. A new visual monitoring technique based on hyperspectral imaging (HSI) has been proposed to monitor pork aging progress. from 15 pigs were stored at 4 °C for 12 days while quality indexes and HSI spectra were measured daily. Based on changes in physical and chemical indicators, 100 out of the 180 pieces of meat were selected and classified into rigor mortis, aged, and spoilt meat. Discrete wavelet transform (DWT) technology was used to improve the accuracy of classification. DWT separated approximate and detailed signals from the spectrum, resulting in a significant increase in classification speed and precision. The support vector machine (SVM) model with 70 band spectra achieved remarkable classification accuracy of 97.06%. The study findings revealed that the aging and microbial spoilage process started at the edges of the meat, with varying rates from one pig to another. Using HSI and visualization techniques, it was possible to evaluate and portray the postmortem aging progress and edible safety of pork during storage. This technology has the potential to aid the meat industry in making informed decisions on the optimal storage and cooking times that would preserve the quality of the meat and ensure its safety for consumption.
肉类宰后成熟过程是一个复杂的过程,在此过程中,嫩度和香气的改善与诸如水分流失和微生物生长等负面影响同时存在。确定肉类的最佳宰后储存时间至关重要但也具有挑战性。一种基于高光谱成像(HSI)的新型视觉监测技术已被提出用于监测猪肉的成熟进程。从15头猪身上获取的猪肉在4℃下储存12天,同时每天测量其品质指标和HSI光谱。根据理化指标的变化,从180块肉中选出100块,并分为尸僵肉、成熟肉和变质肉。采用离散小波变换(DWT)技术提高分类准确率。DWT从光谱中分离出近似信号和细节信号,从而显著提高了分类速度和精度。具有70个波段光谱的支持向量机(SVM)模型实现了97.06%的显著分类准确率。研究结果表明,老化和微生物腐败过程从肉的边缘开始,不同猪之间的速率有所不同。利用HSI和可视化技术,可以评估和描绘猪肉在储存期间的宰后成熟进程和食用安全性。这项技术有潜力帮助肉类行业就最佳储存和烹饪时间做出明智决策,从而保持肉的品质并确保其食用安全。