Tian Xiao-Yu, Aheto Joshua H, Huang Xingyi, Zheng Kaiyi, Dai Chunxia, Wang Chengquan, Bai Jun-Wen
School of Food and Biological Engineering, Jiangsu University, Zhenjiang, PR China.
School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, PR China.
J Sci Food Agric. 2021 Nov;101(14):5972-5983. doi: 10.1002/jsfa.11251. Epub 2021 Apr 29.
Food processing induces various modifications that affect the structure, physical and chemical properties of food products and hence the acceptance of the product by the consumer. In this work, the evolution of volatile components, 2-thiobarbituric acid reactive substances (TBARS), moisture content (MC) and microstructural changes of pork was investigated by hyperspectral (HSI) and confocal imaging (CLSM) techniques in synergy with gas chromatography-ion mobility spectrometry (GC-IMS). Models based on partial least squares regression (PLSR) were developed using the full HSI spectrum variables as well as optimum variables selected through a competitive adaptive reweighted sampling algorithm.
Prediction results for MC and TBARS using multiplicative scatter correction pre-processed spectra models demonstrated greater efficiency and predictability with determination coefficient of prediction of 0.928, 0.930 and root mean square error of prediction of 0.114, 1.002, respectively. Major structural changes were also observed during CLSM imaging, which were greatly pronounced in pork samples oven cooked for 15 and 20 h. These structural changes could be related to the denaturation of the major meat components, which could explain the loss of moisture and the formation of TBARS visualized from the HSI chemical distribution maps. GC-IMS identified 35 volatile components, including hexanal and pentanal, which are also known to have a higher lipid oxidation specificity.
The synergistic application of HSI, CLSM and GC-IMS enhanced data mining and interpretation and provided a convenient way for analyzing the chemical, structural and volatile changes occurring in meat during processing. © 2021 Society of Chemical Industry.
食品加工会引发各种变化,这些变化会影响食品的结构、物理和化学性质,进而影响消费者对产品的接受度。在本研究中,利用高光谱成像(HSI)和共聚焦成像(CLSM)技术,结合气相色谱 - 离子迁移谱(GC - IMS),研究了猪肉中挥发性成分、硫代巴比妥酸反应物(TBARS)、水分含量(MC)的变化以及微观结构的改变。使用全HSI光谱变量以及通过竞争性自适应重加权采样算法选择的最优变量,建立了基于偏最小二乘回归(PLSR)的模型。
使用乘法散射校正预处理光谱模型对MC和TBARS的预测结果显示出更高的效率和可预测性,预测决定系数分别为0.928和0.930,预测均方根误差分别为0.114和1.002。在CLSM成像过程中也观察到了主要的结构变化,在烤箱中烤制15和20小时的猪肉样品中这种变化尤为明显。这些结构变化可能与主要肉类成分的变性有关,这可以解释从HSI化学分布图中观察到的水分损失和TBARS的形成。GC - IMS鉴定出35种挥发性成分,包括己醛和戊醛,它们也具有较高的脂质氧化特异性。
HSI、CLSM和GC - IMS的协同应用增强了数据挖掘和解释能力,并为分析肉类加工过程中发生的化学、结构和挥发性变化提供了一种便捷的方法。© 2021化学工业协会。