Xiao-Yu Tian1, Joshua H Aheto1, Xingyi Huang1, Kaiyi Zheng1, Chunxia Dai1,2, Chenquang Wang1, Jun-Wen Bai1. 1. School of Food and Biological Engineering, Jiangsu University, Xuefu Road 301, Zhenjiang, 212013, Jiangsu, China. 2. School of Electrical and Information Engineering, Jiangsu University, Xuefu Road 301, Zhenjiang, 212013, Jiangsu, China.
Abstract
BACKGROUND: Food processing induces various modifications that affect the structure, physical and chemical properties of food products and thus affect 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 ion mobility spectrometry GC-IMS). Models based on partial least square regression (PLSR) were developed using the full HSI spectrum variables as well as optimum variables selected through a competitive adaptive reweighted sampling algorithm. RESULTS: 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 (O-C-15 and O-C-20). 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. The GC-IMS identified 35 volatile components, including hexanal and pentanal, which are also known to have a higher lipid oxidation specificity. CONCLUSION: 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. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
BACKGROUND: Food processing induces various modifications that affect the structure, physical and chemical properties of food products and thus affect 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 ion mobility spectrometry GC-IMS). Models based on partial least square regression (PLSR) were developed using the full HSI spectrum variables as well as optimum variables selected through a competitive adaptive reweighted sampling algorithm. RESULTS: 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 (O-C-15 and O-C-20). 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. The GC-IMS identified 35 volatile components, including hexanal and pentanal, which are also known to have a higher lipid oxidation specificity. CONCLUSION: 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. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.