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Food Chem

Title:		Application of volatile and spectral profiling together with multimode data fusion strategy for the discrimination of preserved eggs
Author(s):		Ren Y; Huang X; Aheto JH; Wang C; Ernest B; Tian X; He P; Chang X; Wang C;
Address:		"School of Food and Biological Engineering, Jiangsu University, Xuefu Road 301, Zhenjiang 212013, Jiangsu, PR China; School of Smart Agriculture, Suzhou Polytechnic Institute of Agriculture, Xiyuan Road 279, Suzhou 215008, Jiangsu, PR China. School of Food and Biological Engineering, Jiangsu University, Xuefu Road 301, Zhenjiang 212013, Jiangsu, PR China. Electronic address: h_xingyi@163.com. School of Food and Biological Engineering, Jiangsu University, Xuefu Road 301, Zhenjiang 212013, Jiangsu, PR China. School of Food and Biological Engineering, Jiangsu University, Xuefu Road 301, Zhenjiang 212013, Jiangsu, PR China. Electronic address: wangcq@ujs.edu.cn. School of Food and Biological Engineering, Jiangsu University, Xuefu Road 301, Zhenjiang 212013, Jiangsu, PR China; Laboratory Services Department, Food and Drugs Authority, Accra, Ghana. Gaoyou Qinyou Egg Products Co. LTD, Gaoyou, China"
Journal Title:		Food Chem
Year:		2021
Volume:		20201031
Issue:
Page Number:		128515 -
DOI:		10.1016/j.foodchem.2020.128515
ISSN/ISBN:		1873-7072 (Electronic) 0308-8146 (Linking)
Abstract:		"The maturity level of eggs during pickling is conventionally assessed by choosing few eggs from each curing batch to crack open. Yet, this method is destructive, creates waste and has consequences for financial losses. In this work, the feasibility of integrating electronic nose (EN) with reflectance hyperspectral (RH) and transmittance hyperspectral (TH) data for accurate classification of preserved eggs (PEs) at different maturation periods was investigated. Classifier models based solely on RH and TH with EN achieved a training accuracy (93.33%, 97.78%) and prediction accuracy (88.89%; 93.33%) respectively. The fusion of the three datasets, (EN + RH + TH) as a single classifier model yielded an overall training accuracy of 98.89% and prediction accuracy of 95.56%. Also, 52 volatile compounds were obtained from the PE headspace, of which 32 belonged to seven functional groups. This study demonstrates the ability to integrate EN with RH and TH data to effectively identify PEs during processing"
Keywords:		Animals Ducks Eggs/*analysis *Electronic Nose Food Analysis/methods Food Preservation/*methods Gas Chromatography-Mass Spectrometry/methods Hyperspectral Imaging/*methods Volatile Organic Compounds/*analysis 1-Hexanol (PubChem CID: 8103) 2-Heptanone (PubC;
Notes:		"MedlineRen, Yi Huang, Xingyi Aheto, Joshua H Wang, Chengquan Ernest, Bonah Tian, Xiaoyu He, Peihuan Chang, Xianhui Wang, Chen eng England 2020/11/09 Food Chem. 2021 May 1; 343:128515. doi: 10.1016/j.foodchem.2020.128515. Epub 2020 Oct 31"