Structured-illumination reflectance imaging for the evaluation of microorganism contamination in pork:effects of spectral and imaging features on its prediction performance  

作　　者：Binjing Zhou Xiaohua Liu Yan Ge Kang Tu Jing Peng Juan Francisco García-Martín Jie Wu Weijie Lan Leiqing Pan 

机构地区：[1]College of Food Science and Technology,Nanjing Agricultural University,Nanjing 210095,China [2]College of Engineering,Nanjing Agricultural University,Nanjing 210095,China [3]The Academy of Science,Nanjing Agricultural University,Nanjing 210095,China [4]Departamento de Ingeniería Química,Facultad de Química,Universidad de Sevilla,Sevilla 41012,Spain [5]School of Food and Biological Engineering,Bengbu University,Bengbu 233030,China

出　　处：《Food Science and Human Wellness》2025年第2期683-691,共9页食品科学与人类健康(英文)

基　　金：supported by Key Research&Development Program of Jiangsu Province in China(BE2020693);Major Project of Science and Technology of Anhui Province(201903a06020010);Joint Key Project of Science and Technology Innovation of Yangtze River Delta in Anhui Province(202004g01020009);the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)。

摘　　要：Structured-illumination reflectance imaging(SIRI)provides a new means for food quality detection.This original work investigated the capability of(SIRI)technique coupled with multivariate chemometrics to evaluate the microbial contamination in pork inoculated with Pseudomonas fluorescens and Brochothrix thermosphacta during storage at different temperatures.The prediction performances based on different spectrum and the textural features of direct component and amplitude component images demodulated from the SIRI pattern,as well as their data fusion were comprehensively compared.Based on the full wavelength spectrum(420-700 nm)of amplitude component images,the orthogonal signal correction coupled with support vector machine regression provided the best predictions of the number of P.fluorescens and B.thermosphacta in pork,with the determination coefficients of prediction(R_(p)^(2))values of 0.870 and 0.906,respectively.Besides,the prediction models based on the amplitude component or direct component image textural features and the data fusion models using spectrum and textural features from direct component and amplitude component images cannot significantly improve their prediction accuracy.Consequently,SIRI can be further considered as a potential technique for the rapid evaluation of microbial contaminations in pork meat.

关 键 词：Pseudomonas fluorescens Brochothrix thermosphacta PORK Structured-illumination reflectance imaging Data fusion 

分 类 号：F41[经济管理—产业经济]