肉类研究2017，Vol.31Issue(3)：35-39,5.DOI:10.7506/rlyj1001-8123-201703007
基于高光谱成像技术的鸡肉菌落总数快速无损检测
Rapid Non-Destructive Detection of Total Bacterial Count in Chicken Using Hyperspectral Imaging
摘要
Abstract
In order to develop a rapid and non-destructive method to predict total bacterial count in chicken breasts by using hyperspectral imaging technology, 83 chicken breast samples refrigerated at 4 ℃ were collected from local supermarket and 63 of these were used as calibration samples. The hyperspectral scattering image of each sample was collected by using hyperspectral imaging system in the wavelength range of 400-1100 nm. Various algorithm combinations were used to preprocess the hyperspectral information of the samples to enhance the performance of the model developed by using partial least square regression (PLSR) algorithm. Based on the predictive accuracy and stability of the model, the efficiency of different algorithm combinations for spectral preprocessing were evaluated and discussed. The results showed that the optimal model performance was achieved by preprocessing of the hyperspectral information with standard normalized variate. The standard error of calibration (sEC) and standard error of prediction (SEP) of the model were 0.40 and 0.57, respectively. The correlation coefficients of calibration (RC) and prediction (RP) were 0.93 and 0.86, respectively. The optimal model allowed effective prediction of distribution maps of total bacterial count in chicken breasts.关键词
鸡肉/菌落总数/高光谱成像/图像预处理/偏最小二乘法(PLSR)/无损检测Key words
chicken/total bacterial count/hyperspectral imaging/image processing/partial least square regression (PLSR)/non-destructive detection分类
化学化工引用本文复制引用
李文采,乔晓玲,刘飞,田寒友,邹昊,王辉,张振琪,郑晓春,李永玉,李家鹏..基于高光谱成像技术的鸡肉菌落总数快速无损检测[J].肉类研究,2017,31(3):35-39,5.基金项目
"十二五"国家科技支撑计划项目(2014BAD04B05) （2014BAD04B05）
