基于高光谱反透射图像的新疆冰糖心红富士水心鉴别  

Identification of Watercore in Xinjiang-Grown Fuji Apples Based on Reflection-Transmission Hyperspectral Imaging

作　　者：郭俊先 马永杰 田海清[2] 黄华[3] 史勇 周军 GUO Junxian;MA Yongjie;TIAN Haiqing;HUANG Hua;SHI Yong;ZHOU Jun(College of Mechanical and Electronic Engineering,Xinjiang Agricultural University,ürümqi 830052,China;College of Mechanical and Electronic Engineering,Inner Mongolia Agricultural University,Hohhot 010018,China;College of Mathematics and Physics,Xinjiang Agricultural University,ürümqi 830052,China)

机构地区：[1]新疆农业大学机电工程学院,新疆乌鲁木齐830052 [2]内蒙古农业大学机电工程学院,内蒙古呼和浩特010018 [3]新疆农业大学数理学院,新疆乌鲁木齐830052

出　　处：《食品科学》2020年第6期278-284,共7页Food Science

基　　金：国家自然科学基金面上项目(61367001);新疆农业大学研究生科研创新项目(XJAUGRI2017-031)。

摘　　要：采用高光谱成像技术结合化学计量法,采集新疆冰糖心红富士好果与水心病果样本在波长范围380~1004 nm的可见近红外高光谱反透射图像,选取感兴趣区域获得平均光谱,对原始光谱采用直接差分一阶求导等9种光谱预处理方法,再分别用主成分分析、快速独立分量分析、相关系数法完成数据降维,结合贝叶斯判别、K最近邻法、马氏距离判别、最小二乘支持向量机、二次线性判别方法识别是否有水心病。结果表明,主成分分析提取前15主成分,采用标准正态变量变换-主成分分析-最小二乘支持向量机与多元散射校正-主成分分析-最小二乘支持向量机模型识别效果最优,校正集和预测集识别率分别为100%和91.2%。In this research,hyperspectral technique combined with chemometrics was used to discriminate between Xinjiang-grown Fuji apples with and without watercore.Visible and near infrared hyperspectral images were acquired within the wavelength range of 380 to 1004 nm.The region of interest was selected from the images to calculated average spectra.The original spectra were preprocessed by 9 different methods such as direct difference first-order derivative,and then principal component analysis(PCA),independent component analysis and correlation coefficient method were used to reduce the dimensionality of the spectral data.Finally,Bayes discriminant,K nearest neighbor method,Mahalanobis distance discriminant,least squares support vector machine,quadratic linear discriminant method were combined to perform pattern recognition.Results indicated that 15 principal components were extracted by PCA.The model developed using standard normal variate(SNV)or multiple scatter calibration(MSC)combined with PCA and least squares support vector machine(LSSVM)exhibited the best recognition performance with identification rates for the calibration and prediction sets of 100%and 91.2%,respectively.

关 键 词：苹果水心病 高光谱图像 化学计量法 主成分分析 模式识别 

分 类 号：S661.1[农业科学—果树学]