基于模糊鉴别主成分分析的生菜贮藏时间鉴别  

Discrimination of lettuce storage time based on fuzzy discriminant principal component analysis

作　　者：侯晓蕾 武小红[2] 武斌[3] 沈嘉棋 汪鑫 HOU Xiao-lei;WU Xiao-hong;WU Bin;SHEN Jia-qi;WANG Xin(Institute of Talented Engineering Students,Jiangsu University,Zhenjiang,Jiangsu 212013,China;School of Electrical and Information Engineering,Jiangsu University,Zhenjiang,Jiangsu 212013,China;School of Information Engineering,Chuzhou Polytechnic,Chuzhou,Anhui 239000,China)

机构地区：[1]江苏大学卓越学院,江苏镇江212013 [2]江苏大学电气信息工程学院,江苏镇江212013 [3]滁州职业技术学院信息工程学院,安徽滁州239000

出　　处：《食品与机械》2021年第10期119-123,共5页Food and Machinery

基　　金：国家自然科学基金资助项目(编号:31471413);安徽省教育厅高校自然科学研究重点项目(编号:KJ2019A1129);滁州职业技术学院校级自科重点项目(编号:YJZ-2020-12);滁州职业技术学院院级人才项目(编号:YG2019026,YG2019024);江苏大学大学生创新训练计划项目(编号:202010299246Y)。

摘　　要：目的:设计一种较为准确的生菜贮藏时间鉴别模型。方法:以新鲜生菜为试验对象,分别采用主成分分析、鉴别主成分分析、模糊鉴别主成分分析3种特征提取方法对预处理后的生菜近红外光谱数据进行特征提取,选出具有较高准确度的贮藏时间鉴别算法,并建立基于模糊鉴别主成分分析的生菜贮藏时间鉴别模型。结果:利用模糊鉴别主成分分析进行特征提取后的鉴别准确度显著增加。主成分分析、鉴别主成分分析和模糊鉴别主成分分析的最高准确度分别为46.67%,86.67%,93.33%。结论:采用近红外光谱分析和模糊鉴别主成分分析的鉴别模型具有较高的准确性和优越性。Objective:This study focuses on designing a more accurate identification model of lettuce storage time.Methods:The near-infrared spectral data from extraction feature of the preprocessed lettuce was obtained by principal component analysis(PCA),discriminant principal component analysis(DPCA)and fuzzy discriminant principal component analysis(FDPCA)respectively.An algorithm of higher accuracy in storage time discrimination was explored,and then a lettuce storage time discriminant model based on FDPCA was established.Results:The identification accuracy raised dramatically after FDPCA was used to extract feature.When employing PCA,DPCA and FDPCA algorithms,the highest accuracies achieved were 46.67%,86.67%and 93.33%respectively.Conclusion:This discrimination model of employing near-infrared spectroscopy and FDPCA was characterized by high accuracy and superiority.

关 键 词：生菜 贮藏时间 近红外光谱 模糊鉴别主成分分析 

分 类 号：TS255.7[轻工技术与工程—农产品加工及贮藏工程] O657.33[轻工技术与工程—食品科学与工程]