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作 者:Yingwang Gao Qiwei Li Xiuqin Rao Yibin Ying
机构地区:[1]College of Biosystems Engineering and Food Science,Zhejiang University,Hangzhou 310058,China [2]Key Laboratory of Equipment and Informatization in Environment Controlled Agriculture,Ministry of Agriculture,Hangzhou 310058,China [3]Faculty of Agricultural and Food Science,Zhejiang A&F University,Hangzhou 311300,China
出 处:《International Journal of Agricultural and Biological Engineering》2018年第2期153-157,共5页国际农业与生物工程学报(英文)
基 金:supported by the National Key Research and Development Plan of China(2016YFD0701603).
摘 要:Sprouted potatoes are not allowed for healthy diet.A good knowledge of the sprouting stage of potatoes can help manage the storage conditions and guide market distribution,thus enabling the quality assurance of potatoes on table.This article presented an intelligent method for precautionary analysis of potato eyes based on hyperspectral imaging technique.Potential potato eyes were classified into two categories according to the time gap to the sprouting date,i.e.by-sprouting and pre-sprouting potato eyes,representing eyes about to sprout and eyes that will take a while to sprout.Features used for classification were extracted by two methods,including successive projections algorithm(SPA)and a newly-developed sine fit algorithm(SFA).Then classifiers of fisher discriminant analysis(FDA)and least square support vector machine(LSSVM)were utilized for classification of potential sprouting potato eyes.Results showed that FDA was more effective than LSSVM in classifying pre-sprouting and by-sprouting potato eyes,and SFA performed well in FDA classifier with the recognition accuracy of 95.3%for prediction set.It is concluded that hyperspectral imaging has the potential for predicting the sprouting stages of potato eyes.
关 键 词:potato tuber potato eyes sprouting stage hyperspectral imaging sine fit algorithm(SFA) quality and safety prediction
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