Classification of the firmness of peaches by sensor fusion

作     者：Kubilay Kazim Vursavus Yesim Benal Yurtlu Belen Diezma-Iglesias Lourdes Lleo-Garcia Margarita Ruiz-Altisent 

作者机构：Department of Agricultural Machinery and Technologies EngineeringFaculty of AgricultureÇukurova University01330 AdanaTurkey Department of Agricultural Machinery and Technologies EngineeringFaculty of AgricultureOndokus Mayıs UniversitySamsunTurkey LPF-TagraliaDepartment of Agricultural EngineeringTechnical Polytechnic University of MadridAvda.Computense s/n28040 MadridSpain 

出 版 物：《International Journal of Agricultural and Biological Engineering》 (国际农业与生物工程学报（英文）)

年 卷 期：2015年第8卷第6期

页      面：104-115,I0002页

核心收录：

学科分类：0710[理学-生物学] 0810[工学-信息与通信工程] 08[工学] 0805[工学-材料科学与工程（可授工学、理学学位）] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 081102[工学-检测技术与自动化装置] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：We express our appreciation to the head of department of Madrid Polytechnic University Physical Properties Laboratory(Technical University of Madrid LPF-TAGRALIA)for support to this study The authors Kubilay Kazim VURSAVUS and Yesim Benal YURTLU were also supported by a grant from The Council of Higher Education of Turkish Government for the present study 

主　　题：peach firmness classification nondestructive sensor high level fusion Bayesian classifier 

摘      要：The objectives of this research were to compare the performance of each individual nondestructive sensor with the destructive sensor,and to apply sensor fusion technique to explore whether a combination of sensors would give better results than a single sensor for classification of peach *** were carried out with four peach varieties namely Royal Glory,Caterina,Tirrenia and *** this research,the three nondestructive firmness sensors acoustic firmness,low-mass impact and micro-deformation impact were used to measure firmness.A Bayesian classifier was chosen to provide a classification into three categories,namely soft,intermediate and *** level fusion technique was performed by using identity declaration provided by each *** data fusion system processed the information of the sensors to output the fused *** result of the high level fusion was compared with the classification provided by an unsupervised algorithm based on destructive reference *** fusion process of the nondestructive sensors provided some improvements in the firmness classification;the error rate varied from 25%to 19%for individual ***,the results of fusion process by using three sensors decreased the error rate from 19%to 13%.This research demonstrated that the fused systems provided more complete and complementary information and,thus,were more effective than individual sensors in the firmness classification of peaches.