Non-destructive detection of the fruit firmness of Korla fragrant pear based on electrical properties  

作　　者：Hong Zhang Yang Liu Yurong Tang Haipeng Lan Hao Niu Hong Zhang 

机构地区：[1]Modern Agricultural Engineering Key Laboratory at Universities of Education Department of Xinjiang Uygur Autonomous Region,Tarim University,Alaer 843300,Xinjiang,China [2]College of Water Resources and Architectural Engineering,Tarim University,Alaer 843300,Xinjiang,China [3]College of Mechanical and Electrical Engineering,Tarim University,Alaer 843300,Xinjiang,China

出　　处：《International Journal of Agricultural and Biological Engineering》2022年第6期216-221,共6页国际农业与生物工程学报(英文)

基　　金：supported by the National Natural Science Foundation of China(Grant No.32202139,32260618);the Tarim University President Fund Project(Grant No.TDZKCQ201902,TDZKSS202109);the Innovation Research Team Project of President’s Fund of Tarim University(Grant No.TDZKCX202203);Xinjiang Production&Construction Group Key Laboratory of Agricultural Products Processing in Xinjiang South(Grant No.AP1905);the“Strong Youth”Key Talents of Scientific and Technological Innovation(Grant No.2021CB039)and the authors also acknowledge all of the persons who assisted in this writing.

摘　　要：In order to achieve the non-destructive detection of the firmness of Korla fragrant pear during the ripening period,the characteristic variables integrating the parallel equivalent inductance(Lp),quality factor(Q),parallel equivalent capacitance(Cp),dissipation factor(D),parallel equivalent resistance(Rp)and impedance(Z)were formulated through principal component analysis(PCA).Further,based on the characteristic variables,the models were established for predicting the firmness of Korla fragrant pear by using the generalized regression neural network(GRNN)and back-propagation neural network(BPNN).The results showed that firmness has significant correlations with the six electrical parameters.The first two principal components(PCs)were selected as the characteristic variables of the electrical parameters.GRNN exhibited the best performance in predicting firmness(R2=0.9628,RMSE=0.383).The results could provide important references for non-destructive detection of the quality of Korla fragrant pear.

关 键 词：Korla fragrant pear FIRMNESS electrical properties principal component analysis non-destructive detection 

分 类 号：S661.2[农业科学—果树学]