Detection of moldy core in apples and its symptom types using transmittance spectroscopy

作     者：Zhou Zhaoyong Lei Yu Su Dong Zhang Haihui He Dongjian Chenghai Yang 

作者机构：College of Mechanical and Electronic EngineeringNorthwest A&F UniversityYangling 712100China Network&Education Technology CenterNorthwest A&F UniversityYangling 712100China U.S.Department of AgricultureAgricultural Research ServiceCollege Station 77845TXUSA 

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：2016年第9卷第6期

页      面：148-155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）] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National High-tech Research and Development Projects(863)(2013AA10230402) National Natural Science Foundation of China(61473235) the Major Pilot Projects of the Agro-Tech Extension and Service in Shaanxi(2016XXPT-05) 

主　　题：moldy core of apples transmittance spectrum wavelet transform support vector machine genetic algorithm symptom types 

摘      要：A detection method based on transmittance spectroscopy and support vector machine(SVM)was proposed to achieve rapid nondestructive detection of moldy core in apples.A visible to near-infrared(Vis/NIR)spectroradiometer was used for scanning transmittance spectra of 215 apple samples in the wavelength range of 200-1025 *** transform was used to reduce the dimensionality of the spectra and extract wavelet *** classification algorithms including artificial neural network(ANN)and SVM were used to develop models whose parameters were optimized by genetic algorithms(GA)for determination of the presence and types of moldy core in *** results of the models showed that the GA-SVM model obtained the optimal result with an accuracy of 96.92%for detecting the presence of moldy core and 81.48%for distinguishing symptom types of the *** results indicate that it is feasible to detect moldy core in apples nondestructively and rapidly based on transmittance spectroscopy and that wavelet transform is an effective method for extraction of characteristics from ***,the GA-SVM algorithm in conjunction with Vis/NIR transmittance spectroscopy can accurately achieve fast and nondestructive detection of the presence and types of moldy core in apples.