介电谱无损检测梨内部品质方法研究  

Nondestructive Detection of Internal Qualities for Pears Using Dielectric Spectra

作　　者：郭文川[1] 房丽洁 董金磊[1] 王转卫[1] 

机构地区：[1]西北农林科技大学机械与电子工程学院,陕西杨凌712100

出　　处：《农业机械学报》2015年第9期233-239,共7页Transactions of the Chinese Society for Agricultural Machinery

基　　金：国家自然科学基金资助项目(31171720)

摘　　要：为了探索利用介电谱无损检测采后梨内部品质的潜力，采用同轴探头技术测量了采摘于4个果园的310个“砀山酥”梨在采后8周贮藏期间20～4500MHz间201个频率点下的相对介电常数和介质损耗因数；分别以可溶性固形物含量（SSC）、硬度和含水率作为内部品质指标，基于x-y共生距离的样本划分法确定了校正集样本233个和预测集样本77个。采用连续投影选法（SPA）从全介电谱中分别提取出了15个、14个和15个用于预测SSC、硬度和含水率的特征变量；建立了基于全介电谱和SPA提取的特征变量预测SSC、硬度和含水率的最小二乘支持向量机（LSSVM）、极限学习机和BP神经网络模型。结果指出，基于全介电谱的LSSVM模型具有最好的SSC决定性能和良好的预测能力，其校正集和预测集相关系数分别为0．974和0．931，校正集和预测集均方根误差分别为0．592°Brix和0．868。Brix，剩余预测偏差为2．65；基于SPA的LSSVM模型可粗略预测含水率；但是所有模型对硬度的预测能力很差。研究结果表明，介电谱结合LSSVM可用于无损检测梨的SSC和含水率，但尚难用于检测梨的硬度。To explore the potential of dielectric spectra in predicting internal qualities of pears, the dielectric constants and loss factors were measured by using open-ended coaxial-line probe technology at 201 discrete frequencies from 20 MHz to 4 500 MHz on 310 pears, picked from four different orchards, during 8-week storage. Soluble solids content, firmness, and moisture content were considered as internal qualities. Sample set partitioning based on joint x -y distances was used to subset partitioning, and 233 samples were used in calibration set and 77 samples were used in prediction set. To simply establish model, successive projection algorithm method was applied to extract characteristic variables （CVs） , and 15, 14 and 15 CVs were extracted for soluble solids content, firmness and moisture content, respectively. The modeling methods, such as least square support vector machine （LSSVM）, extreme learning machine （ELM） and back propagation （BP） network were used to establish soluble solids content, firmness and moisture content determination models based on full dielectric spectra and extracted CVs by SPA. The results showed that the LSSVM model based on full dielectric spectra had the best soluble solids content determination performance and good prediction ability, with the correlation coefficient of calibration set of 0. 974 and prediction set of 0. 931, the root-mean-square error of calibration set of 0. 592°Brix and prediction set of 0. 868~Brix, and the highest residual prediction deviation of 2.65. The LSSVM model based on SPA could be used to predict the moisture contentroughly. However, all models had poor prediction ability on firmness. The study indicates that dielectric spectra combined with LSSVM could be used to predict soluble solids content and moisture content of pears, but it is difficult to predict firmness using dielectric spectra. The study provides a method for nondestructive determination of soluble solids content and moisture content of pears.

关 键 词：梨 内部品质 介电特性 无损检测 

分 类 号：S183[农业科学—农业基础科学] TS207.3[轻工技术与工程—食品科学]