红心李总可溶性固形物含量的电子鼻预测方法研究  

Study of Red-heart Plum Total Soluble Solids Content Predicting Method Using Electronic Nose

作　　者：李剑[1] 郑乐[1] 林涵[1] 郑飞翔[1] 惠国华[1] 

机构地区：[1]浙江农林大学信息工程学院/浙江省林业智能监测与信息技术研究重点实验室,浙江临安311300

出　　处：《核农学报》2015年第12期2360-2365,共6页Journal of Nuclear Agricultural Sciences

基　　金：浙江省自然科学基金(LQ14F020014);浙江农林大学人才发展基金(2015FR020;2012FK028)

摘　　要：为实现红心李品质的无损检测,采用国标法检测红心李样品的可溶性固形物含量,测定并记录电子鼻响应值,采用非线性随机共振提取电子鼻信噪比特征值,构建红心李总可溶性固形物含量非线性Boltzmann预测模型。结果表明,构建的红心李可溶性固形物含量预测模型的相关系数R2=0.9700,表明电子鼻可以预测红心李可溶性固形物含量。验证可知,该模型的预测精度较高,对所有测试样品的预测值皆较准确。本研究为果蔬品质电子鼻快速无损检测提供了理论参考。In this paper,cold-stored red-heart plum（ P. Salicina Lindl.） total soluble solids（ TSS） predicting method using electronic nose（ e-nose） was studied in order to realize quality non-destructive analysis. TSS contents of plum samples from the same batch were examined according to the Chinese national standard method. E-nose responses were also measured. Non-linear stochastic resonance（ SR） was used to extract e-nose signal-to-noise ratio（ SNR） eigen values for red-heart plum TSS content non-linear Boltzmann predicting model development. Results demonstrated that the red-heart plum TSS content predicting model of correlation coefficent R2= 0. 9700,indicated that e-nose successfully predicted the TSS content of the plums. This model presented high forecasting accuracy and gave accurate predictions for tested samples. The proposed method presented some advantages,such as rapid response,high accuracy,and low cost,etc. This work provided theoritical reference for fruits and vegetables quality e-nose rapid and non-destructive analysis.

关 键 词：红心李 总可溶性固形物含量预测 电子鼻 随机共振 信噪比 

分 类 号：S662.3[农业科学—果树学]