基于CWT和GRNN的可见-近红外漫反射光谱检测樱桃糖度的研究

doi:10.7506/spkx1002-6630-200912027

食品科学 ›› 2009, Vol. 30 ›› Issue (12): 140-143.doi: 10.7506/spkx1002-6630-200912027

基于CWT和GRNN的可见-近红外漫反射光谱检测樱桃糖度的研究

郭卫东¹,倪开诚¹,孙旭东²,张长江¹,陈文荣²

1.浙江师范大学化学与生命科学学院 2.江西农业大学工学院

收稿日期:2008-09-16 修回日期:2009-01-05 出版日期:2009-06-15 发布日期:2010-12-29
通讯作者: 郭卫东 E-mail:gwd@zjnu.cn
基金资助:
浙江省重大科技专项(2007C12021)；国家自然科学基金项目(60468002)

Determination of Sugar Content in Cherry Fruit by Visible-Near Infrared Diffuse Reflectance Spectroscopy Based on CWT and GRNN

GUO Wei-dong1，NI Kai-cheng1，SUN Xu-dong2，ZHANG Chang-jiang1，CHEN Wen-rong1

(1. College of Chemistry and Life Science, Zhejiang Normal University, Jinhua 321004, China；
2. College of Engineering, Jiangxi Agricultural University, Nanchang 330045, China)

Received:2008-09-16 Revised:2009-01-05 Online:2009-06-15 Published:2010-12-29
Contact: GUO Wei-dong1， E-mail:gwd@zjnu.cn

摘要/Abstract

摘要：

联合使用连续小波变换(continuous wavelet transform，CWT)和广义回归神经网络(generalized regression neural networks，GRNN)建立用于测定樱桃中糖含量的CWT-GRNN 预测校正模型。利用CWT 提取樱桃样本数据中反映含糖量的关键光谱特征，在CWT 域中选择3 个具有代表性的尺度，并在每个尺度下根据樱桃样本的可见- 近红外光谱的特征将其划分为4 个特征区间，从而构造12 个特征输入到GRNN，GRNN 的光滑因子取为0.0001。CWTGRNN模型对20 个预测样本集中的樱桃含糖量的预测相对误差在2% 以内。结果表明，可见- 近红外光谱技术可以快速、准确和无损地测定樱桃中的含糖量，本研究提出的方法可以用于果蔬产业的品质管理与控制。

关键词: 可见-近红外漫反射光谱, 内部品质指标, 无损检测, 糖度, 樱桃

Abstract:

CWT - GRNN model was constructed to predict sugar content in cherry fruit by combining continuous wavelet transform (CWT) with generalized regression neural networks (GRNN). CWT was used to extract the key features, which were related to the sugar content of cherry. Three scales in the CWT domain were selected to efficiently extract the features of cherry fruit, and four feature spaces were divided according to the features of visible-near infrared (VIS-NIR) diffuse reflectance spectroscopy. Thus a feature vector, which contains twelve parameters, was input to the GRNN and the smooth factor of the GRNN was set as 0.0001. Twenty cherry samples were used to verify the performance of the CWT - GRNN model. Experimental results showed that the relative error of predicted samples was below 2%. CWT - GRNN model could be used to quickly, accurately and non-destructively predict the sugar content in cherry fruit. Also, the proposed method could be applied in control and evaluation in fruit and vegetable industry.

Key words: visible-near infrared diffuse reflectance spectroscopy, internal quality index, nondestructive measurement, sugar content, cherry

中图分类号:

TS207.3

郭卫东1，倪开诚1，孙旭东2，张长江1，陈文荣1. 基于CWT和GRNN的可见-近红外漫反射光谱检测樱桃糖度的研究[J]. 食品科学, 2009, 30(12): 140-143.

GUO Wei-dong1，NI Kai-cheng1，SUN Xu-dong2，ZHANG Chang-jiang1，CHEN Wen-rong1. Determination of Sugar Content in Cherry Fruit by Visible-Near Infrared Diffuse Reflectance Spectroscopy Based on CWT and GRNN[J]. FOOD SCIENCE, 2009, 30(12): 140-143.

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基于CWT和GRNN的可见-近红外漫反射光谱检测樱桃糖度的研究

Determination of Sugar Content in Cherry Fruit by Visible-Near Infrared Diffuse Reflectance Spectroscopy Based on CWT and GRNN

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