苹果内在组分与隐形缺陷的近红外透射光谱同步在线检测研究
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- 英文论文题名：Simultaneous determination of edible quality and internal defect in apple by NIR transmittance spectroscopy
- 论文作者：郭志明 ; 陈全胜 ; 樊书祥 ; 欧阳琴 ; 赵杰文
- 英文论文作者：Guo Zhiming ; Chen Quansheng ; Fan Shuxiang ; Ouyang qin ; Zhao Jiewen ; School of Food and Biological Engineering ; Jiangsu University ; National Engineering Research Center of Intelligent Equipment for Agriculture
- 年：2016
- 作者机构：江苏大学食品与生物工程学院;国家农业智能装备工程技术研究中心;
- 论文关键词：近红外透射光谱 ; 隐形缺陷 ; 内在组分 ; 同步在线检测 ; 苹果
- 英文论文关键词：NIR transmittance spectroscopy ; internal defect ; edible quality ; simultaneous determination ; apple
- 会议召开时间：2016-11-09
- 会议录名称：中国食品科学技术学会第十三届年会论文摘要集
- 英文会议录名称：Abstracts of the 13th Annual Meeting of CIFST
- 语种：中文
- 分类号：TS255.7;O657.3
- 学会代码：ZGSP
- 会议名称：中国食品科学技术学会第十三届年会
- 会议地点：中国北京
- 主办单位：中国食品科学技术学会
- 学会名称：中国食品科学技术学会
- 页数：1
- 文件大小：58k
- 原文格式：O
- 会议级别：全国
摘要
针对苹果内在组分和隐形缺陷快速检测的产业技术需求,研究基于透射光谱技术的苹果在线检测系统及检测方法。研究首先设计了在线检测软硬件系统,实现苹果内部品质信息的无损在线获取。然后在线采集制备的真菌感染的隐形缺陷苹果的近红外透射光谱,采用线性判别分析建立了不同内部缺陷程度的判别模型,预测的识别率为91%;同样参数采集的完好苹果的近红外透射光谱,在分析光谱响应机理的基础上,利用偏最小二乘法结合光谱预处理建立了苹果可溶性固形物含量的在线检测模型,模型的相关系数为0.95,模型预测均方根误差为0.42。研究结果表明近红外透射光谱同时检测苹果的内在组分和隐形缺陷是可行的,为研发基于透射光谱技术的果蔬自动化检测装备提供了技术支撑和方法参考。
In order to simultaneous nondestructive on-line inspect edible quality and internal defect of apple,this work presents the development of an on-line detection prototype system using near infrared transmittance technology as a novel approach for on-line detect quality attributes without sample destructiveness.In this experiment,internal defects of apple caused by core rot fungi are collected and cultivated,because the natural internal defects apple sample is difficult to collect.We tried the preparation of samples and achieved good performance.It was achieved internal quality information in nondestructive online way by this system.Partial least squares-discriminant analysis(PLS-DA) models were developed to identify internal defects samples.The results obtained from PLS-DA models,in validation,gave a positive predictive value of classification about 91%.Moreover,predictive models were performed applying fast PLS regression algorithm to predict the soluble solid content(SSC)in apple.Very good results were obtained for SSC with R and RPD equal to 0.90 and 3.00,respectively.The results showed that the nondestructive on-line detection prototype based on NIR transmittance technique was feasible to simultaneous inspect the edible quality and internal defect of apple.The present research provides the foundation for the future development of an automatic system based on transmittance spectroscopy which is extremely important from the economic point of view.
In order to simultaneous nondestructive on-line inspect edible quality and internal defect of apple,this work presents the development of an on-line detection prototype system using near infrared transmittance technology as a novel approach for on-line detect quality attributes without sample destructiveness.In this experiment,internal defects of apple caused by core rot fungi are collected and cultivated,because the natural internal defects apple sample is difficult to collect.We tried the preparation of samples and achieved good performance.It was achieved internal quality information in nondestructive online way by this system.Partial least squares-discriminant analysis(PLS-DA) models were developed to identify internal defects samples.The results obtained from PLS-DA models,in validation,gave a positive predictive value of classification about 91%.Moreover,predictive models were performed applying fast PLS regression algorithm to predict the soluble solid content(SSC)in apple.Very good results were obtained for SSC with R and RPD equal to 0.90 and 3.00,respectively.The results showed that the nondestructive on-line detection prototype based on NIR transmittance technique was feasible to simultaneous inspect the edible quality and internal defect of apple.The present research provides the foundation for the future development of an automatic system based on transmittance spectroscopy which is extremely important from the economic point of view.
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