基于MATLAB软件的苹果内部品质系统化无损检测

马玉娟; 赵见军; 孟永宏; 邓红; 郭玉蓉

doi:10.13386/j.issn1002-0306.2014.13.004

基于MATLAB软件的苹果内部品质系统化无损检测

陕西师范大学食品工程与营养科学学院

基金项目:

中央高校基本科研业务项目(GK201002018)；陕西省科技统筹计划(2011KTCQ02-03)；农业部项目(CARS-28)资助；

详细信息

作者简介:
马玉娟 (1987-) , 女, 硕士, 研究方向:农产品加工。;

中图分类号: TS255.7
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出版历程
- 收稿日期: 2013-10-28

Systematic non-destructive test of the apple internal quality based on MATLAB software

College of Food Engineering and Nutritional Science, Shaanxi Normal University

摘要

摘要: 研究将近红外设备与MATLAB软件链接,实现苹果糖度及可滴定酸度的近红外光谱扫描、数据处理、模型建立、含量预测及模型评价等在线无损检测水果内部品质的一体化。以市售陕西红富士苹果为材料,通过近红外文件格式转换、近红外光谱预处理、偏最小二乘法(PLS)回归分析、预测模型的建立、结果预测及模型精度检验等工作编写和调试基于MATLAB语言的模块化程序,经主程序调用建立苹果糖度及可滴定酸度的定量预测模型。结果表明:本实验所建预测模型糖度及可滴定酸度预测值和真实值之间的相关系数R分别为0.9528,0.8786;标准校正误差(SEC)分别为0.4788,0.0215;标准预测误差(SEP)分别为0.3170,0.0128;标准偏差(SD)分别为1.4111,0.0390,模型具有较高的预测精度。因此,将近红外设备与MATLAB软件链接,实现苹果糖度及可滴定酸度在线无损检测的一体化具有可行性且模型检测精度较高,对开发水果内部品质评价及在线分级软件具有重要意义。
- MATLAB语言; /
- 近红外; /
- 无损检测;
Abstract: The objective of this study was through linking nearly infrared equipment with MATLAB software to realize online non- destructive testing the fruit internal quality based on integration of infrared light scanning, data processing, prediction model and model evaluation of apple sugar and titratable acidity. Through writing and debugging the MATLAB modularized program of the near infrared spectra pretreatment, partial least squares ( PLS) regression analysis, quantitative prediction model, prediction results and model accuracy test to get the quantitative forecasting and model evaluation of apple sugar and titratable acidity.The results showed that the correlation coefficient ( R) between predicted values and real values, Standard error of correction ( SEC) , Standard error of prediction ( SEP) , and the standard deviation ( SD) of apple sugar ( titratable acidity) builded the prediction models were 0.9528 ( 0.8786) , 0.4788 ( 0.0215) , 0.3170 ( 0.0128) , and 1.4111 ( 0.0390) , respectively.It had been demonstrated that rapid quantitative forecasting the content of apple sugar and titratable acidity using Near Infrared reflectance spectroscopy based on MATLAB 7.1 were feasibility, and the model had a good prediction accuracy.The method of quantitative online non- destructive prediction the content of apple sugar and titratable acidity will have a important significance to develop internal quality automation evaluation software of fruit and classification software.
- MATLAB language; /
- near infrared; /
- nondestructive testing;

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参考文献(23)

[1]	董一威.基于CCD近红外光谱的苹果内部品质检测[D].北京:中国农业大学食品工程与营养科学学院, 2006:1-2.
[2]	Huang H B, Yu H Y, Xu H R, et al.Near infrared spectroscopy for on/in-line monitoring of quality in foods and beverages:A review[J].J Food Eng, 2008, 87 (3) :303-313.
[3]	Sun T, Xu H R, Ying Y B.Progress in Application of Near Infrared Spectroscopy to Nondestructive On-line Detection of Products/Food Quality[J].Spectrosc Spect Anal, 2009, 29 (1) :122-126.
[4]	Ann P, Nico S, Bart M.NicolaI.Temperature compensation for near infrared reflectance measurement of apple fruit soluble solids contents[J].Postharvest Biology and Technology, 2003, 30:233-248.
[5]	Valeroc, Ruiz-altisent M, Cubeddu R, et al.Selection models for the internal quality of fruit, based on time domain laser reflectance spectroscopy[J].Biosystems Engineering, 2004, 88 (3) :313-323.
[6]	W Luo, S Hunmg, H Fu, et al.Preliminary study on the application of near infrared ectroscopy and pattern recognition methods to classify different types of apple sample[J].Food Chemistry, 2011, 128 (2) :555-561.
[7]	Peirs A, Lammertyn J, Nicolar B, el al.Non-destructive quality measurements of apples by means of NIR-spectroscopy[J].Acta Horticulture, 2000, 517:435-440.
[8]	傅霞萍, 应义斌, 刘燕德.苹果糖度近红外光谱检测的初步实验研究[J].中国食品学报, 2005, 2 (5) :103-106.
[9]	SHI B, JI B, TU Z, et al.Determination of Soluble Solids Content in Fuji Apples Based on Near Infrared Spectroscopy and Artificial Neural Networks[J].Italian Journal of Food ScienceRivista Italiana di Scienza Alimentare, 2008, 20 (1) :23.
[10]	叶海华, 吉海彦, 张录达.MATLAB语言在光谱定量分析中的应用[J].化学分析计量, 2002, 11 (3) :39-41.
[11]	刘燕德, 应义斌.基于MATLAB语言的苹果糖度近红外光谱定量分析[J].浙江大学学报, 2004, 38 (10) :1371-1374.
[12]	应义斌, 刘燕德, 傅霞萍.苹果有效酸度的近红外漫反射无损检测[J].农业机械学报, 2004, 35 (6) :124-126.
[13]	褚小立, 袁洪福, 陆婉珍.近红外光谱分析中光谱预处理及波长选择方法进展与应用[J].化学进展, 2004, 16 (4) :528-542.
[14]	吴瑾光.近代傅立叶变换近红外光谱技术及应用 (上卷) [M].北京:科学技术文献出版社, 1994, 12:56-59.
[15]	赵丽丽.果品类内部品质近红外无损检测技术的研究[D].北京:中国农业大学, 2003:42-44.
[16]	梁逸曾, 渝汝勤.化学计量学[M].北京:高等教育出版社, 2003, 5:136-140.
[17]	许国根, 许萍萍.化学化工中的数学方法及MATLAB实现[M].北京:化学工业出版社, 2008, 1.269.
[18]	严衍禄.近红外光谱分析基础与应用[M].北京:中国轻工业出版社, 2005, 1:4.
[19]	Liu Y D, Yg Y B, Fu C X.The application of detection apple sugar and acidity effectively of Near Infrared Diffuse Reflection[J].Spectroscopy and Spectral Analysis, 2005, 25 (11) :1793-1796.
[20]	杜一平, 张玉兰.化学计量学应用[M].北京:化学工业出版社, 2008, 3.159.
[21]	褚小立.化学计量学方法与分子光谱分析技术[M].北京:化学工业出版社, 2011, 4.75-78.
[22]	李桂峰, 赵国建, 王向东, 等.苹果质地品质近红外无损检测和指纹分析[J].农业工程学报, 2008, 24 (6) :169-173.
[23]	刘建学, 李守军.基于Matlab与C++Builder偏最小二乘分析的编程实现[J].江南大学学报, 2006, 5 (1) :33-37.