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基于近红外与中红外光谱技术的淀粉回生度检测

邹小波 崔雪平 石吉勇 胡雪桃 徐艺伟 薛瑾

农业机械学报2018,Vol.49Issue(3):341-346,6.
农业机械学报2018,Vol.49Issue(3):341-346,6.DOI:10.6041/j.issn.1000-1298.2018.03.042

基于近红外与中红外光谱技术的淀粉回生度检测

Detection of Retrogradation Degree of Starch Based on Near-infrared and Mid-infrared Spectroscopy

邹小波 1崔雪平 1石吉勇 1胡雪桃 1徐艺伟 1薛瑾1

作者信息

  • 1. 江苏大学食品与生物工程学院,镇江212013
  • 折叠

摘要

Abstract

Starch food is easy to retrograde during processing,transportation and storage,and the degree of retrogradation seriously affects the nutritional value and shelf-life of starch food.Soretrogradation degree is really expected to determine rapidly and non-destructively during storage,that is near-infrared and mid-infrared spectroscopy.The near-infrared and mid-infrared spectra of starch in different storage times (0 d,1 d,2 d,3 d,4 d,5 d,10 d,15 d and 20 d) were collected.There was a certain associations between spectra data and chemical reference detected by spectrophotometry,then chemometrics (partial least squares,PLS) were used to establish the prediction model of starch retrogradation with near-infrared,mid-infrared and fusion data,the best one that had higher correlation coefficient and lower error was chosen.The results showed that the backward interval partial least squares (biPLS) prediction model of fusion technology was the best one,the root mean square error of crossvalidation (RMSECV) and root mean square error of prediction (RMSEP) were 6.79% and 9.52%,and the calibration and prediction correlation coefficient were 0.965 5 and O.931 3,respectively.The results indicated that the fusion spectroscopy was superior to any single spectral technique,which could provide more accurately information of starch.Hence,the infrared spectroscopy could detect the retrogradation degree of corn starch rapidly and non-destructively,provide guidance for the processing of starchy food,and ensure the quality and safety of starchy food.

关键词

淀粉回生度/近红外光谱/中红外光谱/偏最小二乘法

Key words

starch retrogradation degree/near-infrared spectroscopy/mid-infrared spectroscopy/partial least squares

分类

化学化工

引用本文复制引用

邹小波,崔雪平,石吉勇,胡雪桃,徐艺伟,薛瑾..基于近红外与中红外光谱技术的淀粉回生度检测[J].农业机械学报,2018,49(3):341-346,6.

基金项目

“十二五”国家科技支撑计划项目(2015BAD17B04) (2015BAD17B04)

农业机械学报

OA北大核心CSCDCSTPCD

1000-1298

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