应用近红外光谱快速测定单粒糙米水分含量

J4 ›› 2018, Vol. 35 ›› Issue (2): 136-141.

应用近红外光谱快速测定单粒糙米水分含量

王纯阳¹,马玉涵¹,范爽¹,黄青²

1 中国科学院合肥物质科学研究院技术生物与农业工程研究所，安徽合肥230031； 2 中国科学技术大学生命科学学院，安徽合肥230026

收稿日期:2017-05-17 修回日期:2017-05-25 出版日期:2018-03-28 发布日期:2018-03-30
通讯作者: 黄青（1968-）研究员，博士，博士生导师，主要从事生物物理与物理化学、生物光谱、核技术生物应用等方面的研究。E-mail：huangq@ipp.ac.cn
作者简介:王纯阳（1991-）安徽人，研究生，主要从事生物物理-生物光谱学方面的研究。E-mail：wcy68@mail.ustc.edu.cn
基金资助:
Supported by National Natural Science Foundation of China(国家自然科学基金, 11475217 , 11635013), Strategic Priority Research Program of Chinese Academy of Sciences(中国科学院战略先导项目, XDA08040107)

Rapid determination of single brown-rice kernels moisture content using near-infrared spectroscopy

1 Institute of Technical Biology and Agriculture Engineering, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China; 2 School of Life Sciences, University of Science and Technology of China, Hefei 230026, China

Received:2017-05-17 Revised:2017-05-25 Published:2018-03-28 Online:2018-03-30

摘要/Abstract

摘要： 建立单粒糙米水分含量的近红外漫反射光谱（NIRS）模型，并结合不同的预处理及变量选择方法对其进行优化。结果表明在5292～5616 cm-1 、7236～7600 cm-1、7884～8208 cm-1波数范围，用标准正态变化光谱预处理建立的单粒糙米水分含量偏最小二乘（PLS）模型的预测能力最佳，其决定系数为0.98，预测误差均方根为1.01%；选择5492.56、7158.84、8285.12 cm-1这三个波数变量建立的单粒糙米含水量多元线性回归（MLR）模型变量最少且预测能力较优，其决定系数为0.9661，预测误差均方根为1.137%。结果表明应用近红外光谱技术能快速、准确地测定单粒糙米水分含量。

关键词: 近红外光谱；水分；定量模型；单粒糙米；漫反射

Abstract: A near infrared spectroscopy (NIRS) model of single brown-rice kernels moisture content is established and optimized by applying different preprocessing treatments and variables selection methods. Results show that in the following three ranges, from 5292 cm-1 to 5616 cm-1, 7236 cm-1 to 7600 cm-1, 7884 cm-1 to 8208 cm-1, the predictive ability of single brown-rice kernels moisture content partial least squares (PLS) model established by standard normal variation spectral pretreatment is optimal. Its determination coefficient (R2) is 0.98 and prediction root mean square error is 1.01%. The multivariate linear regression model(MLR) of single brown-rice kernels moisture content at 5492.56, 7158.84, 8285.12 cm-1 has the least variables and better prediction ability, whose determination coefficient is 0.9661 and prediction root mean square error is 1.1137%. Results show that near infrared spectroscopy can be employed to determine single brown-rice kernels moisture content rapidly and accurately.

Key words: near infrared spectroscopy; moisture; quantitative model; single brown-rice kernels; diffuse reflectance

中图分类号:

O433

王纯阳马玉涵范爽黄青. 应用近红外光谱快速测定单粒糙米水分含量[J]. J4, 2018, 35(2): 136-141.

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