量子电子学报, 2018, 35 (2): 136, 网络出版: 2018-04-23
应用近红外光谱快速测定单粒糙米水份含量
Rapid determination of single brown-rice kernels moisture content using near-infrared spectroscopy
光谱学 近红外光谱 水份 定量模型 单粒糙米 漫反射 spectroscopy near-infrared spectroscopy moisture quantitative model single brown-rice kernels diffuse reflectance
摘要
建立单粒糙米水份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份含量偏最小二乘(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份含量。
Abstract
A near-infrared spectroscopy (NIRS) model of single brown-rice kernels moisture content is established and optimized by applying different preprocessing treatment 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 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.
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份含量[J]. 量子电子学报, 2018, 35(2): 136. WANG Chunyang, MA Yuhan, FAN Shuang, HUANG Qing. Rapid determination of single brown-rice kernels moisture content using near-infrared spectroscopy[J]. Chinese Journal of Quantum Electronics, 2018, 35(2): 136.