| 一种用于预测蚕丝含量占比的近红外光谱分析方法 |
| 投稿时间：2020-08-19 修订日期：2020-09-05 点此下载全文 |
| 引用本文：范雅婷,刘胜.一种用于预测蚕丝含量占比的近红外光谱分析方法[J].红外,2021,42(1):43~48 |
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| 基金项目:国家自然科学基金项目（61571002; 61179034） |
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| 中文摘要:针对近红外光谱分析技术中未充分利用预测模型光谱数据的问题，提出了一种可充分利用光谱数据和有效预测蚕丝含量占比的新方法。以5种类型共145个样本的蚕丝含量占比以及相应的所有蛋白质基光谱数据为研究对象，将这些样本分别划分为校正集和验证集，并采用偏最小二乘回归（Partial Least Squares Regression, PLSR）方法和提出的偏最小二乘回归多模型（multi-model Partial Least Squares Regression， multi-PLSR）方法建立了预测模型。然后对比和观察了两种方法的预测效果。以类型2的蚕丝样本为例，选用13个主成分并对比两种模型后发现，multi-PLSR模型的相关系数由0.594增至0.9784，平均相对误差由0.4866降至0.1384。实验结果表明，新方法充分利用了光谱数据中的信息，提高了蚕丝含量占比预测模型的精度，为建立近红外光谱预测模型提供了一种新思路。 |
| 中文关键词:近红外光谱 蚕丝含量 多模型 偏最小二乘回归 |
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| A Near Infrared Spectroscopy Method for Predicting the Percentage of Silk Content |
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| Abstract:Aiming at the problem that the spectral data of prediction model are not fully utilized in near infrared spectroscopy, a new method which can make full use of spectral data and effectively predict the proportion of silk content is proposed. The proportion of silk content in 145 samples of 5 types and the corresponding spectral data of all protein bases are taken as the research objects. The samples are divided into calibration and verification sets respectively. The partial least squares regression method and the partial least squares regression multi-model method are respectively used to establish the prediction model, and the prediction effects of the two methods are compared and observed. Taking the silk samples of type 2 as an example, 13 principal components are selected and the two models are compared. It is found that the correlation coefficient of multi-PLSR increases from 0.594 to 0.9784, and the average relative error decreases from 0.4866 to 0.1384. The experimental results show that the new method makes full use of the information in the spectral data and improves the accuracy of the prediction model of silk content proportion, which provides a new thought for the establishment of the near infrared spectrum prediction model. |
| keywords:near infrared spectrum silk content multiple model partial least squares regression |
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