基于中红外光谱对牛乳中乳铁蛋白含量的快速检测

徐大江; 马占峰; 孙艳; 赵丽娟; 高一娜; 杨青青

doi:10.12377/1671-4393.25.07.19

中国乳业 >

2025 , Vol. 0 >Issue 7: 115 - 120

DOI: https://doi.org/10.12377/1671-4393.25.07.19

质量安全

基于中红外光谱对牛乳中乳铁蛋白含量的快速检测

徐大江 ,
马占峰 ,
孙艳 ,
赵丽娟 ,
高一娜 ,
杨青青

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哈尔滨市产品质量综合检验检测中心,黑龙江哈尔滨 150036

徐大江（1982-）,男,河北邢台人,硕士,高级工程师,研究方向为食品监督检验;孙艳（1971-）,女,山东招远人,硕士,高级工程师,研究方向为食品监督检测;赵丽娟（1978-）,女,山东烟台人,硕士,高级工程师,研究方向为食品监督检验;高一娜（1985-）,女,黑龙江哈尔滨人,硕士,高级农艺师,研究方向为检验检测;杨青青（1982-）,女,黑龙江齐齐哈尔人,硕士,高级工程师,研究方向为食品监督检验。

网络出版日期: 2025-08-04

基金资助

国家市场监督管理总局科技计划项目（2021MK132）

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Study on Lactoferrin in Milk Based on Mid-infrared Spectroscopy Rapid Detection of Content

XU Dajiang ,
MA Zhanfeng ,
SUN Yan ,
ZHAO Lijuan ,
GAO Yina ,
YANG Qingqing

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Harbin Product Quality Comprehensive Inspection and Testing Center,Harbin Heilongjiang 150036

Online published: 2025-08-04

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摘要

[目的]为满足乳制品加工过程中快速、精准定量检测大量样品中乳铁蛋白含量的需求,利用中红外光谱结合化学计量学建立牛乳中乳铁蛋白含量检测校正模型。[方法]以108份牛乳样本为研究对象,使用高效液相色谱法测量其中乳铁蛋白含量,并采集牛乳样本的光谱数据,考察归一化、一阶导数、二阶导数、标准正态变量变换、多元散射校正以及小波变换等预处理方法对乳铁蛋白偏最小二乘算法（PLS）定量模型预测精度的影响。[结果]一阶导数和标准正态变量变换是最优的光谱数据预处理方法;模型校正集决定系数为0.941 7,校正均方根误差为1.142;预测集的预测均方根误差为1.187,具有较好的预测能力。[结论]本研究结果对乳制品生产过程中的品质控制及生产效率优化有重要意义。

关键词： 乳铁蛋白; 中红外光谱; PLS预测模型; 定量分析; 质量监测

本文引用格式

徐大江 , 马占峰 , 孙艳 , 赵丽娟 , 高一娜 , 杨青青 . 基于中红外光谱对牛乳中乳铁蛋白含量的快速检测[J]. 中国乳业, 2025 , 0(7) : 115 -120 . DOI: 10.12377/1671-4393.25.07.19

Abstract

[Objective] To meet the demand for rapid and accurate quantitative determination of lactoferrin content in a large number of samples during dairy processing a detection and correction model for lactoferrin content in milk was established by combining mid-infrared spectroscopy with chemometric. [Method] Taking 108 milk samples as the research objects,the lactoferrin content was measured by high performance liquid chromatography,and the spectral data of the milk samples were collected. To investigate the effects of preprocessing methods such as normalization first derivative second derivative standard normal variable transformation multiple scattering correction and wavelet transform on the prediction accuracy of partial least squares PLS quantitative model lactoferrin. [Result] The first derivative and the standard normal variable transformation were the optimal preprocessing methods for spectral data. The determination coefficient of the model correction set was 0.941 7, and the root mean square error of the correction was 1.142. The root mean square error of prediction was 1.187 which had good prediction ability. [Conclusion] The results of this study are of great significance for quality control and production efficiency optimization in dairy production proces.

Key words： lactoferrin; mid-infrared spectroscopy; PLS prediction model; quantitative analysis; quality monitoring

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