Temperature correction of near-infrared spectra of raw milk

IF 3.7 2区 化学 Q2 AUTOMATION & CONTROL SYSTEMS
Jose A. Diaz-Olivares , Stef Grauwels , Xinyue Fu , Ines Adriaens , Wouter Saeys , Ryad Bendoula , Jean-Michel Roger , Ben Aernouts
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引用次数: 0

Abstract

Accurate milk composition analysis is crucial for improving product quality, economic efficiency, and animal health in the dairy industry. Near-infrared (NIR) spectroscopy can quantify milk composition quickly and nondestructively. However, external factors, such as temperature fluctuations, can alter the molecular vibrations and hydrogen bonding in milk, altering the NIR spectra and leading to errors in predicting key constituents such as fat, protein, and lactose. This study compares the effectiveness of Piecewise Direct Standardization (PDS), Continuous PDS (CPDS), External Parameter Orthogonalization (EPO), and Dynamic Orthogonal Projection (DOP in correcting the impact of temperature-induced variations on predictions in milk long-wave NIR spectra (LW-NIR, 1000–1700 nm).
A total of 270 raw milk samples were analyzed, collecting both reflectance and transmittance spectra at five different temperatures (20 °C, 25 °C, 30 °C, 35 °C, and 40 °C). The experimental setup ensured precise temperature control and accurate spectral measurements. PLSR models were calibrated at 30 °C to predict milk fat, protein, and lactose content. The performance of these models was assessed before and after applying the temperature correction methods, with a primary focus on reflectance spectra.
Results indicate that EPO and DOP significantly enhance model robustness and prediction accuracy across all temperatures, outperforming PDS and CPDS, especially for lactose prediction. These orthogonalization methods were compared against PLSR models calibrated with spectra from all temperatures. EPO and DOP showed comparable or superior performance, highlighting their effectiveness without requiring extensive temperature-specific calibration data. These findings suggest that orthogonalization methods are particularly suitable for in-line milk quality measurements under farm conditions where temperature control is challenging. This study highlights the potential of advanced chemometric techniques to improve real-time, on-farm milk composition analysis, facilitating better farm management and enhanced dairy product quality.
生乳近红外光谱的温度校正
准确的牛奶成分分析对于提高乳制品行业的产品质量、经济效益和动物健康至关重要。近红外(NIR)光谱可快速、无损地量化牛奶成分。然而,温度波动等外部因素会改变牛奶中的分子振动和氢键,从而改变近红外光谱,导致对脂肪、蛋白质和乳糖等主要成分的预测出现误差。本研究比较了分片直接标准化(PDS)、连续 PDS(CPDS)、外部参数正交化(EPO)和动态正交投影(DOP)在校正温度引起的变化对牛奶长波近红外光谱(LW-NIR,1000-1700 nm)预测的影响方面的有效性。共分析了 270 个原奶样品,收集了五个不同温度(20 °C、25 °C、30 °C、35 °C和 40 °C)下的反射和透射光谱。实验装置确保了精确的温度控制和准确的光谱测量。在 30 °C 时校准 PLSR 模型,以预测牛奶中的脂肪、蛋白质和乳糖含量。结果表明,EPO 和 DOP 显著提高了模型在所有温度下的稳健性和预测准确性,其性能优于 PDS 和 CPDS,尤其是在乳糖预测方面。这些正交化方法与使用所有温度光谱校准的 PLSR 模型进行了比较。EPO 和 DOP 的性能相当或更优,这表明它们无需大量特定温度的校准数据即可发挥功效。这些研究结果表明,正交化方法特别适用于温度控制难度较大的牧场条件下的在线牛奶质量测量。这项研究凸显了先进的化学计量学技术在改善实时牧场牛奶成分分析方面的潜力,有助于改善牧场管理和提高乳制品质量。
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来源期刊
CiteScore
7.50
自引率
7.70%
发文量
169
审稿时长
3.4 months
期刊介绍: Chemometrics and Intelligent Laboratory Systems publishes original research papers, short communications, reviews, tutorials and Original Software Publications reporting on development of novel statistical, mathematical, or computer techniques in Chemistry and related disciplines. Chemometrics is the chemical discipline that uses mathematical and statistical methods to design or select optimal procedures and experiments, and to provide maximum chemical information by analysing chemical data. The journal deals with the following topics: 1) Development of new statistical, mathematical and chemometrical methods for Chemistry and related fields (Environmental Chemistry, Biochemistry, Toxicology, System Biology, -Omics, etc.) 2) Novel applications of chemometrics to all branches of Chemistry and related fields (typical domains of interest are: process data analysis, experimental design, data mining, signal processing, supervised modelling, decision making, robust statistics, mixture analysis, multivariate calibration etc.) Routine applications of established chemometrical techniques will not be considered. 3) Development of new software that provides novel tools or truly advances the use of chemometrical methods. 4) Well characterized data sets to test performance for the new methods and software. The journal complies with International Committee of Medical Journal Editors'' Uniform requirements for manuscripts.
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