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用于农场原奶成分分析的微机电系统近红外光谱仪评估

Evaluation of MEMS NIR Spectrometers for On-Farm Analysis of Raw Milk Composition.

作者信息

Uusitalo Sanna, Diaz-Olivares José, Sumen Juha, Hietala Eero, Adriaens Ines, Saeys Wouter, Utriainen Mikko, Frondelius Lilli, Pastell Matti, Aernouts Ben

机构信息

Optical Measurements, VTT Technical Research Centre of Finland, 90570 Oulu, Finland.

Animal and Human Health Engineering, Department of Biosystems, KU Leuven, 2440 Geel, Belgium.

出版信息

Foods. 2021 Nov 3;10(11):2686. doi: 10.3390/foods10112686.

Abstract

Today, measurement of raw milk quality and composition relies on Fourier transform infrared spectroscopy to monitor and improve dairy production and cow health. However, these laboratory analyzers are bulky, expensive and can only be used by experts. Moreover, the sample logistics and data transfer delay the information on product quality, and the measures taken to optimize the care and feeding of the cattle render them less suitable for real-time monitoring. An on-farm spectrometer with compact size and affordable cost could bring a solution for this discrepancy. This paper evaluates the performance of microelectromechanical system (MEMS)-based near-infrared (NIR) spectrometers as on-farm milk analyzers. These spectrometers use Fabry-Pérot interferometers for wavelength tuning, giving them the advantage of very compact size and affordable price. This study discusses the ability of MEMS spectrometers to reach the accuracy limits set by the International Committee for Animal Recording (ICAR) for at-line analyzers of the milk content regarding fat, protein and lactose. According to the achieved results, the transmission measurements with the NIRONE 2.5 spectrometer perform best, with an acceptable root mean squared error of prediction (RMSEP = 0.21% /) for the measurement of milk fat and excellent performance (RMSEP ≤ 0.11% /) for protein and lactose. In addition, the transmission measurements using the NIRONE 2.0 module give similar results for fat and lactose (RMSEP of 0.21 and 0.10% / respectively), while the prediction of protein is slightly deteriorated (RMSEP = 0.15% /). These results show that the MEMS spectrometers can reach sufficient prediction accuracy compared to ICAR standard values for at-line and in-line fat, protein and lactose prediction.

摘要

如今,原奶质量和成分的检测依赖于傅里叶变换红外光谱技术,以监测和改善乳制品生产及奶牛健康状况。然而,这些实验室分析仪体积庞大、价格昂贵,且只能由专业人员使用。此外,样品物流和数据传输会延迟产品质量信息,而为优化奶牛护理和饲养所采取的措施也使这些分析仪不太适合实时监测。一款尺寸紧凑且成本低廉的农场用光谱仪或许能解决这一矛盾。本文评估了基于微机电系统(MEMS)的近红外(NIR)光谱仪作为农场牛奶分析仪的性能。这些光谱仪使用法布里 - 珀罗干涉仪进行波长调谐,具有体积非常紧凑和价格低廉的优势。本研究探讨了MEMS光谱仪达到国际动物记录委员会(ICAR)为牛奶脂肪、蛋白质和乳糖在线分析仪设定的精度极限的能力。根据所得结果,使用NIRONE 2.5光谱仪进行的透射测量表现最佳,牛奶脂肪测量的预测均方根误差(RMSEP = 0.21% /)可接受,蛋白质和乳糖测量表现优异(RMSEP≤0.11% /)。此外,使用NIRONE 2.0模块进行的透射测量对脂肪和乳糖给出了类似结果(RMSEP分别为0.21和0.10% /),而蛋白质预测略有下降(RMSEP = 0.15% /)。这些结果表明,与ICAR在线和在线脂肪、蛋白质和乳糖预测的标准值相比,MEMS光谱仪能够达到足够的预测精度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1ea2/8621007/1d51c430a19f/foods-10-02686-g001.jpg

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