首页> 外文期刊>Applied Spectroscopy: Society for Applied Spectroscopy >Development of a New Measurement Unit (MilkSpec-1) for Rapid Determination of Fat, Lactose, and Protein in Raw Milk Using Near-Infrared Transmittance Spectroscopy
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Development of a New Measurement Unit (MilkSpec-1) for Rapid Determination of Fat, Lactose, and Protein in Raw Milk Using Near-Infrared Transmittance Spectroscopy

机译:开发了一种新的测量装置(MilkSpec-1),用于使用近红外透射光谱法快速测定生乳中的脂肪,乳糖和蛋白质

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摘要

A new measurement unit, the MilkSpec-1, has been developed to determine rapidly and nondestructively the content of fat, lactose, and protein in raw milk using near-infrared transmittance spectroscopy. The spectral range over 700 to 1100 nm was used. This unit was designed for general glass test tubes, 12 mm in diameter and 10 mL in volume. Al_(2)O_(3) with a thickness of 2.5 mm was found to be optimum as a reference for acquiring the milk spectrum for this measurement. The NIR transmittance spectra of milk were acquired from raw milk samples without homogenization. The calibration model was developed and predicted by using a partial least-squares (PLS) algorithm. In order to reduce the scattering effect due to fat globules and casein micelles in NIR transmittance spectra, multiplicative scatter correction (MSC) and/or second derivative treatment were performed. MSC treatment proved to be useful for the development of calibration models for fat and protein. This study resulted in low standard errors of prediction (SEP), with 0.06, 0.10, and 0.10% for fat, lactose, and protein, respectively. It is shown that accurate, rapid, and nondestructive determination of milk composition could be successfully performed by using the MilkSpec-1, presenting the potential use of this method for realtime on-line monitoring in a milking process.
机译:已经开发了一种新的测量单位MilkSpec-1,可以使用近红外透射光谱法快速,无损地确定原料奶中脂肪,乳糖和蛋白质的含量。使用了700至1100 nm的光谱范围。该装置设计用于直径为12毫米,体积为10毫升的普通玻璃试管。发现厚度为2.5mm的Al_(2)O_(3)是最佳的,作为获取用于该测量的牛奶光谱的参考。牛奶的NIR透射光谱是从未经均化的原奶样品中获取的。通过使用偏最小二乘(PLS)算法开发并预测了校准模型。为了减少由于脂肪球和酪蛋白胶束在近红外透射光谱中的散射效应,进行了倍增散射校正(MSC)和/或二阶导数处理。事实证明,MSC处理可用于开发脂肪和蛋白质的校准模型。这项研究导致较低的标准预测误差(SEP),脂肪,乳糖和蛋白质的预测误差分别为0.06%,0.10%和0.10%。结果表明,使用MilkSpec-1可以成功,准确,快速且无损地确定牛奶成分,这表明该方法可用于挤奶过程中的实时在线监测。

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