基于近红外的奶粉品质检测技术研究

Study on Quality Detection of Milk Powder Based on Near Infrared Spectroscopy(NIR)

奶粉种类繁多且检测的理化指标较多,为了进一步简化近红外光谱检测技术在奶粉生产过程中的应用步骤,文章首次提出了建立包含不同种类奶粉样品集的6个指标:酸度、脂肪、乳糖、蔗糖、蛋白和灰分的近红外模型,用于奶粉质量控制。该文采用全谱分析结合模型优化方法研究,分别建立了该混合奶粉样品集的6个指标的近红外模型。实验表明:除酸度外,该研究所建立混合奶粉的其他理化指标的近红外定标模型具有较好的稳定性和预测能力(RSD<10%,RPD>3)。因此该方法的提出可以简化近红外技术在奶粉定量分析中的步骤。

The traditional NIR model was usually built according to various parameters of an individual type of milk powder so that it＇s really time-consuming.To simplify the application of NIR in real-time quality detection of milk powder,it was proposed in the present paper to build NIR models for a sample set composed of different types of milk powder.With 70 samples provided by one manufacturer,6 NIR models including acidity,fat,lactose,sucrose,protein and ash,were built by optimizing algorithms.The results indicated that these NIR models except the acidity model have good stability and high prediction ability（RSD〈10%,RPD〉3）.