摘要
测量了7个牧场连续7天合格奶样的三维荧光光谱,使用Matlab对三维荧光光谱进行了归一化、平滑滤波和去除散射效应等预处理,然后对处理后的数据矩阵依次进行了奇异值分解,提取其第一主成分作为特征光谱。结果表明:该特征光谱可区分7个牧场来源的合格奶样,且可判断出该牧场合格奶样质量是否稳定。各牧场奶质的稳定性,相关系数、第一第二大奇异值比值与第一主成分特征光谱直观结果一致。
3D fluorescence spectrum of qualified milk from seven firms were measured in seven days and their feature extraction methods were explored. With simple ordering Rayleigh scattering data as zero, tlie obtained 3D spectrum was processed by singular value decomposition. The result showed that the singular value decomposed spectrum could be used as a characteristic spectrum to differentiate the qualified milk from seven farms and analyze its quality stability. For milk quality stability of seven farms, correlation coefficient, singular value decomposition and character spectrum share the same result.
出处
《中国乳品工业》
CAS
北大核心
2009年第7期13-15,19,共4页
China Dairy Industry
关键词
牛奶
三维荧光光谱
奇异值分解
相关系数
milk
3D spectrum
Singular Value Decomposition （SVD）
correlation coefficient
