摘要
收集了一年内不同月份不同种类的纯奶牛精补料20个,制备土霉素含量不同的掺假奶牛精补料100个,在全光谱范围内对样品进行近红外透反射光谱扫描,利用CARS法对光谱数据进行前处理,采用偏最小二乘-线性判别分析(PLS-LDA)法来建立判别模型。建立的PLS-LDA模型的交互验证最小错误率为0.0729,模型错分率为0,模型预测错误率为0.0417。说明利用近红外光谱技术建立定性判别模型来检测奶牛饲料中是否掺有土霉素是可行的。
In this paper, 20 pure dairy concentrate supplements were collected within one year months and different pared. Scan samples types, and 100 oxytetracycline adulteration samples with different with the near-infrared transmission and reflection spectra in the full contents spectral in different were pre- range, use Competitive Adaptive Reweighted Sampling （CARS） to pretreat spectroscopic data and build the diseriminant models with Partial Least Squares-Linear Discriminant Analysis （PLS-LDA）. The minimum error rate of cross validation for the established PLS-LDA model was 0. 0729 ; model misclassification rate 0, and the model pre- diction error rate 0. 0417. It is feasible to establish qualitative analysis models to detect whether mixed with oxytetracycline in dairy feed by near infrared spectroscopy.
出处
《包装与食品机械》
CAS
2012年第4期1-4,共4页
Packaging and Food Machinery
基金
"十一五"国家科技支撑计划项目(2009BADB7B07)
中南大学学位论文创新资助项目(2010ssxt256)
关键词
奶牛饲料
土霉素
竞争性自适应重加权采样法
偏最小二乘-线性判别分析法
dairy feed
oxytetracycline
Competitive Adaptive Reweighted Sampling （ CARS ）
PartialLeast Squares Linear Discriminant Analysis（ PLS -LDA）
作者简介
刘星（1986-），女，硕士，研究方向为食品分析与测试，通信地址：410125湖南长沙市岳麓区麓山南路932号中南大学隆平分院，E-mail：liuxinglyg@126．com。
