饲料中肉骨粉含量的近红外反射光谱检测方法

Prediction of meat and bone meal content in feed by near infrared reflectance spectroscopy

收集28份鸡饲料,31份猪饲料,25份牛饲料和肉骨粉7份,在饲料中掺入不同比例(0.5%～6.0%)的肉骨粉,制成分析样本。采用偏最小二乘(PLS)法,分别对光谱进行散射校正、平滑、一阶导数和二阶导数预处理,建立了鸡饲料、猪饲料和牛饲料中肉骨粉含量的近红外定量分析模型。利用验证集样本对定标模型进行了检验,鸡饲料、猪饲料和牛饲料中肉骨粉含量的真值与预测值之间的决定系数分别为0.9694、0.9846和0.9788;标准差分别为0.279、0.252和0.287;相对分析误差分别为5.663、6.865和5.889。结果表明,利用近红外光谱法测定饲料中的肉骨粉含量具有较高的预测精度。

Twenty-eight feed samples for chicken, 31 feed samples for swine, 25 feed samples for cattle and 7 meat and bone meal（MBM） samples were collected, and MBM was deliberately adulterated with feed at 0.5%-6.0% by weight, and analysis samples were prepared. The initial spectrum was pretreated by scatter correcting, smoothing, first derivative and second derivative, respectively. The NIRS calibration models of the prediction meat and bone meal content in feed for chicken, swine and cattle were developed using the partial least squares（PLS） regression technique. The calibration model was proved in its precinct by validation set samples. The coefficients of determination in calibration sets （R^2） are 0.9694, 0.9846 and 0.9788; the standard errors （RMSEC） are 0.279, 0.252 and 0.287; the relative percent differences （RPDs） are 5.663, 6.865 and 5.889 for chicken, swine and cattle feed, respectively. The results show that the NIRS can accurately and quantitatively measure the MBM content in feed. Key words：