近红外光谱快速检测婴幼儿配方乳粉中主要成分的方法研究

Study of the rapid detection method of near-infrared spectroscopy of main components in infant formula

目的研究利用近红外光谱技术快速检测婴幼儿配方乳粉中主要成分的方法。方法收集12个品牌的婴幼儿配方乳粉共100份样品,采集10 000~4 000 cm-1波数范围内的近红外光谱,采用主成分回归和偏最小二乘法建立校正模型,并对比光谱预处理方法对模型的影响。结果采用偏最小二乘法建模,光谱采用标准正态变量变换预处理,模型预测效果最佳,主要成分蛋白质、脂肪、膳食纤维、水分、灰分、可获得碳水化合物和能量的预测方差分别为98.44%、97.40%、96.18%、96.74%、96.97%、96.55%和95.35%,估计标准误差分别为0.354 2、0.473 8、0.201 4、0.105 8、0.093 61、0.520 7和13.64。对模型进行外部验证,将预测样品的7项主要成分的预测结果与实验室检测结果进行比较,相对误差及相对偏差均在5.00%以下,7项主要成分符合国家标准的精密度的要求。结论本方法能快速有效的测定婴幼儿配方乳粉中蛋白质、脂肪、膳食纤维、水分、灰分、可获得碳水化合物的质量分数及能量的含量。

Objective The method of rapid detection of main ingredients in infant formula milk powder was studied by near infrared spectroscopy. Methods A total of 100 samples of 12 brands of infant formula were collected,and10 000-4 000 cm-1 band of near-infrared spectra were collected. The calibration model was established by principal component regression and partial least square method. Results The model predicted the best result by partial least-squares method and standard normal variable transformation pretreatment. The predicted variances of main ingredients,protein,fat,dietary fiber,moisture,ash,carbohydrate and energy were 98. 44%,97. 40%,96. 18%,96. 74%,96. 97%,96. 55% and 95. 35%,and the estimated standard error were 0. 354 2,0. 473 8,0. 201 4,0. 105 8,0. 093 61,0. 520 7 and 13. 64. For external validation of the model,the predictive value of 7 main ingredients of the predicted sample was compared with that of the laboratory test result. Comparison result of relative error and relative deviation were below5. 00%. The result of seven main ingredients met the precision requirements of national standards. Conclusion The method could be used to determine the quantity fraction and quantity of protein,fat,dietary fiber,moisture,ash,carbohydrate and energy in infant formula and the quality.