近红外光谱结合极限学习机的榛子蛋白质含量检测  

Determination of Hazelnut Protein Content by Near Infrared Spectroscopy Combined with Limit Learning Machine

作　　者：张冬妍[1] 周宝龙 张瑞[1] 韩睿 赵思琦 ZHANG Dong-yan;ZHOU Bao-long;ZHANG Rui;HAN Rui;ZHAO Si-qi(Northeast Forestry University,Harbin 150040,Heilongjiang,China)

机构地区：[1]东北林业大学,黑龙江哈尔滨150040

出　　处：《食品研究与开发》2021年第4期175-179,共5页Food Research and Development

摘　　要：以毛榛与平榛作为研究对象,将去壳后的毛榛与平榛分别制成90组与60组试验样本,获取波长范围为900 nm~1700 nm的原始光,同时,通过凯氏定氮法测得其中蛋白质含量真实值,并通过对比研究一阶(1-der)导数、二阶(2-der)导数、多元散射校正(multiplicative scatter correction,MSC)以及标准变量变换(standard normal variate,SNV)等预处理方法对模型精度的影响,确定适合榛子光谱的预处理方法。并通过反向间隔偏最小二乘法(backward interval partial least squares,BiPLS)分别选出适用于蛋白质预测的特征波段,达到精简模型的效果。以极限学习机(extreme learning machine,ELM)为建模方法建立蛋白质含量预测模型,最终可以得出两种榛子的预测集的相关系数R与预测均方根误差(root mean square error of prediction,RMSEP)分别为0.8806和0.5993,0.8823和0.5984,模型精确度较高。Corylus heterophlla Fisch and Corylus mandshurica Maxim were taken as the research objects.After removing the shell,Corylus heterophlla Fisch and Corylus mandshurica Maxim were made into 90 groups and 60 groups respectively,and the original light with the wavelength range of 900 nm-1700 nm was obtained.At the same time,the true value of protein content in hazelnut was measured by Kjeldahl Nitrogen method.And the influence of pretreatment methods such as 1st derivative(1-der),2nd derivative(2-der),multiplicative scatter correction(MSC)and standard normal variate(SNV)on the model accuracy was compared,and the pretreatment methods suitable for hazelnut spectrum were selected.The feature bands suitable for protein prediction were selected by the method of backward interval partial least squares(BiPLS),which could simplify the model.A prediction model of protein content was established by using the extreme learning machine(ELM).Finally,it could be concluded that the correlation coefficient R and root mean square error of prediction(RMSEP)of the two hazelnuts were 0.8806 and 0.5993,0.8823 and 0.5984 respectively,indicated a high model accuracy.

关 键 词：近红外光谱检测 极限学习机 榛子 蛋白质 

分 类 号：O657.33[理学—分析化学] TS255.7[理学—化学]