基于近红外光谱技术的紫薯贮藏期间花青素含量检测  

Detection of Anthocyanin Content of Purple Sweet Potato during Storage Period Based on Near Infrared Spectroscopy

作　　者：田潇瑜[1] 黄星奕[1] 白竣文[1] 吕日琴[1] 孙兆燕 TIAN Xiaoyu;HUANG Xingyi;BAI Junwen;LU Riqin;SUN Zhaoyan(School of Food and Biological Engineering,Jiangsu University,Zhenjiang 212013,China)

机构地区：[1]江苏大学食品与生物工程学院,镇江212013

出　　处：《农业机械学报》2019年第2期350-355,共6页Transactions of the Chinese Society for Agricultural Machinery

基　　金：国家重点研发计划项目(2016YFD0401302);江苏省博士后科研计划项目(1501068C)

摘　　要：紫薯采后贮藏过程中,受环境因素影响,紫薯花青素会逐渐发生降解,导致紫薯色泽变化,营养品质下降。应用近红外光谱技术对贮藏期间的紫薯花青素含量变化进行了分析,建立了快速无损检测模型。实验采集了不同贮藏时间紫薯样本(120个)的近红外光谱,基于全波长范围4 000～10 000 cm-1结合不同光谱信号预处理方法(数据卷积平滑、一阶求导、标准正态变量变换(SNV))建立紫薯花青素的PLS(偏最小二乘)、SNV-PLS、i PLS(区间偏最小二乘)、GA-PLS(遗传算法-偏最小二乘)定量预测模型。结果显示,全波段经SNV为最优的原始光谱预处理方法。对经SNV预处理的光谱进行i PLS、GA特征波段筛选,所建立的GA-PLS模型预测效果最佳,预测集决定系数R2v和均方根误差为0. 913 6和7. 239 8 mg/(100 g),剩余预测偏差为3. 339 7。研究结果表明,应用近红外光谱技术可以较好地检测紫薯花青素含量,研究结果可为紫薯加工原料智能筛选以及贮藏品质监测提供一种可靠手段。Anthocyanin in purple sweet potato is easy to degrade due to environmental factors during the storage,resulting in changes of purple sweet potato color and reduction of nutritional quality.The changes of anthocyanin in purple sweet potato during storage were analyzed by using near-infrared spectroscopy,and rapid and nondestructive testing model was established.The near-infrared spectra of 120 purple sweet potato samples were collected at different storage times(0 d,2 d,4 d,6 d,8 d,10 d,12 d,14 d,16 d,18 d,22 d and 30 d).In the spectral region between 4 000 cm^-1 and 10 000 cm^-1,statistical mathematical models of anthocyanins in purple sweet potato were established with different preprocessing methods(Savitzky Golay,first derivation and standard normal variate)using the partial least squares(PLS,SNV PLS,iPLS and GA PLS)methods.The results showed that standard normal variate(SNV)transformation was the best preprocessing approach.The iPLS and GA methods were used to select characteristic wavelengths,and the GA PLS model was the best among the models developed,the R 2 v and root mean square error of validation values were 0.913 6 and 7.239 8 mg/(100 g),the residual predictive deviation value was 3.339 7.The optimal prediction model was verified,where the R 2 p and root mean square error were 0.831 4 and 10.766 3 mg/(100 g),respectively,and the residual sum was-10.041 7 mg/(100 g).These results confirmed the feasibility of using near-infrared spectroscopy for the non-destructive detection of anthocyanin of purple sweet potato,which can provide a reliable method for intelligent screening of raw materials of purple sweet potato and quality monitoring during storage.

关 键 词：紫薯 花青素 近红外光谱 偏最小二乘回归 遗传算法 

分 类 号：O657.33[理学—分析化学]