摘要
本研究利用近红外方法预测馒头品质评分参数,并取得了较好的预测效果.从150份小麦粉样品中筛选出31个具有不同品质特性的小麦粉样品,使用FOSS Infraxact Lab近红外光谱仪在570～1 850nm波长下扫描,按实验室馒头制作方法制作馒头并进行评分,使用WinISI Ⅲ处理软件处理数据,结合修正偏最小二乘法（MPLS）建立了定标模型,高径比、比容、色泽、外观性状等11项参数的定标决定系数（r2）在0.60～0.94之间,定标标准误差（SEC）范围为0.02～2.06,并且取得较好的交叉验证相关系数（1-VR）和较低的交叉验证标准误差（SECV）,结果表明利用近红外方法预测馒头品质评分参数具有可行性.
The near infrared method was firstly used to predict steamed bun quality scoring parameters to achieved gold prediction results in the paper.Thirty-one samples with different quality characteristics have been selected from 150 pieces of flour samples.The near infrared spectrum of the thirty one samples were obtained by the FOSS near-infrared spectroscopy （Infraxact Lab） at a wavelengths between 570 ～ 1 850 nm,and steamed bun obtained from each sample was scored.The software WinISI Ⅲ combined with modified partial least squares was applied to build calibration models.The ranges of regression squared and standard error of calibration of eleven indicators,including the height-diameter ratio,specific volume,color,appearance,surface structure,etc.were 0.60 ～ 0.94and 0.02 ～ 2.06 respectively.Each parameter exhibited a high cross-validation relation coefficient （1-VR） value and relative low standard error of cross validation （SECV） value.The results showed that the predicting score of steamed bun in NIR models was feasible.
出处
《中国粮油学报》
EI
CAS
CSCD
北大核心
2014年第4期113-117,共5页
Journal of the Chinese Cereals and Oils Association
关键词
近红外光谱
馒头
品质评分
预测
near-infrared spectrum
steamed bun
quality scores
prediction
作者简介
郝学飞,男,1979年出生,助理研究员,粮油食品检测及标准制定
