近红外光谱检测猕猴桃可溶性固形物和pH  

Detecting of Soluble Solid Content and pH of Kiwifruit by Near-infrared Spectroscopy

作　　者：王旭[1] 宋庆恒 

机构地区：[1]怀化学院机械与光电物理学院,怀化418008 [2]武陵山片区生态农业智能控制技术湖南省重点实验室,怀化418008

出　　处：《食品工业》2017年第3期305-307,共3页The Food Industry

基　　金：湖南省教育厅科研项目(15C1092);武陵山片区生态农业智能控制技术湖南省重点实验室科研项目(ZNKZ2015-3)

摘　　要：研究了利用近红外漫反射无损检测海沃德猕猴桃可溶性固形物含量和pH的方法。以45个湘西海沃德猕猴桃为标准样本,采集1 000~1 800 nm范围的近红外光光谱,光谱采用9点滑动窗口平滑处理、一阶微分和多元散射校正分别进行预处理,然后采用偏最小二乘算法(PLS)、主成分回归算法(PCR)和多元线性回归算法(MLR)分别建立预测模型。经比较,采用一阶微分的PLS模型预测性能最好。This paper studies detecting soluble solid content（SSC） and pH of Hayward kiwifruits by using near-infrared spectroscopy. A total 45 samples were used to collect near-infrared spectroscopy between 1 000-1 800 nm, then 9 point moving average filter, the first derivative D1log（1/R） and multi-variant scattering correction were used to preprocess the primitive spectrum of Hayward kiwifruits, and then the partial least squares（PLS）, the principal component regression（PCR）, the multi-linear regression（MLR） were used to build prediction models which were used to quantitatively analyze SSC content and pH of Hayward kiwifruits. The PLS model with D1log（1/R） data treatment was prior to the other two ways based on the comparative analysis.

关 键 词：近红外漫反射 无损检测 可溶性固形物含量 PH 海沃德猕猴桃 

分 类 号：O657.33[理学—分析化学] S663.4[理学—化学]