摘要
以加工过程中的苹果脆片为对象,对其水分、可溶性固形物、总糖、可滴定酸和硬度5个品质指标进行综合分析,得到各指标的权重和脆片品质的综合得分,根据综合得分情况,将脆片分为A(高品质)、B(中品质)、C(低品质)三类。利用近红外光谱技术获取苹果脆片光谱信息,运用偏最小二乘判别分析(partial least-squares discriminant analysis,PLSDA)方法建立基于光谱特征的苹果脆片综合品质得分的判别模型,对3类脆片进行分类的实际值和预测值的相关系数R分别为0.84,0.63,0.89,均方根误差RMSEC分别为0.26,0.34,0.22,预测集样本的判别准确率分别为83.33%,80.0%,93.33%,说明了结合数据融合技术与近红外光谱评价加工过程中苹果脆片综合品质具有较好的可行性。
In this study,five quality indicators,i.e.moisture,soluble solid content,total sugar content,titratable acid content and hardness,of apple chips during processing period were analyzed by analytic hierarchy process,and quality scores was obtained.Near infrared spectroscopy（NIRS）combined with partial least-squares discriminant analysis（PLS-DA）was applied for the prediction of quality scores of apple chips.The results showed that the correlation coefficients between predicted category variable of calibration and the measured category variable were 0.84,0.63 and 0.89,and the root mean square error of cross validation were 0.26,0.34 and 0.22 for each quality category,respectively.The discrimination accuracy for this model were found 83.33%,80% and 93.33%.Thus,this suggested that NIRS combined with PLS-DA method was a potential way to assess quality of apple chips processing period.
出处
《食品与机械》
CSCD
北大核心
2016年第12期45-49,共5页
Food and Machinery
基金
上海市自然科学基金(编号:14ZR1419200)
关键词
苹果脆片
数据融合
近红外
品质评价
apple chips
data fusion processing
NIR
quality assessment
作者简介
管骁，男，上海理工大学副教授，博士。
通信作者：刘静（1979-），女，上海海事大学副教授，博士。E-mail：jingliu@shmtu．edu．cn
