摘要
本实验利用Purespect型近红外光谱仪获得南果梨样品的光谱数据,采用不同的化学测定方法测定样品中糖、酸含量,分别以可溶性固形物含量(SSC)、还原糖含量(RSC)、总酸度含量(TA)和有效酸度(pH)为定标参数建立四项指标近红外定标模型,并分析比较4个模型的RC、RP、RMSEC、RMSEP及预测集样品的残差e。结果表明:对于糖度指标而言,SSC模型的RC、RP值高于RSC模型,且残差e分布较RSC的均匀,SSC是南果梨糖度近红外光谱无损检测定标模型建立适宜的定标参数;对于酸度指标而言,pH模型的RC值高于TA模型,两个酸度模型的RP均大于0.9,且二者之间无明显差异,TA模型的残差e分布优于pH模型,考虑到实际应用效果,确定酸度定标模型采用TA作为定标参数。
Near infrared spectroscopy models for nondestructive detection of sugar content and acidity of Nanguo pears were established based on the spectrum recorded by Purespect near infrared instrument and the content of soluble solids （SSC）, reducing sugar （RSC）, and titratable acidity （TA） and pH value determined by chemical methods. Based on the comparison results of correlation coefficient of calibration （Pc）, correlation coefficient of prediction （Rp）, root mean standard error of calibration （RMSEC）, root mean standard error of prediction （RMSEP） and sum of residual error, the best parameters which were used for building up NIR models were confirmed. Results showed that the Rc and RP value of SSC are higher than those of RSC, and the residual error is better distributed Therefore, SSC is the optimum parameters. NIR models for detection of sugar. Rc value of pH is higher than that of TA, Pp of both TA and pH are above 0.9, and the residual error sum of TA is better than pH. Considering the purpose of practice application, TA is the optimum parameter for NIR models for detection of acid.
出处
《食品科学》
EI
CAS
CSCD
北大核心
2008年第10期512-516,共5页
Food Science
关键词
南果梨
近红外光谱
糖度
酸度
Nanguo pear
NIR spectrum
sugar content
acidity
