Study on the method of canned citrus quality measurement based on the Near-infrared spectroscopy
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摘要: 为了快速检测柑橘罐头主要营养指标的含量,实验对柑橘罐头进行光谱采集,通过偏最小二乘(PLS)线性拟合建立关于柑橘罐头总糖、总酸、黄酮和维生素C的近红外定量分析模型。通过分析比较不同的光谱预处理方法对近红外光谱模型的影响,其中经归一化预处理后建立的总糖和黄酮模型最优,相关系数分别为0.9156和0.9147,交互验证均方根误差(RMSECV)为0.6305%和2.7028 mg/100 g;平滑预处理后总酸的相关系数为0.8921,RMSECV为0.0539%;以原始光谱数据建立的维生素C模型的相关系数为0.9129,RMSECV为1.4323 mg/100 g;预测集总糖、总酸、黄酮和维生素C的相关系数分别为0.8519、0.8106、0.8334和0.8425,预测均方根误差(RMSEP)为0.8969%、0.0638%、3.6055 mg/100 g和1.9732 mg/100 g。实验结果表明:应用近红外光谱技术测定柑橘罐头中总糖、总酸、黄酮和维生素C的含量是可行的。Abstract: In order to quickly detect the contents of main nutrition indicators of canned citrus,the experiment was conducted to spectral acquisition of canned citrus,by Partial Least Squares(PLS) linear fit to establish Nearinfrared quantitative analysis model on canned citrus total sugar,acid,flavonoids and vitamin C. Analyzed and compared the effects of different spectral pretreatment methods on Near- infrared spectroscopy models, in which the normalized model of total sugar and flavonoids were optimal,correlation coefficients were 0.9156 and0.9147,root mean square error of cross-validation(RMSECV) were 0.6305% and 2.7028 mg/100 g. Smoothed model of total acid correlation coefficient was 0.8921,RMSECV was 0.0539%. Model of vitamin C based on raw spectral data whose correlation coefficient was 0.9129,RMSECV was 1.4323 mg/100 g. Through validation,prediction set of total sugar,total acid,flavonoids and vitamin C correlation coefficient were 0.8519,0.8106,0.8334 and 0.8425,predict root mean square error(RMSEP) were 0.8969%,0.0638%,3.6055 mg/100 g and1.9732 mg/100 g. The results showed that Near-infrared spectroscopy for rapid detection of canned citrus total sugar,total acid,flavonoids and vitamin C content was feasible.
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Keywords:
- canned citrus /
- Near-infrared /
- total sugar /
- total acid /
- flavonoids /
- vitamin c
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[1] 单杨.中国柑橘工业的现状、发展趋势与对策[J].中国食品学报,2008,8(1):1-8. [2] 王俊,崔绍庆,陈新伟.电子鼻传感技术与应用研究进展[J].农业机械学报,2013,44(11):160-167. [3] 毛莎莎,曾明,何绍兰,等.近红外光谱技术在水果成熟期预测中的应用[J].亚热带植物科学,2010,39(1):82-89. [4] Cao Fang,Wu Di,He Yong.Soluble solids content and p H prediction and varieties discrimination of grapes based on visible near infrared spectroscopy[J].Computers and electronics in agriculture,2010(71):15-18.
[5] R Ferrer-Gallego,J M Hernandez-Hierro,J C Rivas-Gonzalo,et al.Determination of phenolic compounds of grape skins during ripening by NIR spectroscopy[J].LWT-Food Science and Technology,2011,44(4):847-853.
[6] Jiangbo Li,Wenqian Huang,Liping Chen,et al.Variable Selection in Visible and Near-Infrared Spectral Analysis for Noninvasive Determination of Soluble Solids Content of‘Ya’Pear[J].Food Anal,2014,7:1891-1902.
[7] Aichen Wang,Lijuan Xie.Technology using near infrared spectroscopic and multivariate analysis to determine the soluble solids content of citrus fruit[J].Journal of Food Engineering,2014,143:17-24.
[8] 吴晓红,陈宝宏,李小华.柑橘类水果中总酸与总糖的测定[J].食品研究与开发,2012,33(9):144-146. [9] 李文生,冯晓元,王宝刚,等.应用自动电位滴定仪测定水果中的可滴定酸[J].食品科学,2009,30(4):247-249. [10] 刘志明,唐彦君,吴海舟,等.苯酚-硫酸法测定葡萄酒中总糖含量的样品处理[J].中国酿造,2011(2):158-161. [11] NY/T 2010-2011柑橘类水果及其制品中总黄酮含量的测定[S].2011. [12] 曹建康,姜微波,赵玉梅.果蔬采后生理生化实验指导[M].北京:中国轻工业出版社,2007. [13] 闵顺耕,李宁,张明祥.近红外光谱分析中异常值的判别与定量模型优化[J].光谱学与光谱分析,2004,24(10):1205-1209. [14] 夏俊芳.基于近红外光谱的贮藏脐橙品质无损检测方法研究[D].武汉:华中农业大学,2007.
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