采用近红外光谱技术快速检测桃汁原汁含量的方法研究
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摘要
利用近红外光谱技术结合偏最小二乘法(PLS)对桃汁样本中原汁的含量进行定量分析.采用5种不同预处理方法优化检测数据,结果表明标准化预处理所建立的定量检测模型性能最优,其预测相关系数(R2p)、预测均方根误差(RMSEP)、校正相关系数(R2c)、校正均方根误差(RMSEC)分别为0.998 8、0.014 0、0.997 3、0.021 2.研究为桃汁等果汁饮品中原汁含量的检测提供一种快速、无损、简便、廉价、准确的方法.
The content of normal juice in peach juice drinks was quantitatively analyzed by using the near infrared spectroscopy(NIR) and partial least squares(PLS). Test data was optimized by using five different pretreatment method,and the results showed that the quantitative detection model based on the normalized pretreatment exhibits the optimal performance,whose correlation coefficient of prediction(R2p),root mean square errors of prediction(RMSEP),correlation coefficient of calibration(R2c),and root mean squared error of calibration(RMSEC) are 0. 998 8,0. 014 0,0. 997 3 and0.021 2,respectively. Thus,this study may provide a rapid,nondestructive,simple,cheap and accurate method for rapidly evaluating the quality of different commercially available fruit juice drinks.
The content of normal juice in peach juice drinks was quantitatively analyzed by using the near infrared spectroscopy(NIR) and partial least squares(PLS). Test data was optimized by using five different pretreatment method,and the results showed that the quantitative detection model based on the normalized pretreatment exhibits the optimal performance,whose correlation coefficient of prediction(R2p),root mean square errors of prediction(RMSEP),correlation coefficient of calibration(R2c),and root mean squared error of calibration(RMSEC) are 0. 998 8,0. 014 0,0. 997 3 and0.021 2,respectively. Thus,this study may provide a rapid,nondestructive,simple,cheap and accurate method for rapidly evaluating the quality of different commercially available fruit juice drinks.
引文
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[13]付才力,李颖,陈荔凡,等.近红外光谱技术快速检测莲子粉[J].光谱学与光谱分析,2018,38(2):424-429.
[2]WILLIAMS A B,AYEJUYO O O,OGUNYALE A F. Trace metal levels in fruit juices and carbonated beverages in Nigeria[J].Environmental Monitoring and Assessment,2009,156(14):303-306.
[3]康明丽,潘思轶,范刚,等. HS-SPME-GC-MS法测定不同成熟度蜜柑果汁挥发性成分[J].食品工业科技,2014,35(19):326-330.
[4]PEI M,HUANG X. Determination of trace phenolic acids in fruit juice samples using multiple monolithic fiber solid-phase microextraction coupled with high-performance liquid chromatography[J]. Analytical Methods,2016,8(18):3831-3838.
[5]孙通,魏小梅,胡田,等.可见/近红外结合MIA变量优选和支持向量机判别山茶油的制取方式[J].食品工业科技,2014,35(20):62-65.
[6]MOSER J K,SINGH M,RENNICK K A,et al. Detection of corn adulteration in brazilian coffee(Coffea arabica)by tocopherol profiling and NIR spectroscopy[J]. Journal of Agricultural&Food Chemistry,2015,63(49):10662-10668.
[7]陈兰珍.蜂蜜品质近红外光谱评价技术研究[D].北京:中国农业科学院,2010.
[8]丁家欣,张秋海,李树莉,等.应用近红外光谱法快速测定蜂蜜中葡萄糖和果糖含量[J].光谱学与光谱分析,2016,36(增刊1):197-198.
[9]LI Y,GUO Y J,LIU C,et al. SPA combined with swarm intelligence optimization algorithms for wavelength variable selection to rapidly discriminate the adulteration of apple juice[J]. Food Analytical Methods,2017,10(6):1965-1971.
[10]谷如祥,赵武奇,石珂心,等.近红外光谱测定苹果饮料中原果汁含量[J].食品工业科技,2013,34(20):75-77.
[11]朱大洲,孟超英,屠振华,等.不同类型近红外模型在苹果汁检测中的应用[J].农业工程学报,2009,25(增刊2):325-329.
[12] LIN W,CHAI Q,WANG W,et al. A novel method for geographical origin identification of Tetrastigma hemsleyanum(Sanyeqing)by near-infrared spectroscopy[J]. Analytical Methods,2018,10(25):2980-2988.
[13]付才力,李颖,陈荔凡,等.近红外光谱技术快速检测莲子粉[J].光谱学与光谱分析,2018,38(2):424-429.