马铃薯主要营养成分的近红外光谱分析

食品科学 ›› 2013, Vol. 34 ›› Issue (2): 165-169.

马铃薯主要营养成分的近红外光谱分析

张小燕,杨炳南

中国农业机械化科学研究院

收稿日期:2011-11-11 修回日期:2012-11-30 出版日期:2013-01-25 发布日期:2013-01-15
通讯作者: 杨炳南 E-mail:yangbn@caams.org.cn
基金资助:
公益性行业（农业）科研专项经费项目“大宗农产品加工特性研究与品质评价技术”

Analysis of Models for Main Potato Nutrients Content Based on Near Infrared Spectroscopy

Received:2011-11-11 Revised:2012-11-30 Online:2013-01-25 Published:2013-01-15

摘要/Abstract

摘要：

摘要：以44个品系马铃薯为原料，利用主成分分析(PCA)方法筛选出代表马铃薯块茎主要营养成分指标(水分、还原糖、淀粉和蛋白质)，应用偏最小二乘法(PLS)建立这四种营养成分的预测模型，并对模型预测结果进行了评价。试验结果表明，马铃薯主要营养成分的模型预测与其相应的化学测量值之间具有较好的相关性，对于水分模型，校正效果：R2cal =98.37%，RMSEE=0.445，RPD=7.84；交叉验证效果：R2cv=93.05%，RMSECV=0.84，RPD=3.79。还原糖模型校正模型效果：R2cal = 98.43%，RMSEE= 0.0236，RPD= 7.99；交叉验证效果：R2cv= 86.42%，RMSECV= 0.0598，RPD= 2.71。淀粉模型校正模型效果：R2cal = 97.13%，RMSEE= 0.577，RPD= 5.9；交叉验证效果：R2cv= 95.370%，RMSECV= 0.7，RPD= 4.65。蛋白质模型校正模型效果：R2cal = 98.41%，RMSEE= 0.0334，RPD= 7.92；交叉验证效果：R2cv= 89.49%，RMSECV= 0.0767，RPD= 3.08。

Abstract:

Analysis of Models for Main Potato Nutrients Content Based on Near Infrared Spectroscopy ZHANG Xiao-yan, YANG Bing-nan*, LIU Wei, ZHAO Feng-min, YANG Yan-chen, XING Li (Chinese Academy of Agricultural Mechanization Sciences, Beijing 100083, China) Abstract: With 44 different potato cultivars as the material, Principal component analysis (PCA) was used to select four indicators (water, reducing sugar, starch and protein) which can cover most information of potato samples. Predicted mathematic models for analysis were established and evaluated with partial least square (PLS) method. The accuracy of models was estimated by the determination coefficients (R2cal), relative predictive determination (RPD) and the root mean square errors of calibration (RMSEE), the determination coefficients (R2cv) and the root mean square errors of cross validation (RMSECV). For the calibration model of water, R2cal =98.37%, RMSEE=0.445, RPD=7.84; for the cross validation model of water, R2cv=93.05%, RMSECV=0.84, RPD=3.79. For the calibration model of reducing sugar, R2cal = 98.43%, RMSEE= 0.0236, RPD= 7.99; for the cross validation model of reducing sugar, R2cv= 86.42%, RMSECV= 0.0598, RPD= 2.71. For the calibration model of starch, R2cal = 97.13%, RMSEE= 0.577, RPD= 5.9; for the cross validation model of starch, R2cv= 95.370%, RMSECV= 0.7, RPD= 4.65. For the calibration model of protein, R2cal = 98.41%, RMSEE= 0.0334, RPD= 7.92; for the cross validation model of protein, R2cv= 89.49%, RMSECV= 0.0767, RPD= 3.08.

中图分类号:

O433.4

张小燕杨炳南. 马铃薯主要营养成分的近红外光谱分析[J]. 食品科学, 2013, 34(2): 165-169.

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