| 近红外光谱快速检测食用油必需脂肪酸 |
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| 引用本文： | 张 辉,吴 迪,李 想,石品艳,王思寒,冯凤琴,何 勇.近红外光谱快速检测食用油必需脂肪酸[J].农业工程学报,2012,28(7):266-270. |
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| 作者姓名： | 张 辉 吴 迪 李 想 石品艳 王思寒 冯凤琴 何 勇 |
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| 作者单位： | 浙江大学生物系统工程与食品科学学院,杭州,310029 |
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| 基金项目： | 国家科技支撑计划（No.2006BAD05A02）；国家高技术研究发展计划（“863”计划）项目（2007AA10Z210） |
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| 摘 要： | 为了建立食用油必需脂肪酸快速检测的方法,该研究提出了基于近红外光谱技术检测食用油中α-亚麻酸和亚油酸含量的快速测定方法。对光谱信息分别采用偏最小二乘回归方法(PLS)和最小二乘支持向量机(LS-SVM)建立模型。比较了多种光谱预处理方法对模型预测能力的影响。结果表明对于亚油酸含量的预测,采用Savitzky-Golay平滑法结合多元散射校正(MSC)的光谱预处理所建立的LS-SVM模型最优。预测集的决定系数(R2)、预测均方根误差(RMSEP)和剩余预测偏差(RPD)分别达到了0.989,0.0161和9.4783。对于α-亚麻酸含量的预测,采用Savitzky-Golay平滑法结合标准正态变换(SNV)的光谱预处理所建立的LS-SVM模型最优。α-亚麻酸含量预测结果的R2、RMSEP和RPD为0.972,0.0036和6.0561,据此表明,应用近红外光谱技术能够检测食用油中α-亚麻酸和亚油酸的含量,为快速检测食用油的必需脂肪酸提供了参考。
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| 关 键 词： | 近红外光谱 模型 优化 α-亚麻酸和亚油酸 食用油 检测 |
| 收稿时间： | 2010/10/9 0:00:00 |
| 修稿时间： | 2011/11/21 0:00:00 |
Rapid determination of essential fatty acids in edible oils based on near infrared spectroscopy |
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| Zhang Hui,Wu Di,Li Xiang,Shi Pinyan,Wang Sihan,Feng Fengqin and He Yong.Rapid determination of essential fatty acids in edible oils based on near infrared spectroscopy[J].Transactions of the Chinese Society of Agricultural Engineering,2012,28(7):266-270. |
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| Authors: | Zhang Hui Wu Di Li Xiang Shi Pinyan Wang Sihan Feng Fengqin and He Yong |
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| Institution: | (College of Biosystems Engineering and Food Science,Zhejiang University,Hangzhou,310029,China) |
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| Abstract: | In order to find out a fast quantitative determination method for the essential fatty acids in edible oils,near infrared spectroscopy was applied in determination of the contents ofα-linolenic acid and linoleic acid.The chemometrics models between near infrared spectra and the contents ofα-linolenic acid and linoleic acid were established by partial least squares regression(PLS)and least-squares support vector machine(LS-SVM).Several common used spectral pretreatment methods were used to establish different PLS and LS-SVM models.For linoleic acid prediction,best predictive performance was obtained using LS-SVM model and spectral pretreatment of Savitzky-Golay smoothing and multiplicative scatter correction(MSC).Coefficient of determination(Rp 2),root mean square error for prediction(RMSEP)and residual predictive deviation(RPD)were 0.0161,0.989 and 9.4783,respectively.For α-linolenic acid prediction,best predictive performance was obtained using LS-SVM model and the spectral pretreatment of Savitzky-Golay smoothing and standard normal variation(SNV).Rp 2,RMSEP and RPD were 0.0036,0.972 and 6.0561,respectively.The results indicate that it is feasible to use near infrared spectroscopy for fast determination ofα-linolenic acid and linoleic acid contents in edible oils. |
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| Keywords: | near infrared spectroscopy models optimization α-linolenic acid and linolenic acid edible oils determination |
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