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投稿时间:2019-03-14
投稿时间:2019-03-14
中文摘要: 该文提出一种对松原不同品种大米进行判别的方法,对来自松原的稻花香、小高粱、通系926、吉粳515、农大521,5 个品种共368 个大米样品,利用波数范围为12 000 cm-1~4 000 cm-1 的傅里叶近红外光谱仪获取光谱数据并对数据进行6 种方法的预处理。结果表明,一阶导数结合SG9 点平滑为最佳预处理方法,并用偏最小二乘判别(partial least squares discrimination analysis,PLS-DA)方法对校正样本建立判别分析模型,用验证集对模型进行验证,模型对验证集中稻花香、小高粱、通系926、吉粳515、农大521 共5 个品种的识别率均为100%;且优于主成分分析的结果。用来自柳河和梅河的稻花香样本与松原的稻花香样本进行产地判别,结果显示,此模型可以将松原样本与非松原样本进行判别。
中文关键词: 品种鉴别 近红外光谱 主成分分析 偏最小二乘判别(PLS-DA) 产地确证
Abstract:This paper proposes a method for identifying different varieties of rice in Songyuan.For 368 rice samples from five varieties of Dao Huaxiang,Xiao Gaoliang,Tongxi926,Jijing515 and Nongda521 from Songyuan.Using Fourier transform infrared spectroscopy with a wave number in the range of 12 000 cm-1-4 000 cm-1 to acquire spectral data and preprocesses the data in six ways.The analysis results showed that the first derivative combined with SG9 point smoothing was the best pretreatment method.And using the partial least squares discriminant partial least squares discrimination analysis(PLS-DA)method to establish a discriminant analysis model for the corrected samples,and verify the model with the verification set.The model is validated by the combination of Dao Huaxiang,Xiao Gaoliang,Tongxi926,Jijing515 and Nongda521.The recognition rate of each variety was 100 %.And better than the results of principal component analysis.Dao Huaxiang samples from Liuhe and Meihe,and the same variety from Songyuan were used for discrimination.The results showed that the model can distinguish between Songyuan samples and non-Songyuan samples.This study provided a reference method for the identification and source identification of Songyuan rice varieties.
keywords: variety identification near-infrared spectroscopy principal component analysis partial least squares discrimination(PLS-DA) origin confirmation
文章编号:202004025 中图分类号: 文献标志码:
基金项目:吉林省重点科技研发项目(20180201051NY)
作者 | 单位 |
王朝辉,高地,赖瀚清,王艳辉,沈海鸥,陈雷,程娇娇,王靖会 | 吉林农业大学食品科学与工程学院,吉林长春130118;吉林省长春市净月开发区福祉街道办事处,吉林长春130122;吉林农业大学资源与环境学院,吉林长春130118;吉林省长春市交警支队南关区大队,吉林长春130000;吉林农业大学信息技术学院,吉林长春130118 |
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