| 近红外光谱柑橘货架期的快速鉴别模型——基于主成分分析神经网络 |
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| 引用本文： | 刘辉军,李文军,吕进,吴向峰.近红外光谱柑橘货架期的快速鉴别模型——基于主成分分析神经网络[J].农机化研究,2009,31(5). |
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| 作者姓名： | 刘辉军 李文军 吕进 吴向峰 |
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| 作者单位： | 1. 中国计量学院,计量技术工程学院,杭州,310018
2. 福建出入境检验检疫局,福州,350001 |
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| 基金项目： | 浙江省科技计划项目，浙江省仪器科学与技术重中之重项目 |
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| 摘 要： | 利用近红外光谱技术进行了柑橘货架期的快速鉴别模型的研究.在两个不同的时间采集从市场上购买的黄岩地区的32个柑橘(同一时间采摘)的近红外光谱,并将不同时间采集光谱时的柑橘的货架期分别定为1类和2类(间隔为10天),对不同货架期的柑橘样品光谱进行主成分特征提取,将提取的特征变量作为神经网络的输入,建立了基于主成分和神经网络的近红外光谱柑橘货架期的快速鉴别模型.所建模型对1类中7个样品货架期的鉴别结果中有4个样品的货架期预测准确率在90%以上;对2类中8个样品货架期的鉴别结果准确率均在90%以上.结果表明,近红外光谱技术可以很好地进行柑橘类水果的货架期的快速鉴别.
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| 关 键 词： | 近红外光谱 主成分分析 径向神经网络 柑橘 货架期 |
Rapid Shelf-life Identification Model of Citrus Based on Principal Component Analysis and Radial Neural Network by Near Infrared Spectroscopy |
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| Liu Huijun,Li Wenjun,Lv Jin,Wu Xiangfeng.Rapid Shelf-life Identification Model of Citrus Based on Principal Component Analysis and Radial Neural Network by Near Infrared Spectroscopy[J].Journal of Agricultural Mechanization Research,2009,31(5). |
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| Authors: | Liu Huijun Li Wenjun Lv Jin Wu Xiangfeng |
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| Institution: | 1.College of Metrological Technology and Engineering;China Jiliang University;Hangzhou 310018;China;2.Fujian Entry-exit Inspection and Quarantine Bureau;Fuzhou 350001;China |
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| Abstract: | The near-infrared spectroscopy was used in modeling of rapid shelf-life identification in citrus.The spectrum of 32 citrus yielded in Huangyan was collected at two different time,and were set for class 1 and class 2(interval of 10 days).The principal component analysis was applied in feature selection,the characteristics of variables used as the neural network input.The shelf-life identification model of citrus based on principal component analysi and neural network by near-infrared spectroscopy was built.T... |
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| Keywords: | near-infrared spectrum principal component analysis radial neural network citrus shelf life |
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