孙海霞,张淑娟,薛建新,刘蒋龙,赵旭婷.鲜枣内部综合品质光谱评价指标建立与分析[J].农业机械学报,2017,48(9):324-329.
SUN Haixia,ZHANG Shujuan,XUE Jianxin,LIU Jianglong,ZHAO Xuting.Establishment and Analysis of Internal Comprehensive Quality Spectral Evaluation Index for Fresh Jujube[J].Transactions of the Chinese Society for Agricultural Machinery,2017,48(9):324-329.
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鲜枣内部综合品质光谱评价指标建立与分析   [下载全文]
Establishment and Analysis of Internal Comprehensive Quality Spectral Evaluation Index for Fresh Jujube   [Download Pdf][in English]
投稿时间:2017-01-02  
DOI:10.6041/j.issn.1000-1298.2017.09.041
中文关键词:  鲜枣  内部综合品质  特征提取  可见/近红外光谱
基金项目:国家自然科学基金项目(31271973)
作者单位
孙海霞 山西农业大学 
张淑娟 山西农业大学 
薛建新 山西农业大学 
刘蒋龙 山西农业大学 
赵旭婷 山西农业大学 
中文摘要:为实现鲜枣内部综合品质的在线无损快速检测,利用可见/近红外光谱漫反射技术,针对完熟期壶瓶枣的内部品质,包括含水率、可溶性固形物含量、硬度、可溶性蛋白质含量、维生素C含量5项指标,分别采用竞争性自适应重加权算法(CARS)提取特征波长并建立最小二乘-支持向量机(LS-SVM)预测模型,硬度预测模型的相关系数和均方根误差分别为0.9452和41.6849,其余品质预测模型的相关系数均在0.9230及以上、均方根误差均在3.7792及以下。在此基础上,对5项品质指标进行了相关性分析,表明在0.01或0.05水平上两两指标间存在极显著或显著的相关性,故采用因子分析法构建了内部综合品质评价指标,建立了CARS-LS-SVM预测模型,结果表明该模型的相关系数和均方根误差分别为0.9241和6.0635,预测精度较高。研究表明,所建立的CARS-LS-SVM模型可有效实现鲜枣内部综合品质的评价。
SUN Haixia  ZHANG Shujuan  XUE Jianxin  LIU Jianglong  ZHAO Xuting
Shanxi Agricultural University,Shanxi Agricultural University,Shanxi Agricultural University,Shanxi Agricultural University and Shanxi Agricultural University
Key Words:fresh jujube  internal comprehensive quality  feature extraction  visible/near-infrared spectrum
Abstract:A non-destructive method for on-line determining the internal comprehensive quality of Huping jujube fruit was investigated based on visible/near-infrared reflection spectrum. Moisture content, soluble solid content, firmness, soluble protein content and vitamin C content were respectively used as internal indexes to assess the quality of Huping jujube at full ripe stage. Competitive adaptive reweighted sampling (CARS) was applied to select sensitive wavelengths. Models of the least squares-support vector machines (LS-SVM) were built based on the sensitive wavelengths respectively. The model of firmness showed that the correlation coefficient of prediction was 0.9452 and root mean square error of prediction was 41.6849. The other four models obtained the better results with the correlation coefficient of each prediction over 0.9230 and root mean square error of each prediction from 0.2674 to 3.7792. Then, the correlation was analyzed between the quality indexes. The results indicated that an extremely significant or a significant correlation was revealed between any two indexes in the P<0.01 or P<0.05 levels. Therefore, factor analysis was carried out on five internal quality index of fresh jujube to develop the internal comprehensive quality index, and the CARS-LS-SVM model of this index was established. The results indicated that the correlation coefficient of prediction was 0.9241 and root mean square error of prediction was 6.0635. This research showed that the established CARS-LS-SVM model was effective to realize evaluation of the internal comprehensive quality on fresh jujube. This research provided theoretical basis for on-line, rapid and non-destructive detection on internal comprehensive quality of fresh jujube.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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