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首页> 外文期刊>Intelligent automation and soft computing >CLUSTER ANALYSIS OF CITRUS GENOTYPES USING NEAR-INFRARED SPECTROSCOPY
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CLUSTER ANALYSIS OF CITRUS GENOTYPES USING NEAR-INFRARED SPECTROSCOPY

机译:基于近红外光谱的柑橘基因型聚类分析

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摘要

There are many genotypes and varieties in the citrus family. Currently, citrus classification systems have significant divergences in varieties of species, and subgenus classification as well. In this study, near-infrared spectroscopy technique was used to acquire spectral information on the surface of citrus fruits. Cluster analysis was consequently conducted to identify citrus genotypes. Results indicated that the combination of 9-point moving average smoothing and multiplicative scattering correction was optimal for preprocessing spectral data. In the spectral range of 1,180-1,220 nm, the cumulative reliability of the first two principal components were greater than 99.4%, and sweet oranges were clustered into an independent class. In 1,280-1,320 nm, systematic clustering performed better than principal component clustering, and all other sour oranges, except Goutoucheng, were clustered into a single clade. With dimensions reduction, the cumulative reliability of first five principle components in full band of 1,000-2,350 nm reached up to 99.1%. Using principal component cluster analysis, pomelo and loose-skin mandarin were clustered together; sweet and sour oranges were clearly separated. Pomelo being clustered with loose-skin mandarin, implies that they may have a hybrid origin; Jiaogan Mandarin, Daoxian yeju Mandarin, Goutoucheng sour oranges, and Zhuhongju sour tangerine were clustered with sweet orange, which implies old varieties may contain similar characteristic matters as sweet orange; Given that Jinlong lemon and Ranpour lime were clustered with sour orange, they were proved to originated from sour orange. The study indicates the great potential of spectral analysis for citrus genotype identification and classification.
机译:柑橘家族有许多基因型和变种。当前,柑橘分类系统在物种变种和亚属分类上也有很大差异。在这项研究中,近红外光谱技术被用来获取柑橘类水果表面的光谱信息。因此,进行了聚类分析以鉴定柑橘的基因型。结果表明,9点移动平均平滑和乘法散射校正相结合是预处理光谱数据的最佳选择。在1,180-1,220 nm的光谱范围内,前两个主要成分的累积可靠性大于99.4%,并且甜橙被归类为一个独立的类。在1,280-1,320 nm处,系统聚类的表现要好于主成分聚类,除钩头城以外的所有其他酸橙均聚集成单个进化枝。随着尺寸的减小,在1,000-2,350 nm的全波段中,前五个主要组件的累积可靠性达到了99.1%。使用主成分聚类分析,将柚子和皮肤普通话聚类在一起;糖醋橘子明显分开了。柚皮和普通话簇拥在一起,暗示它们可能有杂种起源。椒干普通话,道县野菊普通话,狗头城酸橙和朱红菊酸橘子与甜橙簇集在一起,这意味着旧品种可能包含与甜橙相似的特征物质。考虑到金龙柠檬和兰珀酸橙与酸橙聚在一起,证明它们起源于酸橙。研究表明,光谱分析对于柑橘基因型的鉴定和分类具有巨大的潜力。

著录项

  • 来源
    《Intelligent automation and soft computing 》 |2013年第3期| 347-359| 共13页
  • 作者单位

    College of Horticulture and Landscape, Southwest University, Beibei, Chongqing 400715, China,Citrus Research Institute, Southwest University/National Citrus Engineering Research Center, Beibei, Chongqing 400712, China;

    United States Department of Agriculture, Agricultural Research Service, Crop Production Systems Research Unit, Stoneville, MS 38776, USA;

    Citrus Research Institute, Southwest University/National Citrus Engineering Research Center, Beibei, Chongqing 400712, China;

    Citrus Research Institute, Southwest University/National Citrus Engineering Research Center, Beibei, Chongqing 400712, China;

    Citrus Research Institute, Southwest University/National Citrus Engineering Research Center, Beibei, Chongqing 400712, China;

    Citrus Research Institute, Southwest University/National Citrus Engineering Research Center, Beibei, Chongqing 400712, China;

    Citrus Research Institute, Southwest University/National Citrus Engineering Research Center, Beibei, Chongqing 400712, China;

    College of Horticulture and Landscape, Southwest University, Beibei, Chongqing 400715, China,Citrus Research Institute, Southwest University/National Citrus Engineering Research Center, Beibei, Chongqing 400712, China;

    Citrus Research Institute, Southwest University/National Citrus Engineering Research Center, Beibei, Chongqing 400712, China;

    College of Horticulture and Landscape, Southwest University, Beibei, Chongqing 400715, China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Near-infrared Spectroscopy; Citrus Genotype; Variety Classification; Cluster Analysis; Principal Component;

    机译:近红外光谱;柑橘基因型品种分类;聚类分析;主成分;

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