Scientia Agricultura Sinica ›› 2012, Vol. 45 ›› Issue (12): 2431-2437.doi: 10.3864/j.issn.0578-1752.2012.12.011

• HORTICULTURE • Previous Articles     Next Articles

Multiple Analysis of Relationship of Agronomic Traits and Yield Formation in Ginger  

 LI  Xiu, XU  Kun, GONG  Biao, CAO  Bi-Li, WANG  Zhong-Bin   

  1. 山东农业大学园艺科学与工程学院/作物生物学国家重点实验室/农业部黄淮地区园艺作物生物学与种质创制重点实验室， 山东泰安271018
  • Received:2011-12-23 Online:2012-06-15 Published:2012-04-27

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Abstract: 【Objective】 The purpose of this study was to provide academic evidence for germplasm evaluation and innovation of ginger, and identify the primary indexes of yield by investigating the variation of agronomic traits of ginger.【Method】The correlation, path analysis, principal components analysis and multiple linear regression analysis were conducted, whilst integrated the growth status of ginger, and applied critical-path analysis, to identify the primary indexes of ginger yield. 【Result】The results showed that the variation coefficient of agronomic traits of ginger reached 11.4%-51.3%, and the yield had a extremely significant correlation with stem diameter, stem FW, plant height, leaf FW and root FW, but a significant or extremely significant negative correlation with rhizome DM content and branch number. Plant height, stem diameter, root FW, stem FW and rhizome DM content were named as determinative morphological factors of high-yielding varieties, and branch number, leaf number and ginger bulb number were named as determinative morphological factors of low-yielding varieties. The determination coefficient of four factors selected by multiple linear regression analysis to ginger yield model was 0.8194.【Conclusion】The major determining factors of ginger yield were rhizome DM content, leaf FW, stem diameter and stem FW. The high yield varieties had thickest stem, fewer branch number, thicker leaf, developed assimilation system, and lower rhizome DM content.

Key words: ginger(Zingiber officinale Roscoe), agronomic traits, correlation analysis, path analysis, principal components analysis, regression analysis, determining factor of yield

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