African Journal of
Agricultural Research

  • Abbreviation: Afr. J. Agric. Res.
  • Language: English
  • ISSN: 1991-637X
  • DOI: 10.5897/AJAR
  • Start Year: 2006
  • Published Articles: 6709

Full Length Research Paper

Variation, correlation, regression and path analyses in Eruca sativa Mill.

Banglian Huang
  • Banglian Huang
  • Hubei Collaborative Innovation Center for Green Transformation of Bio-Resources, College of Life Science, Hubei University, Wuhan 430062, China.
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Shiying Liao
  • Shiying Liao
  • National Key Lab of Crop Genetic Improvement, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.
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Chao Cheng
  • Chao Cheng
  • Hubei Collaborative Innovation Center for Green Transformation of Bio-Resources, College of Life Science, Hubei University, Wuhan 430062, China.
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Xueying Ye
  • Xueying Ye
  • Hubei Collaborative Innovation Center for Green Transformation of Bio-Resources, College of Life Science, Hubei University, Wuhan 430062, China.
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Mingdan Luo
  • Mingdan Luo
  • Hubei Collaborative Innovation Center for Green Transformation of Bio-Resources, College of Life Science, Hubei University, Wuhan 430062, China.
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Zaiyun Li
  • Zaiyun Li
  • Hubei Collaborative Innovation Center for Green Transformation of Bio-Resources, College of Life Science, Hubei University, Wuhan 430062, China.
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Detian Cai
  • Detian Cai
  • Hubei Collaborative Innovation Center for Green Transformation of Bio-Resources, College of Life Science, Hubei University, Wuhan 430062, China.
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Wenhua Wu
  • Wenhua Wu
  • Hubei Collaborative Innovation Center for Green Transformation of Bio-Resources, College of Life Science, Hubei University, Wuhan 430062, China.
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Bangquan Huang
  • Bangquan Huang
  • Hubei Collaborative Innovation Center for Green Transformation of Bio-Resources, College of Life Science, Hubei University, Wuhan 430062, China.
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  •  Received: 23 April 2014
  •  Accepted: 18 November 2014
  •  Published: 18 December 2014

Abstract

In the present study variation, correlation, regression and path coefficients in Eruca sativa Mill. were analyzed. Great variations were observed with agronomic and oil quality traits in Eruca. Partial correlation, stepwise regression and path analyses indicated that the contributions of siliqua number per plant (X7), seeds per siliqua (X8), 1000-seed weight (X9) and siliqua number of main raceme (X6) to seed yield per plant (Y) were highly significant and positive (P<0.01), and those of number of secondary branches (X4) and plant height (X1) were also significant and positive (P<0.05), while that of branching height (X2) was significant and negative (P<0.05). The regression formula of these agronomic traits to seed yield per plant is Y= -2.134 + 0.010X1- 0.011X2 + 0.049X4 + 0.028X6 + 0.019X7 + 0.056X8 + 0.465X9. Based on the analyses we suggest that future Eruca improvement should focus first on siliqua number per plant, then seeds per siliqua, 1000-seed weight, siliqua number of main raceme, number of secondary branches and plant height, but the negative correlations between 1000-seed weight and seeds per siliqua, 1000-seed weight and siliqua number per plant, siliqua number of main raceme and number of secondary branches should also be considered. The Eruca materials with higher plant, lower branching height, larger and yellow seeds found in this study will be valuable for future Eruca improvement.

 

Key words: Eruca sativa, variation, simple and partial correlation, stepwise regression, path analysis.