An alternate statistical method for dealing outliers in perennial crop experiment

Authors

  • Venugopalan R ICAR-Indian Institute of Horticultural Research, Hesaraghatta Lake Post, Bengaluru - 560089, Karnataka, India
  • Reju M Kurian ICAR-Indian Institute of Horticultural Research, Hesaraghatta Lake Post, Bengaluru - 560089, Karnataka, India
  • Chaithra M ICAR-Indian Institute of Horticultural Research, Hesaraghatta Lake Post, Bengaluru - 560089, Karnataka, India
  • Sisira P ICAR-Indian Institute of Horticultural Research, Hesaraghatta Lake Post, Bengaluru - 560089, Karnataka, India

DOI:

https://doi.org/10.24154/jhs.v18i2.2172

Abstract

A statistical method based on Robust ANOVA to handle outliers induced high coefficient of variation (CV) in pooled (2011-2018) analysis of long-term Mango cv. Totapuri rootstock trail was suggested. Based on the results, it was concluded that the rootstock treatment T3: Olour (average yield over the period 2011 to 2018 as 57.21 kg/tree) as the best. Precision gained as estimated by reduction in CV (%) was in the range of 11.01 % to 78.9 %. SAS IML codes were built-in for analysis. Hence, this study calls for employing robust ANOVA approach in testing the significance of evaluated treatments in a designed perennial crop experiment with high CV that would have reduced the sensitivity of testing the significance of treatment differences otherwise.

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Published

2023-12-20

How to Cite

R, V., Reju M Kurian, M, C., & P, S. (2023). An alternate statistical method for dealing outliers in perennial crop experiment. Journal of Horticultural Sciences, 18(2). https://doi.org/10.24154/jhs.v18i2.2172

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Section

Original Research Papers

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