Optimal method of transforming observables into relative values for multi-environment trials in maize

Zhe Liu, Jianyu Yang, Shaoming Li, Hu Wang, Lin Li, Xiaodong Zhang, Dehai Zhu

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Relative evaluation is commonly used in multi-environment trials of crop varieties. Five methods of transforming observables into relative values were proposed, and the corresponding relative values were measured by the new index standard deviation ratio to find the optimal one. Then, 5 relative values and standard deviation ratios were calculated using 8-year maize variety regional trial data of China. The results show that: the 5 relative values transformation methods can be applied to various traits, and relative values were informative and understandable, and moreover making weighted multi-traits and graphic analysis much easier. The new index standard deviation ratio can directly response the closeness of each relative value to the genetic characteristic, and can be used to measure these relative values transformation methods. For most traits, the optimal methods of transforming observables into relative values were: 3S and 2S value compared to the sample mean value (short for A) > standard order value (C) > the imitated NDVI value compared to the sample mean value (D) > the imitated NDVI value compared to the check variety (E) > 3S and 2S value compared to the check variety (B) > observables (F). 3S and 2S value compared to the sample mean value, which is closest to the genetic characteristic, can be used as the main method of transforming observables into relative values for multi-environment trials in maize.

Original languageEnglish (US)
Pages (from-to)205-209
Number of pages5
JournalNongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
Volume27
Issue number7
DOIs
StatePublished - Jul 1 2011

Keywords

  • Maize variety
  • Multi-environment tests
  • Relative transformations
  • Sample mean value
  • Standard deviation ratio

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