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Genotype-by-year interaction for grain yield of Iranian wheat cultivars and its interpretation using Vrn and Ppd functional markers and environmental covariables

Abstract

In the present study, fifty genotypes were evaluated over 5 years. The analysis of variance revealed significant interaction (P < 0.001) between genotype and year (GYI). The results of different stability statistics illustrate that the Kang’s rank-sum is a good statistic and based on that, Azadi, Roshan, Mahdavi, Marvdasht, and Naz identified as desirable cultivars. Seven environmental factors including maximum temperature, minimum temperature, average temperature, precipitation, relative humidity, daylight hours, and soil temperature over eleven twenty-day periods and sixteen molecular markers associated with vernalization and photoperiod were used as covariates to interpret the interaction. The Partial least square regression biplot with environmental covariates explained 28.23% and with genotypic covariates explained 40.24% of the GYI. The results also showed that genotypes do not respond similarly to environmental variables at different stages of development. Genotypes have been classified into three groups, the first group being more related to environmental factors at the end of the growing season, the second group being more influenced by environmental factors at the beginning of the season, and the third group being genotypes of environmental factors throughout the season, especially the mid-season was affected. Among environmental factors, relative humidity except for period 9 had a special role in GYI in all periods. On the other hand, Ppd.D1D001.KASP, Vrn.B1.B.KASP, Inter1.D.deletion, VRN.A1, Vrn.A1.E7.FT.KASP and Vrn.A1.E4.vern.KASP markers had the most impact on the GYI among the different molecular markers. This information on the causes of the GEI can be useful in future breeding and management programs.

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Correspondence to Hadi Alipour.

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Communicated by A. Mohan.

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Alipour, H., Abdi, H., Rahimi, Y. et al. Genotype-by-year interaction for grain yield of Iranian wheat cultivars and its interpretation using Vrn and Ppd functional markers and environmental covariables. CEREAL RESEARCH COMMUNICATIONS 49, 681–690 (2021). https://doi.org/10.1007/s42976-021-00130-8

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Keywords

  • Environmental and marker covariables
  • Partial least square regression
  • Stability statistics
  • Adaptability