Comparative Study of AMMI- and BLUP-Based Simultaneous Selection for Grain Yield and Stability of Finger Millet [Eleusine coracana (L.) Gaertn.] Genotypes

Abstract

Finger millet, an orphan crop, possesses immense potential in mitigating climate change and could offer threefold security in terms of food, fodder, and nutrition. It is mostly cultivated as a subsistence crop in the marginal areas of plains and hills. Considering the changes in climate inclusive of recurrent weather vagaries witnessed every year, it is crucial to select stable, high-yielding, area-specific, finger millet cultivars. Sixty finger millet varieties released across the country were evaluated over six consecutive rainy seasons from 2011 to 2016 at the Agricultural Research Station, Vizianagaram. The genotype × environment interaction (GEI) was found to be significant in the combined ANOVA. Furthermore, the Additive Main effects and Multiplicative Interaction (AMMI) analysis asserted that genotypes and the GEI effects accounted for approximately 89% of the total variation. Strong positive associations were observed in an estimated set of eleven stability parameters which were chosen to identify stable genotypes. Furthermore, Non-parametric and Parametric Simultaneous Selection indices (NP-SSI and P-SSI) were calculated utilizing AMMI-based stability parameter (ASTAB), modified AMMI stability value (MASV), and Modified AMMI Stability Index (MASI) to identify stable high yielders. Both methods had inherent difficulties in ranking genotypes for SSI. To overcome this, the initial culling [i.e., SSI with culling strategy (C-SSI)] of genotypes was introduced for stability. In the C-SSI method, the top ten genotypes were above-average yielders, while those with below-average yield were observed in NP-SSI and P-SSI methods. Similarly, the estimation of best linear unbiased prediction (BLUP)-based simultaneous selections, such as harmonic mean of genotypic values (HMGV), relative performance of genotypic values (RPGV), and harmonic mean of relative performance of genotypic values (HMRPGV), revealed that none of the top ten entries had below-average yield. The study has proven that C-SSI and BLUP-based methods were equally worthy in the selection of high-yielding genotypes with stable performance. However, the C-SSI approach could be the best method to ensure that genotypes with a considerable amount of stability are selected. The multi-year trial SSI revealed that entries Indaf-9, Sri Chaitanya, PR-202, and A-404; and VL324 and VL146 were ascertained to be the most stable high-yielding genotypes among medium-to-late and early maturity groups, respectively.

Stability Indices to Deciphering the Genotype-by-Environment Interaction (GEI) Effect: An Applicable Review for Use in Plant Breeding Programs

“…Furthermore, they were able to predict the genetic gain and accrue estimations of performance using the BLUP model. In a comparative study, Anuradha et al [ 71 ] used a set of AMMI- and BLUP-based stability statistics to select stable and high-yielding finger millet genotypes. Based on the obtained results, they stated that several statistics, such as ASV, ASTAB, AVAMGE, D A , Dz, EV, and FA, proved that all have equal potential in the identification of stable genotypes.…”

Genotype X Environment Interactions of Fodder Barley Genotypes as Estimated by Ammi, Blup and Non Parametric Measures

“…However, the composite non parametric measures were also suggested to utilize the ranks of genotypes as per yield and corrected yield in number of environments as NP i (1) , NP i (2) , NP i (3) and NP i (4) . In the formulas, r*ij was the rank of X* ij , and r i ̅ and M di were the mean and median ranks for original (unadjusted) grain yield, where (r i ̅ * and M* di were the same parameters computed from the corrected (adjusted) data.…”

“…1 Adaptability and stability of various crops under multi-environment field trials studied by number of analytic measures as observed in the literature. 2 Moreover non parametric measures to assess GxE interaction and stability analysis had been also reflected. 6 The components of analysis of variance, the regression models, non-parametric methods, AMMI methods, BLUP based mixed models would be most suitable analytic methods.…”

“…The stability and adaptability of genotypes were also highlighted by the harmonic mean of genotypic values (HMGV), relative performance of genotypic values (RPGV), and harmonic mean of relative performance of genotypic values (HMRPGV). 5 Besides that nonparametric measures S i 1 , S i 2 , S i 3 , S i 4 , S i 5 ,S i 6 , S i 7 , NP i (1) , NP i (2) , NP i (3) , NP i (4) have been also utilized for genotypes x environmental conditions. 6 All recent analytic measures have been compared to decipher the Gx E interactions effects for fodder barley genotypes evaluated in northern hills zone of the country.…”

Grain Yield of Dual-Purpose Barley Genotypes Estimated by AMMI, BLUP and Non-Parametric measures after One Cut

“…The regeneration ability of barley can be put to use by taking one cutting during the active vegetative growth stage and then leaving the regenerated crop for grain production. Genotype x environment have been estimated under multi-environment trials before the recommendations for wide scale cultivation (Ahakpaz et al, 2021;Anuradha et al, 2022) , NP (3) , NP i (4) had been utilized to interpret the genotypes x environmental conditions (Pour-Aboughadareh et al, 2019). Analytic measures have been compared to estimate the GxE interactions effects of dual purpose barley genotypes after taking one cut for fodder in northern hills zone of the country.…”