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Evaluation of Promising Wheat Genotypes by the Stability Analysis Through Parametric & Non-parametric Methods

Suraiya Yasmin
Principal Scientific Officer
Bangladesh Agricultural Research Institute, Joydebpur, Gazipur, Bangladesh

Abstract/ Executive Summary:

The purpose of the present study was to compare between the application of Non Parametric Stability Analysis (NPSA) and Parametric Stability Analysis (PSA) with appropriate tests in addition to utilization of exact size -α test in solving the stability measures for heterogeneous environments. NPSA vs. PSA statistics subsist some advantages and use of non parametric statistics S₁ (1) and S₂ (2) values, together with ranks of genotypes grown in different environments can be recommend to breeders and agronomists who make selection based upon genotype x environment interaction. The wheat performance trial (AYT) was conducted with ten promising lines along with two check varieties Kanchan and Shatabdi under optimum seeding time at Dinajpur, Jamalpur, Jessore, Ishurdi and Joydebpur. The experiments were laid out in Randomized Complete Block Design during 2002-2003 with four replicates at each location under the supervision of Wheat Research Center. The yields of wheat varieties are location invariant and hence the high yielding varieties against b_i, sd_i² values. From the statistical analysis we observe that no significant differences in rank stability were found among the ten genotypes grown in five environments. Genotypes 6 (BAW-1030) , 8 (BAW-1035) and 10 (BAW-1038 ) are the most stable and well adapted to all environments due to non significant Sd_i² value, bi ≤ 1 and lower S₁ (1) values than other genotypes with mean yield ≥ grand mean. On the other hand, genotypes 4 (BAW-1028), 7 (BAW-1033) and 9 (BAW-1036) have an increasing sensitivity to environmental change and greater specificity of adaptability to high-yielding environments. However, BAW-1021 (G3) was poorly adapted genotypes to all environments and only one genotype BAW-28 (G₁) that response greater resistance to environmental fluctuation, and therefore increasing specificity of adaptability to low-yielding environments.

Keywords: Stability Statistics (parametric & non-parametric), Genotypic ranks, Heterogeneous environments, Exact size test

Location: Dinajpur, Jamalpur, Jessore, Ishurdi and Joydebpur

Start Date: 00-00-2002

End Date: 00-00-2003

Program Area: Crop-Soil-Water Management

Commodity: Wheat

Objectives:

To evaluate 10 promising wheat genotypes by NPSA over five environments and compare the results with parametric stability analysis (PSA)
To overcome limitation of the Stability Analysis by applying exact size-α tests
To compare (NPSA & PSA)’s result based on the plot by assessing visually these values how to vary rank measures vs. yield performances across five environments, and
To suggest of using stability statistics according to the nature of environment

Methodology:

The wheat performance trials were conducted with ten promising lines under optimum at Dinajpur, Jamalpur, Jessore, Ishurdi and Joydebpur along with two check varieties Kanchan and Shatabdi. The experiments were laid out in RBD during 2002-2003 with four replicates at each location and to raise the yield of crop recommended package of practices was followed. The stability analysis with 5 heterogeneous and 4 homogeneous locations were estimated. The exact size -α test were employed as test statistics to the data. Two rank stability measures were the statistic S₁⁽¹⁾ measures the mean absolute rank difference of a genotype over environments and the statistic S₂⁽²⁾gives the variance among the ranks over environments. For a genotype with maximum stability, S₁⁽¹⁾ = 0. Zero variance is indication of maximum stability. If one adjusts the uncorrected yield data by genotypic effects; i.e. using the corrected values, then non parametric measures S₁⁽¹⁾ and S₂⁽²⁾ are nearly perfectly correlated between each other. The genotype with the highest yield was given a rank of 10 and a genotype with the lowest yield was assigned a rank of 1. Genwin42 & MS Excel soft wares was used to perform analysis of NPSA & PSA on the mean values of yield (kg ha^-1) obtained over environments. RANK of MS Excel was ranked genotypes based on means of genotypes within environment. Rank measures and means of yield were used to depict plot by this software. Parametric stability analysis: Stability parameters were calculated for all environments using the model. The model was applied on yield trials with the following three hypothesis: The significance of the differences among variety means, The hypothesis that there are no genetic differences among varieties for their regression on the environmental index, The hypothesis that any regression coefficient does not differ from unity. Exact size α test for treatment effects: The combined test for testing the equality of the treatment effects with Exact size α in series of trials of RCBD with one observation per cell was performed. Non parametric stability analysis was performed. Test statistics for Z values of two non parametric stability measures were performed.

Source of Information: Int. J. Sustain. Crop Prod. 2(3): 9-16, 2007

Article Link (Online Journal):

Funding Source:

1. Government

Budget:

Total Budget (Tk.) :

Achievement/Findings:

The exact size-α test may be recommended to solve the heterogeneity problem of locations and help in interpretation of selecting better genotypes to release a new hybrid variety of any crop. Non-parametric measures for stability based on ranks provide a useful alternative to parametric measures currently used which are based on absolute data. Moreover, non-parametric vs. parametric stability statistics exist some advantages. As a consequence, for an estimation of the non parametric stability Evaluation of Promising Wheat Genotypes by the Stability Analysis through Parametric and Non-Parametric Methods statistics of genotypes grown in different environments, use of non parametric statistics S₁⁽¹⁾ and S₂⁽²⁾values, together with ranks, can be recommend to breeders and agronomists who make selection based upon genotype x environment interaction. In addition, plots provided by mean yield (kg ha^-1) against S₁⁽¹⁾ and mean yield (kg ha^-1)against S₂⁽²⁾values are likely to enhance visual efficiency of selection and similar conclusion was drawn in Bread wheat (Triticum aestivum L.).

Knowledge Management: Journal