Genetic Variability, Character Association, Path Analysis and Genetic Diversity in Mungbean (Vigna radiata L.) Genotypes

Introduction

Mungbean (Vigna radiata L.) is an important pulse crop grown in many parts of India. It is valued for its protein-rich seed, short duration and suitability in different cropping systems. Yield in mungbean is a complex character and is influenced by several component characters. Therefore, information on variability and association among yield and yieldrelated characters is useful for crop improvement. Genetic variability provides the basic material for selection. Genotypic coefficient of variation, phenotypic coefficient of variation, heritability and genetic advance help to understand the amount and nature of variability present in a population. Correlation analysis is useful for studying the association between characters, whereas path coefficient analysis helps to understand the direct and indirect contribution of different characters to yield. Several studies in mungbean have reported useful variability for pods plant⁻¹, branches plant⁻¹, seed weight and seed yield, and have emphasized the importance of these characters in selection. Recent mungbean studies have also used variability, correlation and path analysis together for identifying important yield components. The present investigation was therefore undertaken to study genetic variability, character association, direct and indirect effects of yield-related characters and genetic diversity among selected mungbean genotypes.

Materials and Methods

Experimental material and design

The experiment was conducted at the research farm of G H Raisoni University, Saikheda, Pandhurna, Madhya Pradesh, during the kharif season. Eight mungbean genotypes were evaluated in a randomized block design with three replications. Statistical analysis: Analysis of variance was carried out to test the significance of differences among genotypes. Genotypic and phenotypic variances, GCV, PCV, broadsense heritability and genetic advance were estimated using standard procedures. Genotypic and phenotypic correlation coefficients were calculated to determine the association among characters. Path coefficient analysis was carried out at the genotypic level following Dewey and Lu (1959). Principal component, principal coordinate and cluster analyses were used to study multivariate diversity.

Results and Discussion

Genetic variability: The analysis showed significant differences among the genotypes for the characters studied, indicating the presence of genetic variability. For all characters, phenotypic variance was slightly higher than genotypic variance. The difference between PCV and GCV was comparatively small for most traits, suggesting that environmental influence was not very large for many of the characters. The highest variability was observed for yield plant⁻¹, followed by pods plant⁻¹ and 1000-seed weight. Branches plant⁻¹ also showed comparatively high GCV and PCV. Similar trends have been reported in mungbean where yield, pods plant⁻¹ and seed weight often show higher variability than other quantitative characters.

Heritability and genetic advance: High heritability was recorded for most of the characters. High heritability together with high genetic advance as percentage of mean was observed for plant height, leaves plant⁻¹, branches plant⁻¹, pods plant⁻¹, pod length, seeds pod⁻¹, 1000-seed weight and yield plant⁻¹. This combination indicates that a considerable part of the observed variation is heritable and that selection can be useful for these characters. Pods cluster⁻¹ plant⁻¹ showed comparatively lower heritability and genetic advance than the other traits, suggesting a greater influence of environmental factors on its expression. High heritability with high genetic advance has also been reported for several yield-related traits in mungbean.

Correlation analysis: Yield plant⁻¹ showed significant positive genotypic and phenotypic correlations with leaves plant⁻¹, branches plant⁻¹, pods plant⁻¹, pods cluster⁻¹ plant⁻¹, pod length, seeds pod⁻¹ and 1000-seed weight. The genotypic correlations were generally slightly higher than the corresponding phenotypic correlations. The highest positive genotypic correlation with yield was recorded for seeds pod⁻¹ (0.878), followed by branches plant⁻¹ (0.872). These results indicate that improvement in these characters may be associated with improvement in yield. Positive associations of branches, pods and seed weight with mungbean yield have also been reported by other workers.

Path coefficient analysis: Path analysis was used to separate the correlation of each character with yield into direct and indirect effects. Seeds pod⁻¹ had the highest positive direct effect on yield (0.689). Pods plant⁻¹, leaves plant⁻¹, branches plant⁻¹ and plant height also showed positive direct effects. Pods cluster⁻¹ plant⁻¹ and pod length showed negative direct effects even though their correlations with yield were positive. This indicates that their positive association with yield was mainly due to indirect effects through other characters. The residual effect was 0.106, showing that most of the variation in yield was explained by the characters included in the analysis. The strong positive correlation and positive direct effect of seeds pod⁻¹ make it an important character for selection. Pods plant⁻¹ also showed a comparatively high positive direct effect and a significant positive correlation with yield.

Principal component analysis: Principal component analysis was used to summarize the variation among the characters. The first four principal components together accounted for 89.82% of the total variation. PC I contributed the largest share of variation (57.45%), followed by PC II (14.09%). Thus, a large proportion of the total variation was represented by the first few components. Note: the original thesis states that the first four components had eigenvalues greater than 1. The reported eigenvalues show that only PC I and PC II are greater than 1. Therefore, this statement should be corrected after checking the original PCA output before journal submission.

Genetic diversity and clustering:

The multivariate analysis indicated the presence of genetic divergence among the genotypes. The maximum reported inter-genotypic distance was between G1 and G6 (1.288), followed by G2 and G6 (1.270) and G1 and G7 (1.254). The thesis reports four clusters and gives cluster means for the quantitative characters. Cluster II recorded relatively high values for leaves plant⁻¹, branches plant⁻¹, pods plant⁻¹, pod length and 1000-seed weight. Cluster III recorded a high mean for seeds pod⁻¹ and yield plant⁻¹. An important data issue was found in the original thesis. The main experiment is described as having eight genotypes, whereas the clustering section contains references to G10, G11, G12, G13 and G14 and gives cluster sizes of 4, 2, 2 and 6. These numbers total fourteen genotypes. This cannot be reconciled from the available material, so the cluster membership should be checked against the original statistical output before the paper is submitted.

Nutrient and chlorophyll content

Variation was also recorded for potassium, phosphorus and chlorophyll content among the eight genotypes. G2 recorded the highest potassium content (2.72%) and high phosphorus content (0.11%). G2 and G7 recorded the highest chlorophyll value (0.29 mg g⁻¹) among the reported genotypes.

Conclusion

The present study showed useful genetic variation among the mungbean genotypes for yield and yield-related characters. High variability was observed for yield plant⁻¹, pods plant⁻¹ and 1000-seed weight. High heritability together with high genetic advance was observed for most of the important quantitative characters, indicating good scope for selection. Yield plant⁻¹ was positively associated with leaves plant⁻¹, branches plant⁻¹, pods plant⁻¹, pods cluster⁻¹ plant⁻¹, pod length, seeds pod⁻¹ and 1000-seed weight. Path analysis showed that seeds pod⁻¹ had the highest positive direct effect on yield, followed by pods plant⁻¹ and leaves plant⁻¹. Therefore, these traits can receive greater attention while selecting promising mungbean genotypes. The diversity analysis also indicated that the material was genetically variable, with the highest reported distance between G1 and G6. However, the cluster-analysis section of the original thesis needs verification because the reported cluster membership corresponds to fourteen genotype labels although the experiment is described as involving eight genotypes. After verification of this point, the identified divergent genotypes can be considered for further breeding work.

Acknowledgement

AcknowledgementThe author is thankful to G H Raisoni University, Saikheda, Pandhurna, Madhya Pradesh, and the concerned research and teaching staff for providing the facilities and support required for conducting the study.

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