Diversity analysis in micro-mutant lines of greengram [Vigna radiata (L.) Wilczek] for yield and cold tolerance  

K.K. Panigrahi1 , S.C. Swain1 , A. Mohanty2 , B. Baisakh1
1. Department of Plant Breeding & Genetics
2. Department of Soil Science & Agricultural Chemistry, OUAT, Bhubaneswar, India
Author    Correspondence author
Molecular Plant Breeding, 2015, Vol. 6, No. 9   doi: 10.5376/mpb.2015.06.0009
Received: 07 Jan., 2015    Accepted: 26 Feb., 2015    Published: 09 Apr., 2015
© 2015 BioPublisher Publishing Platform
This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Preferred citation for this article:

Panigrahi et al., Diversity analysis in micro-mutant lines of greengram [Vigna radiata (L.) Wilczek] for yield and cold tolerance, Molecular Plant Breeding, 2015, Vol.6, No. 9 1-8 (doi: 10.5376/mpb.2015.06.0009)

Abstract

Thirty genotypes of greengram including 22 mutant lines, two parents and two standard varieties along with four land races were evaluated in Randomize Block Design (R.B.D.) for yield and component traits.The 30 genotypes showed high genetic divergence (D2) and tolerance to cold at 30, 40 and 10 days old seedling contributed maximum to divergence. On the basis of D2 values using Tocher’s method, the genotypes were grouped into 09 clusters. The 14 genotypes consisting of 12 mutants, one parent and one standard variety was the biggest group. Considering the inter-cluster average D2 values, cluster means for different characters including yield and character complementation in productivity traits, crosses between cluster IV and IX are expected to produce more transgressive in later generation. The Z1-Z2 scatter diagram of genotypes on basis of canonical analysis showed seven clusters almost as on basis of D2 with few exchanges.

Keywords
Divergence; Cluster; Mutant; Canonical; D2 analysis

The efficiency of isolating desirable mutant for quantitative character is low because of different in identifying micro mutants. Techniques that could provide quantitative measures of genetic divergence with regard to multiple characters induced by mutation would prove valuable in breeding. Mahalanobis’ D²-Statistics and Canonical Variate Analysis (CVA) are such multivariate measure of divergence which predicts classification of population into groups on the basis of genetic affinity or diversity with regard to several characters (Rao, 1952, 1960). The utility of D² analysis in grouping from different mutagenic treatment and the undesirable one from the yield point of view but improved in one or few agronomic characters to be utilized as parents in a hybridization programme has been emphasized. It has been demonstrated in wheat (Bhatt, 1973) that selection of parents for hybridization on the basis of D² analysis was more effective for improvement of yield than that based on other methods.

Keeping the above point in view, the present mutation breeding project in green gram was under taken for micro-mutational improvement of yield of two varieties namely Sujata and OBGG-52. The mutagenic treatment included three doses of physical mutagen i.e. gamma ray and three chemical mutagen i.e. Ethyl Methane Sulphonate (EMS), Nitroso guanidine (NG) and Malic Hydrazide (MH) and three combination of physical and chemical mutagen at the intermediate dose of such mutagens. The population was advance to M7 generation and the present study was undertaken with 22 numbers of induced mutants, 02 parents, 04 locals and 02 high yielding standard varieties of diverse geographic and genetic origin.
1 Results and Discussion
Simultaneous variation in all the 12 characters of 30 green gram genotypes were tested for assessing the nature of genetic divergence among them following Mahlanobis’ D2-statistics and canonical analysis. The data recorded were subjected to analysis of variance. The aggregate effect of all 12 character tested by Wilk’s criterion indicated highly significant difference among the genotypes (χ2 for 348 d.f.). It is therefore, worthwhile to classify the population on the basis of characters study.
D2 values for the 435 pair combinations among 30 strains ranged from 41.244 between SM1-3 and SE2-2 to 735.765 between ON3-2 and OE1-2 indicating that, while some strains were quite close to each other genetically, others are quite diverse. The genetic closeness between SM1-3 and SE2-2 was apparently due to their similarity to days to flowering, plant height, clusters per plant, pods per plant ,pod length, seeds per pod ,100-seed weight, yield per plant, Response to 10ºC temperature at 10 days, 20 days, 30 days and 40 days seedling stage. On the other hand, the higher distance between ON3-2 and OE1-2 could be attributed to the wide difference in all the characters except days to 50% flowering, pod length and seeds per pod. The D2 values of the Sujata mutants (Table 2) for all the 45 paired combinations among 10 entries ranged from 41.244 between SM1-3 and SE2-2 to 464.139 between SG1-1 and SE2-3 while genetic divergence (D2) among 66 paired of OBGG-52 varied from 42.488 between ON3-3 and OM2-3 to 710.406 between OE1-2 and OGM2-3. (Table 3).


Table 1 List of cultures/varieties with their pedigree and source of origin



Table 2 D2 values for mutant lines of parent Sujata



Table 3 D2 values for mutant lines of parent OBGG 52


The highest D2 value was observed between ON3-2 and OE1-2 which were the mutant of same parent OBGG 52 but with different mutagenic treatments (T9N3 i.e. NG 0.015 % and T4E1 i.e. EMS 0.2%). In the next order of sequence same genotype OE1-2 exhibited greater diversity with OG1M2-3. Usually, the higher genetic diversity between two genotypes is the indication of good combiners for cross ability and might ultimately yield appreciable recombinants. On the other hand the lowest diversity between SM1-3 and SE2-2 was an indicative of the reverse situation.
The magnitude of D2 values indicated considerable genetic diversity among the strains despite the fact that they constitute an elite group, all selected for high yield. At the same time, the results were in consistent with the diverse origin of the strains, majority of which originated from different mutagenic treatments. Similar results were observed by Mishra and Pradhan (2006), Momin et al. (2006) and Das and Baisakh (2011).
The relative contribution of different characters to total divergence could be accessed through comparison of total D2’s for individual characters over the 435 pair combinations. Rank totals over the paired combinations were also use as an additional criterion for assessing the relative contribution of the character. Considering the first criterion (i.e. D2 over all combinations), survival of 30 days old seedling at 10ºC, made the greatest contribution (26.968%) to divergence followed survival of 40 days old seedling at 10ºC (20.400%), survival of 10 days old seedling at 10ºC (15.655%), survival of 20 days old seedling at 10ºC (13.859%), 100-seed weight (6.120%), plant height (3.975%), pods per plant (3.682%), seeds per pod (2.396%) and yield per plant (2.348%). Rank totals brought out same pattern of relative contribution of all twelve characters judged by the first criterion. The maximum contribution to divergence was by survival of 40, 30, 20 and 10 days old seedling at 10ºC followed by 100 seed weight, plant height, pods per plant and seed yield (Table 4) which was in close agreement with the observations of Jena (2010) and Pradhan (2011).


Table 4 Relative contribution of different characters to genetic divergence among thirty culture/varieties


Thirty strains were grouped on the basis of genetic affinity / diversity as measured by D2 into nine clusters or group consisting of one to fourteen strains (Table 5). Group 1 was the largest cluster consisting of 14 strains, 12 of which were mutant cultures of different parents but with different mutagenic treatments. The varieties and the mutant cultures were from diverse origin but clustered in one group. Group II included four strains which three were local varieties except one mutant SE2-3. Group III consistent of two mutant cultures. They were of from same parent OBGG 52 but again of different mutagenic treatments. Group IV included only three strains consisting of one parent and one of it’s mutant along with one standard variety. Group V contain one mutant and one local. Whereas Group VI includes only two mutants of different parent. Other three groups have single genotype each of different parents and different mutagenic treatment. These observations showed that diverse type of genetic changes were induced by different mutagens and selection towards higher yield made them separate from the parental material.


Table 5 Composition of genetic cluster using D2 value


Similar D2 analysis and grouping of greengram genotypes into genetic clusters have been reported by Muhhamad et al. (2007), Das et al. (2010), Rahim et al. (2010), Das (2011), Gokulakrishnan et al. (2012) and Abna et al. (2012).
The inter cluster average D2’s ranged from 149.844 to 634.792 (Table 6) and average genetic distances (D’s) ranged from 12.241 to 25.195 (Table 7). Clusters I and V were least distant from each other indicating their closeness genetically. Maximum inter cluster distance was observed between III and VI. Thus, clusters III and VI were most diversed genetically. The intra cluster average D2 for the clusters containing two or more strains ranged from 55.625 to 143.421 and the average intra-cluster distance (D’s) ranged from 7.458 to 11.976 (Table 6 and Table 7). Cluster VI (2 strains) having highest average D2, was genetically most heterogeneous group followed by cluster I (14 strains), cluster V (2 Strains) and cluster II (4 strains), Cluster IV (3 Strains) and cluster III (2 strains). The rest clusters had one strains each.


Table 6 Intra and inter cluster average D2 values among clusters



Table 7 Intra and inter cluster average distance (D) = √ D2 values among clusters


The means for 12 traits of nine different clusters are given in Table 8. Yield per plant, cluster per plant, pods per plant, seeds per pod were highest for cluster IV. The survival of 20, 40 days old seedling was highest in group in IX where as Group VIII was highest with survival of 10 days old seedling at 10ºC along with lowest mean for days to flowering. Maximum pod length was observed in case of cluster II whereas maximum 100-seed weight was noticed in cluster VIII. All the other clusters were intermediate in their mean character components.


Table 8 Character means for different genetic clusters


Plant breeders often use varieties or genotypes possessing high genetic divergence in cross breeding programme with an objective of getting more transgressive segregants. The scope of getting high yielding transgressive segregants from a cross between two parents with high genetic divergence is often limited if one or both parents are moderate or low yielder. Thus, for identification of crosses for getting high yielding segregants, the parental genotypes should have high D2 value, moderate to high yield and character complementation in productivity traits. On the basis of this rational crosses between cluster IV x VII, IV x IX and IV x VI are expected to produce more transgressive, yield segregants in later generation. But these crosses are to be tested to get the final conclusion.
Canonical analysis is a multivariate analysis which is an extension of multiple regression analysis. The canonical analysis (Rao, l952) involved estimation of canonical vectors or canonical roots and the first two canonical root values (Z1 and Z2) of each genotype are taken for two dimensional presentation of genotypes in scatter diagram and the genotypes falling close to each other are taken to form a group/cluster.
Canonical analysis of the 30 greengram genotypes based on twelve characters was done and the contribution of first two canonical roots Z1 and Z2 were 32% and 22%, respectively.The genotypes are presented as scatter of points in a two dimensional graph using Z1 and Z2 values of each genotype (Figure 1). Depending on the closeness of points representing genotypes in the scatter diagram, the 30 greengram genotypes were grouped into seven clusters (Table 9).


Table 9 Composition of genetic cluster using Canonical analysis



Figure 1 Group constellations of 30 cultures or varieties (Z1 – Z2) Graph


Cluster I represented by 16 genotypes occupied the central position in the scattered diagram while cluster II occupied the position near to cluster I which includes six genotypes including three mutant culture and three local genotypes. Cluster III, IV and V also each having two genotype but almost at equidistance from cluster I which is at the center. Cluster V composed of two genotypes SG1-1 and OE1-2 which were highly cold tolerant and with satisfactory yield. Cluster VI and VII were having one genotype each and were located near to each other. Cluster VII was away from cluster I in comparison to cluster VI. The genotype of cluster VI, OM1-3 having highest cold sensitivity and very low yielding ability. The genotype of cluster VII, SG3-3 was a cold tolerant genotype with satisfactory yield level Clustering pattern on the basis of D2 Tocher’s method and canonical analysis were almost similar with few deviations. Cluster I of canonical method acquired two genotypes PDM 54, OBGG-52 from cluster IX of Tocher’s method and donated two genotypes ( SE3-2, OG3-2) to cluster II of Canonical method.
2 Materials and Methods
The present investigation on “Diversity analysis in mutant lines of greengram [Vigna radiata (L.) Wilczek] for yield and cold tolerance” was taken up in the Department of Plant Breeding and Genetics, College of Agriculture, OUAT, Bhubaneswar, Odisha, India. The field experiment was conducted at the EB-II Section during rabi season of 2011-12 and laboratory work was taken up in S.K.Sinha Molecular Breeding Laboratory of the department. The materials consisted of 30 cultures/varieties of greengram [Vigna radiata (L.) Wilczek]. Twenty two of these were induced mutants (now in M7 generation) of Sujata and OBGG-52, 02 were parents and other 06 were standard genotypes including 04 locals. The induced genetic variants were developed at OUAT. The mutants were developed through selection for higher yield than the parental material by applying selection pressure from M2 - M6. Finally, the selected cultures were tried in yield trial in present investigation. The source of the materials and their pedigree are given in Table 1.
PS- Pre-Soaking; D- Drying; kR-kilorad (unit of mutagene doses) OUAT- Orissa University of Agriculture and Technology, India; BARC- Bhaba Atomic Research Centre, Trombay, India ; IIPR- Indian Institute of Pulse Research ; MH- Maharastra.
The field experiment was laid out in a randomized block design (RBD) with 3 replications with 30 entries. The crop was shown on 25.09 2011. Each entry was represented by 3 rows of 3 m length. The intra and inter rows distances were 10 cm and 30 cm respectively. Fertilizers were applied at the rate of 20:40:20 kg of N:P2O5:K2O with 300 cubic foot of farm yard manure per hectare. All the farm yard manure (FYM) , phosphatic, potasic and half of the nitrogenous fertilizers were applied as basal dose and rest half of the nitrogenous fertilizers were applied at 21 days after sowing. Hoeing and hand weeding were done at the time of top dressing. No plant protection measure was taken as there was no incidence of diseases and insect pest.
2.1 D2 -analysis and grouping of genotypes
Genetic divergence with regard to the characters was estimated by Mahalanobis D2-statistics following Rao (1952). D2 between any two genotypes was estimated using the formula:
 
Where,    wij di dj
 
Wij is the inverse of the common dispersion matrix Wij and di and dj are the difference in the means of the two populations for ith and jth characters.
As computation by this formula is laborious, the character means were transformed into sets of uncorrelated variables. The transformation was done by pivotal condensation of the common dispersion matrix following Rao (1952). After this transformation, the formula for genetic divergence becomes:
 
All possible D2s among the cultures/varieties were computed; the relative contribution of individual characters to divergence was assessed by (a) ranking of components D2s as well as by (b) percentagecontribution to total D2 over all combinations.
(a) Rank average: In all the D2 combinations, the characters were ranked 1 to 10 on the basis of their contribution to the D2.
(b) Average D2: Average contribution of each character to all the D2 combinations is worked out.
2.2 Grouping of cultures/ genotypes into different clusters
2.21 Tocher’s method
Usually a cluster is defined as a group of population/cultures such that any two populations belonging to the same cluster should, on an average, show a smaller D2 then those belonging to two different clusters. A simple device suggested by Tocher (Rao, 1952) for construction of cluster is to start with two most closely related populations (having the smallest D2) and then find a third one which has smaller average D2 for the first two and so on. At certain stage, when it is felt that after adding a particular population, there is a disrupt increase in the average D2, this population is not added to the cluster. Similarly, construction of 2nd, 3rd and other clusters are formed till all the population are included in one or the other cluster.
Authors’ contributions
KKP and SCS carried out the overall experiment, AM prepared the manuscript. BB supervised the experiment as a Chairman advisory committee for the master degree thesis work.
References
Abna A., Golam F., Bhassu S., 2012, Estimation of genetic diversity of mungbean (Vigna radiata L.Wilczek) in Malaysian tropical environment, African Journal of Microbiology Research, 6(8): 1770-1775
Bhatt G.M., 1973, Comparison of various methods of selecting parents for hybridization in common bread wheat, Australia Journal of Agriculture Research, 24: 457-464
http://dx.doi.org/10.1071/AR9730457
Das T.R., 2011, Studies on genetic variability and improvement of greengram (Vigna radiata L. Wilczek) through induced mutation, Ph.D. Thesis, OUAT, Bhubaneswar, India
Das T.R., and Baisakh B., 2010, Frequency and spectrum of induced morphological mutations in greengram (Vigna radiata L. Wilczek). Journal of Research Orissa University of Agriculture and Technology, 28(1 & 2): 20-26
Gokulakrishnan J., Kumar B Sunil, Prakash M., 2012, Studies on Genetic Diversity in Mung Bean (Vigna radiata L.), Legume Research, 35 (1): 50-52
Jena B, 2010, Genetic architecture of yield and cold tolerance in greengram (Vigna radiata L. Wilczek), M.Sc. (Ag.) Thesis, OUAT, Bhubaneswar, India
Mishra T. K., and Pradhan B., 2006, Genetic divergence and character association in micro mutants of mungbean variety Sujata, Indian Journal of Pulses Research, 19(2): 184-186
Momin B.W, Misra R.C., and Sahu P.K., 2006, Genetic divergence among greengram mutant cultures developed by gamma-rays, EMS and NG treatments. Journal of Research Orissa University of Agriculture and Technology, 24(1&2): 21-25
Muhammad Z., Ajmal S. U., Muhammad A., and Haqqani A. M., 2007, Multivariate analysis for quantitative traits in mungbean (Vigna radiata (L.) Wilczek), Pakistan Journal of Botany, 39: 103-113
Pradhan M, 2011, Genetic architecture of yield and cold resistance in land races of greengram (Vigna radiata L. Wilczek), M.Sc. (Ag.) Thesis, OUAT, Bhubaneswar, India
Rahim M., Mia A. A., Mahmud F., Zeba N., and Afrin K. S., 2010, Genetic variability, character association and genetic divergence in mungbean (Vigna radiata (L.) Wilczek), Plant Omics Journal, 3(1): 1-6
Rao C. R., l952, Advanced statistical methods in biometric research, Edn. 1, John Wiley and Sons, New York

Rao C.R., 1960, Multivariate analysis – an indispensible statistical aid in applied research, Sankhya, 22:317-338

Molecular Plant Breeding
• Volume 6
View Options
. PDF(526KB)
. FPDF
. HTML
. Online fPDF
Associated material
. Readers' comments
Other articles by authors
pornliz suckporn porndick pornstereo . K.K. Panigrahi
. S.C. Swain
. A. Mohanty
. B. Baisakh
Related articles
. Divergence
. Cluster
. Mutant
. Canonical
. D2 analysis
Tools
. Email to a friend
. Post a comment