Evaluation of heritability, genetic advance, correlation and genetic components of variance in Pigeonpea

Introduction

Pigeonpea [Cajanus cajan (L.) Millsp], (2n=2x=22) also known as arhar, tur and red gram, is nutritionally balanced and an exceptional source of protein in both green pea and dried grain (Faris and Singh, 1990) [8] . Along with protein, pigeonpea also renders carbohydrates and Vitamin A and C (Faris et al. 1987) [9] . Pigeonpea seeds are rich in proteins (generally within a range of 18 to 25% and as high as 32%), carbohydrates (57.6%), fiber (1.5%), minerals (3.5%), amino acids, methionine and cystine (Birk, 1993) [4] . Because of its rich source of protein, it is an ultimate addition to traditional cereal, banana or tuber-based diets of poor farmers that are protein deficient. Its ability to produce economic yield under limited moisture conditions makes it an important crop of dryland agriculture. Globally the area and production of pigeonpea have increased from 2.86 million ha and 1.96 million tons in 1980 to 4.36 million ha and 3.46 million tons in 2006, respectively (FAO Stat, 2008) [5] . Pigeonpea represents about 5% of world legume production and more than 70% is being produced in India. Pigeonpea is the second most important pulse crop of India which accounts for 20% of the total pulse production in India. In India, pigeonpea is grown in an area around 4.04 million hectares with a production of approximately 2.65 million tons (Anonymous, 2012) [2] . It has registered a production of 4.02 million tons in the year 2017-18 (All India Coordinated Research Project on Pigeonpea, Annual Report 2017-18). As 'dal', pigeonpea is an important constituent of the Indian meal. Of the total pigeonpea production in the world, India alone contributes nearly 92 per cent of it.

In India average productivity of pigeonpea is lower (671 kg/ha) compared to the world average productivity (742 kg/ha) even though it leads the world in area and production (FAOSTAT, 2010) [7] . Production of pigeonpea in India is still short which cannot fulfil the present consumption of ~19 million tonnes thereby compelling to import pulses to a range of 1.5-2.0 million tons annually (https://www.agricoop.nic.in, accessed on Feb. 28, 2013). WHO recommendation of per capita availability of protein is 80 g/day, while it is only 28 g/day in India which does the ultimate problem of the malnutrition exist among the poor people. The chasm between per capita availability of protein in India and WHO recommendation can be bridged through pulses, which are a rich source of protein.

The importance of pulses in Indian agriculture cannot be denied. Of the total pulses, red gram or pigeonpea takes an important place among rainfed resource poor farmers as it provides quality food, fertilizer, fuel wood and fodder. Despite its immense importance in sustainable agriculture its global production per hectare has remained static over the last three decades. Lack of efficient management practices coupled with biotic and abiotic stresses has widened the gap between the potential yield and onfarm yield. The conventional breeding procedures followed in pigeon pea brought improvement in seed yield and resistance to diseases and pests. However, for further boost in productivity, the possibility of producing pigeon pea hybrids and identification of superior hybrids through line x tester mating design open up new avenues. In a breeding programme, the most important steps are the selection of suitable genotypes as parents for hybridization. Selection of parents on the basis of phenotype is not a sound procedure since phenotypically superior line may yield poor recombinants in the segregating generation. Therefore, selection of parents on the basis of their genetic values is necessary. Generally, parents are chosen on the basis of gene action involved in the expression of quantitative characters. Genetic variation among genotypes and relation between major yield contributing traits are of great vital importance in the breeding programme that aims to produce improved genotype. Yield is a complex character, which is the product of interaction of many traits. Therefore, it is necessary to have the knowledge of the contribution of different characters towards yield through correlation. Basic information of the nature and extent of interrelationships between yield and its attributes will be of great utility for the choice of characters in the selection programme. Utilization of the cross as commercial hybrid is possible if the specific cross has high heterosis and the observations made are true for an economic character like yield, provided there exist cytoplasmic genetic male sterility and fertility restoration system. Analysis of combining ability is considered as the most potent tool for identifying the suitable parents for a hybridization programme. Selection of parents with high general combining ability (GCA) effect and cross combinations with high specific combining ability (SCA) is necessary for heterosis breeding. Therefore, the present investigation was undertaken to study the combining ability of parents and cross combinations as well as to evaluate the nature and magnitude of heterosis for green pod yield and its components. Pigeon pea is an often-cross pollinated crop and therefore, amenable to genetic improvement by following breeding methods suitable for both allogamous and autogamous crops. Understanding the nature and magnitude of genetic variance implies an appropriate breeding procedure for isolation of a suitable genotype that has maximum useful alleles.

Materials and Methods

The experiment entitled "Combining ability analysis for vegetable yield and its components in pigeonpea [Cajanus cajan (L.) Millsp Where, K = selection differential at 5% selection intensity, the value is 2.06 σ p = phenotypic standard deviation

heritability in broad sense

The genetic advance was expressed as% of the mean to facilitate the comparison between different characters under study.

Correlation studies

The correlation coefficient at phenotypic, genotypic and environmental levels was determined according to the formula given.

Genotypic correlation coefficient between character x and y rgxy = Where, 'F' is the coefficient of inbreeding.

In the present study, F was assumed as zero.

Results and Discussion

Essential steps in transmitting traits include selecting the correct parents and employing the appropriate breeding methods. The parents selected for the crossover procedure were evaluated based on how well their genes functioned to produce superior hybrids. An explanation of the outcomes for several field qualities is given below The estimates of coefficient of variation, heritability and genetic advance for yield and yield related traits are given in Table 1. Akram, S., Hussian, B. M. N., Bari, Md, A., Burrit. D. J and Hossain, M.A. 2016 [1] , Khan, R., Farhatullah and Khan, H. 2011 [12] & Kingshlin, M., Subbaraman, N, and Vanniarajan, C. 1999 [13] . The highest genotypic coefficient of variation (GCV) was observed for number of pods/plant (43.10%) followed by secondary branches (38.87%). However, days to flowering (1.88%), 100 grain weight (3.71%) and number of pods/ cluster (4.49%) exhibited the lowest genotypic coefficient of variation. The highest phenotypic coefficient of variation (PCV) was observed for green pod yield (64.94%) followed by number of pods/ plant (46.03%) and secondary branches (41.46%). However, days to 50% flowering (2.16%), 100 grain weight (11.49%) and number of seeds/pod (13.17%) exhibited the lowest phenotypic coefficient of variation. High heritability estimates were observed for number of pods/plant (88.00%), secondary branches (87.86%), primary branches (76.41%) and days to 50% flowering (75.29%) whereas lowest heritability estimates were exhibited by number of pods/cluster (2.00%). The genetic advance as%age of mean was highest for number of pods/plant (83.12%) followed by secondary branches (75.04%). The phenotypic and genotypic correlation coefficient for yield and its components are presented in Table 4.4. Primary branches and plant height had a positive phenotypic correlation coefficient (0.62) with each other. Also, secondary branches and primary branches had a positive association (0.75) with each other. Significant and positive phenotypic correlation coefficient association was observed between pods/ plant and primary branches (0.72). Pods/plant exhibited positive and significant phenotypic correlation coefficient with secondary branches (0.70). Arshad, M., Bakhsh, A., Zubiar, M. And Abudul Ghafoor. 2003 [3] , Fisher, R.A. 1918 [10] & Gupta, S.K; Kaur, A.; Singh, Kuldip and Singh, D. 2003 [11] . Table 2 Genetic components of variance in intervarietal crosses of pigeonpea are presented in Table 4.9. Among the characters studied, sca variance (σ 2 s) and non -additive (σ 2 D) variance components were higher than genetic variance (σ 2 g) and additive (σ 2 A) variance for all the characters under study except for pods per cluster and seeds per pod where additive component of gene action (σ 2 A) was higher than non-additive variance (σ 2 D). Kumara, B.N., Santoshagowda, G.B., Nishanth, G.K. and Dharmaraj, P.S. 2013 [14] , Meena, B.L., Das, S.P., Meena, S.K., Kumari, R., Devi, A.G. and Devi., H.L. 2017 [15] & Sreelakshmi, C., Kumar, C.V.S. and Shivani, D. 2010 [16] .

Conclusion

The present experimental study revealed that secondary branches, number of pods/plant and primary branches showed high heritability along with high genetic advance as percent of mean manifesting that the selection for these traits is likely to accumulate more additive genes leading to further improvement of their performance, primary branches and plant height had a positive phenotypic correlation coefficient with each other. Also, secondary branches and primary branches had a positive association with each other. Significant and positive phenotypic correlation coefficient was observed between pods/plant and primary branches. Pod/plant exhibited positive and significant phenotypic correlation coefficient with secondary branches and the major role of non-additive component was evident for plant height, days to 50% flowering, primary branches, secondary branches, number of pods / plants, 100 seed weight and green pod yield / plant; as the magnitude estimated dominance (σ 2 D) component of variance was higher than that of the additive (σ 2 A) component of variance. For the character number of pods per cluster and number of seeds per pod, equal importance of additive and non-additive components was observed.

The author's input

Each of the aforementioned authors has contributed significantly both directly and intellectually, and they have all approved the work's publication.

Funding None

Available data

The datasets used and/or examined in this investigation are available upon reasonable request from the corresponding author.

Statement of ethics

The work was approved by the Department of Genetics and Plant Breeding, School of Agricultural Sciences and Rural Development, Nagaland University, Medziphema campus

Informed agreement

The subjects provided written informed consent prior to being enrolled in the study.

References

1. Akram S, Hussian BMN, Bari MA, Burrit DJ, Hossain MA. Genetic variability and association analysis of soybean (Glycine max (L.) Merrill) for yield and yield attributing traits. Plant Gene and Trait. 2016;7(13):1-11.
2. Anonymous. Directorate of Economics and Statistics, Ministry of Agriculture, Govt of India, New Delhi. 2012.
3. Arshad M, Bakhsh A, Zubiar M, Abdul Ghafoor. Genetic variability and correlation studies in chickpea. Pakistan Journal of Botany. 2003;35(4):605-611.
4. Birk Y. Anti-nutritional factors (ANFs) in lupin and other legume seeds: Pros and cons. In: Martins M, da Costa J, editors. Advances in lupin research. Proceedings of the 7th Lupin Conference, Evora, Portugal, 18-23 April 1993. p. 424-429. www.hort.purdue.edu.
5. FAO. FAOSTAT. 2008. http://faostat.fao.org/
6. FAO. FAOSTAT. 2009. http://faostat.fao.org
7. FAOStat. Online agricultural statistics. 2010. http://www.faostat.org
8. Faris DG, Singh U. Pigeonpea: Nutrition and Products. In: Nene YL, Hall SD, Shiela VK, editors. The Pigeonpea. Patancheru: ICRISAT; 1990. p. 401-433.
9. Faris DG, Saxena KB, Mazumdar S, Singh U. Vegetable Pigeonpea: A promising Crop for India. Patancheru: ICRISAT; 1987. p. 3.
10. Fisher RA. The correlation among relatives on the supposition of Mendelian Inheritance. Trans Royal Soc Edinberg. 1918;52:399-433.
11. Gupta SK, Kaur A, Singh K, Singh D. Correlation among yield and yield attributes in F3 population of chickpea. Abstracts of the National Symposium on Pulses for Crop Diversification and Natural Resource Management, 20-22 December 2003, IIPR Kanpur. 2003. p. 46.
12. Khan R, Farhatullah, Khan H. Dissection of genetic variability and heritability estimates of chickpea germplasm for various morphological markers and quantitative traits. Sarhad Journal Agriculture. 2011;27(1).
13. Kingshlin M, Subbaraman N, Vanniarajan C. Estimation of heritability and genetic advance in the full-sib progenies of pigeonpea. Crop Research. 1999;14(2):303-306.
14. Meena BL, Das SP, Meena SK, Kumari R, Devi AG, Devi HL. Assessment of GCV, PCV, heritability and genetic advance for yield and its components in field pea (Pisum sativum L.). Int J Curr Microbiol Appl Sci. 2017;6(5):10251033.
15. Sreelakshmi C, Kumar CVS, Shivani D. Genetic analysis of yield and its component traits in drought tolerant genotypes of pigeonpea [Cajanus cajan (L.) Millsp.]. Electron J Plant Breed. 2010;1(6):1488-1491.