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Full Research Article

Exploring the Correlated Response and Cause-effect Relationship for Yield and its Attributing Traits in Fieldpea (Pisum sativum L.) 

Amit1, Rajesh Yadav1, Ravika1,*, Deepak Kaushik1, Kavita1, Kalpana Yadav1, Navreet Kaur Rai1
1Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar-125 004, Haryana, India.

ABSTRACT

Background: Fieldpea (Pisum sativum L.) oldest cultivated, most important nutritious food legume of the world and a major pulse crop of winter season. The present investigation was carried out to access variability, correlation and path coefficients for better understanding of genetic architecture of seed yield and its attributes in fieldpea.

Methods: Twelve parents (9 lines+3 testers) of fieldpea were crossed in Lx T mating design and the parents along with their 27 hybrids were grown in randomized block design with three number of replication during rabi 2020-21.

Result: Narrow differences between PCV and GCV of different traits implying apparent variability present among genotypes not only due to genetic factor but also environment play a crucial role in expression of these traits. Low heritability coupled with low genetic advance were observed for most of traits expect days to maturity, height of first pod and plant height suggesting that these traits are genetically controlled by non-additive gene action and heterosis breeding would be rewarding for these traits. Seed yield had positive and significant correlation with almost all the traits except days to 50% flowering, days to maturity and number of seeds pod-1. Biological yield plant-1 revealed highest positive direct effect on seed yield plant-1 followed by number of primary and secondary branches plant-1and number of pods plant-1.

INTRODUCTION

Fieldpea (Pisum sativum L.) is a diploid (2n=2x =14), major pulse crop belong to family Leguminosae; subfamily papilionoideae and tribe Fabeae. It is most important food legume crop of rabi season widely cultivated in temperate zone of more than 85 countries (Pandey et al., 2021). It is said to be native of Near East and one of the oldest domesticated pulse crops, appearing in the Mediterranean between 7000 and 6000 BC and persisting in current agriculture. In addition, it plays a significant part in crop rotation that breaks up the regular succession of cereals and it can be used as green fertilizer plant (Sharma et al., 2023). Its seeds carry balanced amount of all essential amino acids except, methionine and tryptophan - the sulphur containing amino acids, So, to balance the level of essential amino acids, fieldpea is used along with cereals such as wheat, rice, maize or millets However, In terms of nutritional content, it is a magnificent source of protein (21.2-32.9%) and carbohydrate (56-74%), in juxtaposition with vitamins (A, B and K), macro- and micronutrients and it plays a crucial role  in the food security of  resources poor folks (Parihar et al., 2016). Most fascinatingly, it is said that consuming it lowers the risk of developing Type 2 diabetes, reduces blood cholesterol, improves cardiovascular health and cancer-combating, helps regulate body weight and enhances gastrointestinal function. It is highly adaptable and can flourish in a wide variety of habitats and environments, therefore, it is grown in most regions of the world and provides a staple source of dietary protein and energy for a significant proportion of the population (Amarakoon et al., 2012).
       
India occupies sixth place in fieldpea production with an area of 6.4 lac hectares, production 8.8 lac tons and productivity of 1375 kg/ha in 2020-21 (FAO, 2022). Uttar Pradesh, Madhya Pradesh, Jharkhand, Odisha, Manipur, Assam, Bihar, West Bengal, Chhattisgarh and Rajasthan are the major fieldpea growing states in India. Unfortunately, the productivity of fieldpea is very low in India as compared to the world’s productivity due to the narrow genetic base and use of limited variability to improve the local varieties (Askander and Osman, 2018). There is urgent need to increase the seed yield though yield is a multiplex trait that depends upon a number of other contributing traits and their association (Singh et al., 2005). Thus, information regarding genetic associations between yield and its attributes will help in determining the selection criteria and identification of desirable secondary traits to improve yield, thus enhancing scope of success of breeding programs (Evans and Fischer, 1999). Furthermore, as for two traits, correlation doesn’t exist among them but it involves complicated pathways including many other traits also. Thus, selection for seed yield be more effective when path coefficient partitioning the relationship into direct and indirect effects, which demonstrates the relative relevance of each of the causal components (Dewey and Lu, 1959).

The success of any breeding program depends on a thorough knowledge of genetic diversity, heritability and the nature of gene action involved in the inheritance or improvement of desired traits. Knowledge about the magnitude of genetic variability present for different traits along with its heritable component is of prime importance for achieving the desired goals of any breeding programme (Subbulakshmi et al., 2018). Heritability provides the information about index of transmissibility and measures the selection value for a trait in different progenies, while genetic advance is useful in determining the actual gain anticipated under selection (Ogunniyan and Olakojo, 2014). Hence, the current investigation was undertaken to estimate the genetic variability, genetic associations and direct and indirect effects among thirty-nine genotypes of fieldpea for seed yield and its associated traits.

MATERIALS AND METHODS

The experiment comprised of nine female lines (Aman, RFP 2009-2, HFP 715, IPF 14-13, Pant P-243, IPF 14-16, Pant P-200, DDR-23, RFPG 79) were crossed with three male testers (HFP 1426, GP02/1108, HFP 1545) in line x tester mating design in three replications. The field geometry consists of plot size of a single row of 4m length with 45 x 15 cm spacing. The experiment held during rabi 2020-21 in randomized block design at Pulses Research Area, Department of Genetics and Plant Breeding, CCS, Haryana Agricultural University. The experimental field is located at latitude of 29°10' North, longitude of 75° 46' East and at an altitude of 215.2 meter above mean sea level.  The tract of research station (Hisar) is characterized by sub-tropical and semi-arid climate with mean maximum temperature ranging between 35 to 43°C in summers and mean minimum temperature ranging between 4-7°C in winters. The mean annual rainfall is around 455 mm which is largely received from South-West monsoon during July to September and scanty showers during the spring. The parents along with their crosses were evaluated on the basis of thirteen quantitative traits viz., days to flowering and maturity number of primary and secondary branches plant-1, nodes plant-1, plant height of 1st pod, plant height, pods plant-1, seeds pod-1, 100-seed weight, biological, seed yield and harvest index.  The genetic variability parameters i.e. genotypic coefficients of variation (GCV) and phenotypic coefficients of variation (PCV) were calculated as per Burton and de Vane (1953). Heritability in narrow sense for each character was calculated according to Singh and Chaudhary (1985), whereas expected genetic advance was calculated at 5 per cent selection intensity for each character as per Johnson et al., (1955). Data were analyzed using statistical software R studio version 2023.06.2+561.

RESULTS AND DISCUSSION

Mean performance of parents and F1g hybrids
 
Mean performance of the F1 hybrids and parent genotypes for seed yield and its attributes are shown by boxplot distribution in Fig 1. Seed yield plant-1 varied significantly between genotypes ranging from 5.70 g to 24.77 g. Out of 39 genotypes, 23 genotypes (22 crosses and 1 parent) exhibited above mean seed yield (13.97). The highest seed yield plant-1 was found in Aman x GP02/1108 (24.77g) followed by IPF 14-16 x GP02/1108 (18.84 g), IPF 14-16 x HFP 1426 (18.39 g) and Aman x HFP 1545 (18.23 g) and lowest in genotype GP02/1108. It was also observed that these genotypes proportionately exhibited above average mean performance for almost all the traits. Likewise lowest yielding parents and crosses viz., GP02/1108, HFP 715, RFP 2009-02 x HFP 1426 and HFP715 x HFP 1426, respectively showed low value for most of traits. These results indicated that there is a plenty of variation among these genotypes for almost all traits and selection would be effective among these genotypes. Significant variability was also observed in previous studies of Singh et al. (2018) and Yang et al., (2022) in fieldpea and Manjunath et al., (2023) in garden pea for seed yield and its attributes.

Fig 1: Boxplot distribution of mean performance of different 13 morphological traits in fieldpea.


 
Genetic variability analysis
 
The overall magnitude of PCV was observed higher than that of GCV almost all the traits implying a significant role of environment in expression of these traits as shown in Fig 2a,b. The phenotypic and genotypic coefficients of variation were grouped in three categories i.e., low (less than 10%), moderate (between 10 to 20) and high (greater than 20%) as suggested by Deshmukh et al., (1986). Likewise, similar results were observed by Pratap et al., (2021), Jagadeesh et al., (2023) and Pratap et al., (2021) in fieldpea and Sharma et al., (2023) in gardenpea.
       
Heritability (H2ns) represents the genetic strength of the traits and indicates the efficiency of selection, whereas genetic advance in percentage (expected) of mean (GAM) serve as indicator of efficacious and systematic progress of selection. Genetic advance as per cent mean was grouped in three categories as described by Johnson et al., (1955) i.e., low (0-10%), moderate (10-20%) and high (above 20%). According to Johnson et al., (1955), the degree of additive gene effects has a direct correlation with the narrow sense heritability and expected genetic advance as percentage of mean. Therefore, simple selection would be effective for all traits with high heritability. The heritability and GAM in the present investigation varied from 0.16% to 82.92% and 0.05% to 16.88%, respectively as shown in Fig 2c,d. Low magnitude of H2nscoupled with low GAM indicating pre-dominance of non-additive gene action and hence heterosis breeding would be rewarding for their genetic improvement whereas, moderate H2ns along with low GAM were observed for days to maturity and height of first pod while plant height exhibited high heritability with moderate GAM indicating that these characters might be governed by non-additive gene action and high heritability might be exhibited due to favourable influence of environment.  Similar studies on heritability and genetic advance in fieldpea made by Singh et al., (2017) Pratap et al., (2021), Jagadeesh et al., (2023) and Pratap et al., (2021) were in partial agreement with our findings.

Fig 2: Graphical representation of genotypic and phenotypic coefficient of variation (GCV and PCV), heritability (narrow sense) and genetic advance as percent of mean (GAM).


 
Association among yield contributing traits
 
For initiating an effective breeding programme, a priori knowledge of inter-trait correlation among the traits is must. The inter-relationship among quantitative traits was analyzed using Pearson’s product-moment correlation. Critical perusal of scatter plot (Fig 3) represents the correlations coefficient between the traits and it was observed that most of the examined traits had significant phenotypic correlations. There was concurrence between these correlations; although in some cases differences were prominent which indicated a crucial role of environment in expression of these parameters. In the present investigation number of secondary branches plant-1, number of primary branches plant-1, height of 1st pod, plant height, number of pods plant-1, biological yield plant 1 and harvest index showed positive significant association with seed yield plant-1. Therefore, selection for these positively associated traits could increase yield by a significant proportion.

Fig 3: Scatter plot diagram representing correlation between different 13 morphological traits in fieldpea.


       
In the present study, path coefficient analysis (Table 1) revealed that highest positive direct effect on seed yield was exhibited by biological yield plant-1 (0.739) followed by plant height (0.427), harvest index (0.353), number of secondary branches plant-1 (0.174), number of seeds pod-1 (0.137), number of nodes plant-1 (0.086), 100-seed weight (0.084), number of primary branches plant-1 (0.079) and days to 50% flowering (0.058).

Table 1: Direct (diagonal) and indirect effects of different characters on seed yield in fieldpea.


       
However, day maturity (0.03), height of 1st pod (0.336) and number of pods plant-1 (0.180) had negative direct effect on seed yield plant-1. Days to 50% flowering, days to maturity, number of primary branches plant-1, number of secondary branches plant-1, number of nodes plant-1, plant height of 1st pod, plant height, pods plant-1, 100-seed weight contributed direct effects towards seed yield plant-1 through biological yield per plot. The correlation and path studies of Singh et al., (2017), Panwar et al., (2023) and Pratap et al., (2021) in fieldpea also corroborate our findings.

CONCLUSION

The understanding of variability present among the genotypes of a crop species is of utmost importance for their genetic improvement to produce high yielding cultivars. Thus we investigated 39 genotypes for 13 quantitative traits to examine the genetic variability present, phenotypic and genotypic associations and various traits contributing directly or indirectly to yield in fieldpea. High magnitude of PCV and GCV was observed for number of secondary branches plant-1 followed by plant height, height of 1stpod, seed yield plant-1, biological yield plant-1 and number of pods plant-1 implied that adequate variability is present for almost all the traits. It is evident from association analysis that all the quantitative traits were positively correlated with seed yield plant-1. All the characters observed for direct and indirect effects revealed that a few traits such as biological yield plant-1, plant height, harvest index, number of secondary branches plant-1 and number of seeds pod-1 played a dominant role and hence demand greater attention when creating selection indices for improving seed yield plant-1 since they not only exhibited strong positive direct effects on seed yield plant-1  but also had substantial and positive indirect effects on the other traits through biological yield plant-1.

ACKNOWLEDGEMENT

The authors gratefully acknowledge Chaudhary Charan Singh Haryana Agricultural University, Hisar, India, for providing all field facilities for conducting this study. The authors acknowledge the station managers and technical staff of the Pulses Section, Department of Genetics and Plant Breeding, CCS HAU, for technical assistance and overall support.
 
Author contributions
 
Rajesh Yadav, Ravika and Amit conceived and planned this study. Amit and Kavita collected the literature and tabulated the data. Kavita, D.K. and Navreet Kaur, Ravika edited and finalized the manuscript. All authors have read and agreed to the published version of the manuscript.
 
Funding
 
This research received no external funding.
 
Data availability statement
 
All the data associated with the manuscript is mentioned in the text of the manuscript.

CONFLICT OF INTEREST

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

REFERENCES


  1. Amarakoon, D., McPhee, K. and Thavarajah, P. (2012). Iron-, zinc- and magnesium-rich field peas (Pisum sativum L.) with naturally low phytic acid: A potential food-based solution to global micronutrient malnutrition. Journal of Food Composition and Analysis. 27(1): 8-13. 

  2. Askander, H.S. and Osman, K.F. (2018). Heterosis and combining ability effects for some traits of pea (Pisum sativum L.). Mesopotamia Journal of Agriculture. 46(4): 435-450.

  3. Burton, G.W. and De Vane, D.E. (1953). Estimating heritability in tall fescue (Festuca arundinacea) from replicated clonal material. Agronomy Journal. 45: 478-481.

  4. Deshmukh, S.N., Basu, M.S. and Reddy, P.S. (1986). Genetic variability, character association and path coefficients of quantitative traits in Virginia bunch varieties of groundnut. Indian Journal of Agricultural Science. 56: 816-821

  5. Dewey, D.R. and Lu, K. (1959). A correlation and path coefficient analysis of components of crested wheatgrass seed production. Agronomy Journal. 51(9): 515-518. 

  6. Evans, L.T. and Fischer, R.A. (1999). Yield potential: Its definition, Measurement and Significance. Crop Science. 39(6): 1544-1551.

  7. FAO (2022). Food and Agriculture Organization Statistics. https:// www.fao.org/faostat/en/#data/QCL

  8. Jagadeesh, K., Mahto, C.S. and Kumar, N. (2023). Genetic variability studies in field pea (Pisum sativum L.) for yield and associated characters. Environment Conservation Journal. 24(2): 244-249.

  9. Johnson, H.W., Robinson, H.F. and Comstock, R.E. (1955). Estimates of genetic and environmental variability in soybeans. Agronomy Journal. 47: 314-318

  10. Manjunath, B., Devaraju, Latha, G.K., Ravi, C.S. and Gowda, M.N. (2023). Heterosis and combining studies for growth, yield and quality traits in garden pea (Pisum sativum L.). Journal of Environment and Ecology. 41(3A): 1489-1496. 

  11. Ogunniyan, D.J. and Olakojo, S.A. (2014). Genetic variation, heritability, genetic advance and agronomic character association of yellow elite inbred lines of maize (Zea mays L.). Nigerian Journal of Genetics. 28(2): 24-28. 

  12. Pandey, A.K., Rubiales, D., Wang, Y., Fang, P., Sun, T., Liu, N. and Xu, P. (2021). Omics resources and omics-enabled approaches for achieving high productivity and improved quality in pea (Pisum sativum L.). Theoretical and Applied Genetics. 134: 755-776.

  13. Panwar, S., Thakur, S., Mushtaq, M. and Kumar, A. (2023). Estimation of correlation coefficient and path analysis in field pea (Pisum sativum L.). International Journal of Environment and Climate Change. 13(11): 1871-1877. 

  14. Parihar, A.K., Bohra, A. and Dixit, G.P. (2016). Nutritional Benefits of Winter Pulses with Special Emphasis on Peas and Rajmash. In: Biofortification of Food Crops. Springer. New Delhi, pp 61-71.

  15. Pratap, V., Sharma, V. and Kamaluddin, G.S. (2021). Assessment of genetic variability and relationship between different quantitative traits in field pea (Pisum sativum var. arvense) Germplasm. Legume Research. 1: 6. doi: 10.18805/LR- 4610.

  16. Sharma, A., Yadav, R., Sheoran, R., Kaushik, D., Mohanta, T.K., Sharma, K. and Kaushik, P. (2023). Estimation of heterosis and the combining ability effect for yield and its attributes in field pea (Pisum sativum L.) using PCA and GGE biplots. Horticulturae. 9(2): 256.

  17. Sharma, S., Bhushan, A., Samnotra, R.K. and Kumar, B. (2023). Genetic variability, correlation and path coefficient analysis in advanced matromorphic generations of garden pea (Pisum sativum L.). Legume Research. 1: 7. doi: 10.18805/LR-5128.

  18. Singh, B.K., Sutradhar, M., Singh, A.K. and Singh, S.K. (2017). Evaluation of genetic variability, correlation and path coefficients analysis for yield attributing traits in field pea [Pisum sativum (L.) var. arvense]. Research on Crops. 18(2): 316-321.

  19. Singh, R.K., Sudhir Pratap, S. and Singh, S.B. (2005). Correlation and path analysis in sugarcane ratoon. Sugar Tech. 7(4): 176-178.

  20. Singh, R.K. and Chaudhry, B.D. (1985). Biometrical Methods in Quantitative Genetic Analysis. Kalyani Publisher, New Dehli, India. 38-54. 

  21. Singh, S.K., Singh, V.P., Srivastava, S., Singh, A.K., Chaubey, B. K. and Srivastava, R.K. (2018). Estimation of correlation coefficient among yield and attributing traits of field pea (Pisum sativum L.). Legume Research-An International Journal. 41(1): 20-26. doi: 10.18805/LR-3449.

  22. Subbulakshmi, K., Ravikesavan, R., Babu, C. and Iyanar, K. (2018). Study of genetic variability in pearl millet [Pennisetum glaucum (L.) R. Br.] hybrids for grain yield and quality parameters. Agricultural Science Digest-A Research Journal. 38(4): 289-292. doi: 10.18805/ag.D-4822.

  23. Yang, X., Yang, J., He, Y., Zong, X., Min, G., Lian, R. and Gou, Z. (2022). Performance of different varieties of spring field pea (Pisum sativum L.) under irrigated and rainfed environments in North China. Agronomy. 12(7): 1498. 
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