Studies on morphological evaluation and genetic variability in Cowpea (Vigna unguiculata L. (Walp.) genotypes

Introduction

Cowpea (Vigna unguiculata L. (Walp.) is an important legume of the Fabaceae family, widely grown around the world. It is especially prevalent in Africa and Asia, where it plays a key role as a major protein source in vegetarian diets (Duraipandian et al., 2022) [11] . In addition, it shows better resilience than cereals under moisture stress and low fertility. Despite being a major producer, India faces low cowpea productivity due to the use of traditional, low-yielding varieties. Therefore, there is great scope for improving its production by developing high-yielding cultivars with desirable agronomic traits in cowpea. Progress in crop improvement largely depends on the extent of genetic variability present in a particular crop, as it provides the genes of interest for selection. The greater the genetic variability, the higher the chances of improvement in the desired direction. Considering the above points, studying the morphological evaluation of cowpea genotypes will help in selecting suitable parents for breeding programs and conserving valuable genetic resources.

Materials and Methods

The present investigation was carried out with 50 cowpea genotypes at Central Experiment Station, Wakavali, Dapoli (Ratnagiri) during Rabi 2022-23 for the estimation of genetic variability. The experiment was conducted in Randomized Block Design with two replications. Each genotype was planted at a spacing of 45 × 30 cm, with three rows of five plants each. In each replication, randomly five plants in each genotype were marked for observations. The observations were recorded on 12 quantitative traits. The data recorded were statistically analyzed as suggested by Panse and Sukhatme (1985) [24] for analysis of variance, genotypic and phenotypic coefficients of variation by Burton and De Vane (1953) [4] , heritability in the broad sense by Lush (1949) [20] and genetic advance by the formula suggested by Johnson et al. (1955) [14] . Heritability in the broad sense was categorized by the method suggested by Robinson (1966) [26] and Stansfield (1969) [31] as follows: Low: 5-10%, Moderate: 10-30%, High: 30-60%, and Very High: >60%.

Results and Discussion

The results of mean performance, range, general mean, standard error, coefficient of variance and critical difference from the statistical analysis of fifty cowpea genotypes for twelve quantitative characters are given in Table 2. The analysis of variance showed that the mean sum of squares of all the genotypes were significant for all 12 quantitative characters considered under the study (Table 3). Days to first flower initiation: Days to initiation of flowering recorded a grand mean of 59.44 days and the values ranged from 44.00 days (G48) to 99.00 days (G25). The genotype G48 (44.00 days) was found earliest in flowering followed by G 21 (46.50 days), G16 (48.5 days), G12 and G 37 (51.5 days), G-8, G19, G31, G33, G41, G44, G46, G50 (52 days) whereas G25 (99.0 days) found late in flowering initiation followed by G23 (73.0 days), G35 and G4 (71.5 days). The above results align with the findings of Lazaridi et al. (2023) [18] and Bondade and Deshapande (2021) [3] . They reported a wide variation in flower initiation, ranging from 55. 23 to 85.15 days and 43.50 to 57.00 days after sowing, respectively. In the present study, the genotypes G25, G9, G29, and G3 showed strongly indeterminate growth habit and a significantly later initiation of the first flowers (99, 71, 65.5, and 61.5 days, respectively) compared to the grand mean (59.44 days) and the control, G48 (Konkan Sadabahar) (44 days). The main genes responsible for the plant transition to flowering are TFL1 and FLOWERING LOCUS (FT) from the PEBP family which determine the flowering of the plants (Kobayashi et al., 1999) [16] . During vegetative stage the level of TFL1 expression is low and it increases upon transition to flowering (Krylova, 2020) [17] .

Days to 50% flowering: The variation for days to 50% flowering ranged from 48.50 days (G48) to 111.50 days (G25) with the grand mean of 65.44 days. The genotypes G25 (111.5 days) was found very late in days to 50% flowering followed by G23 (81.5 days), G 11 (78.5 days), G9 (78.5 days), G35 and G 4 (78.0 days). These findings are in accordance with the work of Chandrakar et al (2016) [5] , Devi et al. (2018) [9] , Jadhav et al., (2023) [13] . 50% flowering depends on the interaction of many complex processes such as both environmental and genetic factors (Jadhav et al.,2023) [13] . The earliest in this instance were the G48 (Konkan Sadabahar) and G21, which can be utilized as parents or in the breeding program to achieve even greater progress.

Days to maturity:

The character days to maturity recorded grand mean of 107.67 days. The variation ranged from 82.0 days (G33) to 141.5 days (G25). The genotype G33 (82.0 days) recorded minimum number of days to reach maturity followed by G 21 (87.0 days), G48 (Konkan Sadabahar) (89.0 days), G50 (96.5 days), G16 (97.0 days), G8 (98.0 days). The genotypes G25 (141.5 days) recorded maximum days to maturity followed by G23 (130.5 days), G 29 (124.0 days), G9 (122.0 days), G24 (121.5), G11 (120.5 days) and G 3 (119.5). The studies by Lazaridi et al. (2023) [18] and Lonare et al. (2024) [19] were also in line with the present investigation. Early maturing varieties are considered climate smart cultivars since they have the ability to escape terminal drought as well as pest and disease damage that normally occurs later in the cropping season (Mortimore et al.,1997; Song et al.,2013) [22,30] .

Plant height:

The average plant height was 74.28 cm, with a range of 29.75 cm (G 21) to 283.95 cm (G 29). Among all genotypes, G29 was the tallest, followed by G25 (273.00 cm), G9 (254.70 cm), and G3 (242.25 cm). In comparison to other genotypes, the G21 genotype (29.75 cm) was found shorter than the others followed by the G13 genotype (30.00 cm) and the G38 genotype (30.20 cm). A similar range for plant height were reported by Chandrakar et al. ( 2016) [5] , Mali et al., (2021) [21] . Reduction in plant height may be ascribed to a diminution of mitotic activity of meristematic tissues, cell length, cell number, and phytohormones (Cheng et al., 2019) [8] .

Number of Primary Branches per plant:

The average number of primary branches per plant was 3.76, with a range of 2.20 (G38) to 5.00 (G32). In contrast, G32 (5.00) recorded the highest number of primary branches per plant, followed by G24 (4.80), G49 (4.70), G8 (4.55), and G37 (4.50). These results were matching with the findings for a number of primary branches reported by Odeseye et al., (2022) [23] and Chaudhary et al. ( 2020) [6] . The decreased number of branches per plant might be due to cellular divisions at a low rate, reduced photosynthetic activities, and synthesis of growth regulators (Raina and Khan,2023) [25] .

The variation for pod length ranged between (G 21) 7.75 cm to 34.55 cm (G 25) with 15.57 cm general mean. The G25 was longest among all genotypes followed by G29 (33.35 cm), G3 (32.50 cm), G9 (31.45) and G43 (21.80 cm) whereas the genotypes G21 (7.75 cm) and G46 (9.95 cm) exhibited shortest pod length as compared to other genotypes. Simillar type of findings were recorded by Selvi et al. (2022) [28] and Lonare et al. (2024) [19] in cowpea for this character.

Number of seeds per pod:

The average number of seeds per pod was 12.04, ranging from 8.20 (G21) to 15.10 (G39). The genotype G21 (8.20) exhibited minimum number of seeds per pod followed by G18 (8.60), G22 (9.10) and G17 (9.25) while the genotype G39 (15.1) reported maximum number of seeds per pod followed by G8 (14.80), G37 (14.75), G34 (14.30). The results were in accordance with the findings of Verma et al. (2019) [33] , Selvi et al. (2022) [28] and Lonare et al. (2024) [19] . The relationship between the number of seeds per plant and yield in cowpea is generally positive and strong. [28] and Lonare et al. (2024) [19] . The productivity of cowpea can be improved through emphasis on pod and seed characteristics which are direct contributors to the economic yield either as seed yield in case of grain cowpea or pod yield for yard-long bean (Romanus et al.,2008; Ullah et al., 2011) [27,32] .

Number of pods per plant:

The range of number of pods per plant extended from 9.90 (G11) to 30.80 (G44) and average was 16.02. Among fifty genotypes G11 (9.90) recorded less number of pods per plant followed by G30 (10.10), G1 (10.50) G10 and G24 (11.30), whereas G44 (30.80) shown maximum number of pods followed by G46 (25.80), G50 (22.70) and G16 (21.9). conformity

The general mean for grain yield per plant was 18.20 g with a range from 7.70 g (G30) to 30.70 g (G4). The highest grain yield per plant was recorded by genotype G4 (30.70 g) followed by G5 (27.40 g), G 8 (27.30 g), G40 (24.80 g) while the lowest grain yield per plant was exhibited by genotype G30 (7.70 g) followed by G21 (8.70 g), G10 (10.00 g) and G27 (12.20 g). Similar type of results were recorded by Selvi et al. (2022) [28] and Lonare et al. (2024) [19] . Yield-related traits are often correlated and selection for one may lead to negative or positive response in the other traits (Ajibade and Morakinyo,2000) [1] .

The range of biological yield per plant extended from 29.7 g (G21) to 84.1 g (G4) and average was 57.60 g. The genotype G21 (29.7 g) was lowest in biological yield per plant followed by G37 (39.2 g) and G13 (42.2 g) while the genotype G4 (84.1 g) was highest in biological yield per plant followed by G25 (83.8 g), G29, G3 (83.7 g) and G9 (80.4 g). Allocation of biomass or photosynthates toward desired harvestable product could play a vital role in obtaining a good yield and determines how plant biomass is converted to seed yield (Chen et al., 2021) [7] .

The observed harvest index ranged from 13.87% (G30) to 44.54 (G8) with a grand mean of 32.05%. The genotype G8 (44.54%) exhibited highest harvest index followed by G18 (40.11%), G50 (39.96%), G16 (39.45%) and G38 (39.16%), while the genotype G30 (13.87%) showed lowest harvest index followed by G11 (18.96%), G9 (21.14%) and G28 (22.07%). Similar type of results were recorded by Selvi et al. (2022) [28] and Lonare et al. (2024) [19] . The ratio of seed yield to total dry weight defines the harvest index and signifies its capacity to allocate photosynthetic assimilates into grains (Donald and Hamblin, 1976; Sinclair, 1998) [10,29] . Genetic parameters of variation for grain yield and its component characters studied are presented in Table 4. The phenotypic coefficient of variation was higher compared to genotypic coefficient of variation except number of primary branches per plant. In the present investigation, the highest estimates of genotypic and phenotypic coefficients of variation were observed for plant height, pod length, test weight, number of pods per plant, grain yield per plant, biological yield per plant and harvest index. In contrast, the lowest estimates were recorded for the number of primary branches per plant High estimates of GCV and PCV in cowpea had been observed for seed yield per plant and harvest index by Lonare et al. (2024) [19] and Havaraddi and Deshpande (2018) [12] . While, Bhagavati et al. (2018) [2] and Khan et al. (2015) [15] recorded high estimates of GCV and PCV for the number of pod per plant. Lonare et al. 2024 [19] registered high GCV and PCV for the trait harvest index and number of pods per plant. Most of the traits included in this investigation were considerably highly heritable as they have shown to be associated with very high (> 60%) broad sense heritability. The high magnitude of heritability observed in cowpea had also been reported by Lonare et al. 2024 [19] for days to flowering, number of branch per plant, number of pods per plant, number of seeds per pod, harvest index and seed yield per plant. The quantitative traits days to first flower, days to 50% flowering, days to maturity, plant height, pod length, biological yield per plant and harvest index shown the high heritability with high genetic advance indicating additive gene action and selection is effective while the characters number of primary branches per plant, number of seeds per pod, test weight, number of pods per plant and grain yield per plant exhibited non-additive gene action and selection is ineffective.

References

1. Ajibade SR, Morakinyo JA. Heritability and correlation studies in cowpea (Vigna unguiculata (L.) Walp). Niger J Sci. 2000;15:29-33.
2. Bhagavati PP, Kiran Patro TSKK, Lakshmi Narayana Reddy M, Emmanuel N, Salomi Suneetha DR, Vara Prasad N. Studies on genetic variability, heritability and genetic advance in yardlong bean (Vigna unguiculata (L.) Walp. ssp. sesquipedalis Verdc.). Int J Chem Stud. 2018;6(4):1135-8.
3. Burton GW, De Vane EH. Estimating heritability in tall fescue (Festuca arundinacea) from replicated clonal material. Agron J. 1953;45(2):478-481.
4. Chandrakar R, Verma A, Singh J, Mehta N. Genetic divergence in vegetable cowpea (Vigna unguiculata L.). Asian J Hort. 2016;11(2):323-328.
5. Chaudhary AR, Solanki SD, Rahevar PM, Patel DA. Genetic variability, correlation and path coefficient analysis for yield and its attributing traits in cowpea (Vigna unguiculata (L.) Walp.) accessions. Int J Curr Microbiol Appl Sci. 2020;9(2):1281-93.
6. Chen J, Engbersen N, Stefan L, Schmid B, Sun H, Schöb C. Diversity increases yield but reduces harvest index in crop mixtures. Nat Plants. 2021;7(7):893-8.
7. Cheng Q, Dong L, Su T, Li T, Gan Z, Nan H. CRISPR/Cas9 mediated targeted mutagenesis of GmLHY genes alters plant height and internode length in soybean. BMC Plant Biol. 2019;19(1):562.
8. Devi SM, Jayamani P. Genetic variability, heritability, genetic advance studies in cowpea germplasm (Vigna unguiculata (L.) Walp.). Electron J Plant Breed. 2018;9(2):476-81.
9. Donald CM, Hamblin J. The biological yield and harvest index of cereals as agronomic and plant breeding criteria. Adv Agron. 1976;28:361-405.
10. Duraipandian M, Poorani KE, Abirami H, Anusha MB. Vigna unguiculata (L.) Walp: A strategic crop for nutritional security, well-being and environmental protection. Legume Res. 2022;2. doi:10.5772/intechopen.103025.
11. Havaraddi U, Deshpande SK. Genetic variability studies in advanced stabilized lines of cowpea (Vigna unguiculata (L.) Walp.). Int J Pure Appl Biosci. 2018;6(6):221-226.
12. Jadhav GG, Mahale SP, Deshmukh RN, Wankhade SG. TPI. 2023;12(12):100-102.
13. Johnson HW, Robinson HF, Comstock RE. Estimation of genetic environmental variability in soybean. Agron J. 1955;47(1):314-318.
14. Khan H, Viswanatha KP, Sowmya HC. Study of genetic variability parameters in cowpea (Vigna unguiculata (L.) Walp.) germplasm lines. Bioscan. 2015;10(2):747-750.
15. Kobayashi Y, Kaya H, Goto K, Iwabuchi M, Araki T. A pair of related genes with antagonistic roles in mediating flowering signals. Science. 1999;286(5446):1960-2.
16. Krylova EA, Khlestkina EK, Burlyaeva MO, Vishnyakova MA. Determinate growth habit of grain legumes: role in domestication and selection, genetic control. Ecol Genet. 2020;18(1):43-58.
17. Walp.)-insect pollinator interactions aiming to increase cowpea yield and define new breeding tools. Ecologies. 2023;4(1):124-40.
18. Lonare LM, Pethe UB, Kunkerkar RL, Dhopavkar RV, Kadam JJ, Palshetkar MG, et al. Genetic variability, heritability and genetic advance studies in F2 generation of cowpea (Vigna unguiculata (L.) Walp.). Int J Adv Biochem Res. 2024;8(10):1091-5.
19. Lush JL. Heritability of quantitative characters in farm animals. Hereditas. 1949;35:356-75.
20. Mali VV, Kale VS, Nagre PK, Sonkamble AM, Jadhav PV, Hadole SS. Evaluation of cowpea genotypes for growth, yield and yield attributing characters. TPI. 2021;10(5):265-8.
21. Mortimore MJ, Singh BB, Harris F, Blake SF. Cowpea in traditional cropping systems. In: Singh BB, Mohan Raj DR, Dashiell KE, Jackai LEN, editors. Advances in cowpea research. Ibadan: IITA/JIRCAS; 1997. p. 99113.
22. Odeseye AO, Olufowote JO, Ijagbone IF, Amusa OD, Aladele SA, Gbadegesin HY, et al. Characteristics and molecular identification of differentially expressed genes in some cowpea (Vigna unguiculata (L.) Walp.) accessions. J Agric Food Res. 2022;10:1-10.
23. Panse VG, Sukhatme PV. Statistical methods of agricultural workers. New Delhi: ICAR; 1985. p. 32740.
24. Raina A, Khan S. Field assessment of yield and its contributing traits in cowpea treated with lower, intermediate, and higher doses of gamma rays and sodium azide. Front Plant Sci. 2023;14:1188077. doi:10.3389/fpls.2023.1188077.
25. Robinson DF. Aztec studies on gene action and heritability. Rep Am Breed Assoc. 1966;21:323-60.
26. Romanus KG, Hussein S, Mashela WP. Combining ability analysis and association of yield and yield components among selected cowpea lines. Euphytica. 2008;162:205-10.
27. Selvi VM, Nirmalakumari A, Anandakumar C, Amudha R. Evaluation of genetic potential between F2 and F3 generations of cowpea (Vigna unguiculata (L.) Walp.) using parent progeny regression analysis. Biol Forum Int J. 2022;14(1):1146-53.
28. Sinclair TR. Historical changes in harvest index and crop nitrogen accumulation. Crop Sci. 1998;38(3):638643.
29. Song YH, Ito S, Imaizumi T. Flowering time regulation: photoperiod-and temperature-sensing in leaves. Trends Plant Sci. 2013;18(10):575-83.
30. Stansfield WD. Theory and problems of genetics. New York: McGraw-Hill; 1969. p. 281.
31. Ullah MZ, Hasan MJ, Rahman AHMA, Saki AI. Genetic variability, character association and path analysis in yard long bean. SAARC J Agric. 2011;9:916.
32. Verma AK, Mehta AK, Gontia AS, Sharma D, Singh RP, Singh P. Genetic variability, heritability and genetic advance studies for yield components in F2 generation of cowpea (Vigna unguiculata (L.) Walp.). Int J Chem Stud. 2019;7(6):3084-3088.