Research Article

Role of Genetic Variability, Heritability and Genetic Advance for Various Traits of Bread Wheat (Triticum aestivum L.) under Variable Sowing Times

Sonal Tolwani and R. S. Shukla

  • Page No:  122 - 130
  • Published online: 18 Feb 2022
  • DOI : HTTPS://DOI.ORG/10.23910/1.2022.2722

  • Abstract
  •  16ltph14@uohyd.ac.in

The field experiments were conducted with 54 genotypes including 10 lines, 4 testers and 40 F1’s. The pure seeds of these 14 selected genotypes were grown in crossing blocks to obtain 40 cross combinations, during November–March of rabi 2016–17. These lines and testers along with obtained 40 crosses (F1’s) were grown in randomised complete block design with 3 replications in 3 sowing dates during November–March in rabi 2017-18 and observations were recorded. Each genotype was sown with spacing of 20 cm between rows and 10 cm between plants. Data recorded for 21 characters including different morphological, physiological and quality traits from 5 randomly selected plants of each replication and mean data used for analysis. In the current investigation, value of PCV is higher than GCV for all the 21 characters. The high values of PCV and GCV were observed for GYPP, BYPP, SV, NEPP, and NTPP in E1, GYPP, BYPP, NEPP, NTPP, HI and SV in E2 and GYPP, BYPP, PL, NTPP, and NEPP in E3. However, we noticed maximum PCV and GCV for GYPP followed by BYPP in E1, E2, and E3. Even though remaining traits showed moderate or low PCV and GCV. High heritability, along with high genetic advance were recorded for the traits GYPP, WG, SV, BYPP, 1000 GW, CC, HI, PL, NEPP, and NTPP. Overall, our findings of various variability parameters may help in the selection of high yielding genotypes under different sowing times in wheat crop.

Keywords :   Genetic advance, GCV, heritability, PCV, wheat

  • INTRODUCTION

    Common or bread wheat (Triticum aestivum L.) is a self-pollinated crop belongs to poaceae family, constituted by outstanding group of food plants which can be grown successfully in both tropical and sub-tropical areas (Bharat et al., 2013). Bread wheat accounts for 95% of all the consumed wheat throughout the worldwide and other remaining 5% is made up of durum or hard wheat T. Turgidum sp. Durum, used in food production industries. Today bread wheat is occupying 17% of crop acreage, feeding about 40% of the world population with excellent nutritional values (Patricia et al., 2019).

    Bread wheat stood as one of the second most important staple crop after rice in India, which shows higher genetic diversity in almost all the countries (Thakur et al., 2018; Soumitra et al., 2016). The production of wheat varies based on the environmental changes; even though the consumption of wheat is increasing day by day because of its higher fibre content than any other diets. The mature wheat grain starchy endosperm consists of 55−75% carbohydrates and 10−20% protein (Gillies et al., 2012). On the other hand, aleurone wheat grain layer has its importance for vitamins, micronutrients, minerals, phytochemicals, and fibres (Liu, 2011; Regvar et al., 2011; Lafiandra et al., 2014).

    Grain yield is a complex trait depends on its various component traits (Khairnar et al., 2018). Thus, assessment of variability is essential for the genetic manipulation of grain yield, quality, and other traits in wheat. Genetic variability is an important tool for any successful breeding programme and it is essential to have a critical survey of genetic variability before initiating an improvement programme for development of a high yielding variety (Falconar, 1989). Reduced genetic variability may cause diseases and adverse climatic changes to crop which impacts in yield production (Dargicho et al., 2015). Thus, for selecting a potential genotype, genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) is an important variability parameter (Nukasani et al., 2013; Kumar et al., 2014; Negasa and Kumar, 2016; Bharat et al., 2018).

    Yield and yield contributing characters are essential to determine crop improvement (Susmita et al., 2021). For selection of a given character in a population, the genetic variability along with heritability and genetic advance (GA) is required (Burton, 1952; Johnson et al., 1955). Heritability is important in a breeding process for determining the extent to which a selected character is transmitted to progenies (Sabesan et al., 2009; Meena et al., 2014). Genetic advance is a measure of genetic gain under selection. Genetic advance depends on magnitude of genetic variability and heritability of a character under consideration. Heritability is the heritable portion of phenotypic variation which is, determining gene expressivity carried by a genotype (Gopal et al., 2020). High heritability along with high genetic advance indicates that heritability is mainly due to additive gene effects and it gives a better idea for selection of desirable characters in developing new genotypes, which reveals the strong relationship between heritability and genetic advance (Mishra and Shukla, 2013; Kumar et al., 2015; Sandeep et al., 2017). In concern with the Indian population, it is a challenging task for breeders to increase the production of wheat crop to cope up with the growing demand to ensure food security. Thus keeping in view, the present investigation was conducted to assess genetic variability, heritability coupled with genetic advance for the genetic improvement of grain yield and its quality traits under varying environments in bread wheat.


  • MATERIALS AND METHODS

    This experiment was carried out in seed breeding farm, college of agriculture, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur (M.P.), India. Total 54 genotypes including 10 female lines (GW 273, GW 322, GW 366, JW-1201,  JW-1202, JW-1203, LOK 1, HD 2864, HD 2932, and HI 1544) and 4 testers (JW-3336, JW-3288, MP-3269, and JW-3211) was taken under this study. The pure seeds of these 14 selected genotypes was grown in crossing blocks to obtain 40 cross combinations during November-march of rabi, 2016–17. These 10 lines and 4 testers along with obtained 40 cross combinations was grown in randomized complete block design with three replications under three different sowing dates (25/11/2017 in E1, 15/12/2017 in E2, 5/01/2018 in E3) during November–March of rabi 2017–18. Each genotype was sown in a single row of 5 m length with 20 cm spacing between rows and 10 cm between plants. Data was recorded on 5 randomly selected plants of each genotype in each replication and every environmental condition on 21 morphological, physiological and quality parameters viz. Days to 50% heading, days to maturity, plant height (cm), number of tillers plant-1, number of ears plant-1, number of spikelets ear-1, number of grains ear-1, ear length (cm), ear weight (g), peduncle length (cm), 1000 grain weight (g), biological yield plant-1 (g), harvest index (%), canopy temperature, chlorophyll content, sedimentation value (ml), protein content (%), wet gluten content (%), starch content (%), hectoliter weight (g), and grain yield plant-1 (g).

    2.1.  Statistical analysis

    The analysis of variance was worked out to estimate the differences among the genotypes as per the method suggested by (Panse and Sukhatme, 1967). GCV and PCV were estimated as per the formula given by (Burton, 1952). Heritability in broad sense (%) was calculated by the formula suggested by (Hanson et al., 1956). Genetic advance and Genetic advance as percentage of mean were estimated by the formula suggested by (Lush, 1945; Johnson et al., 1955).


  • RESULTS AND DISCUSSION

    In the present investigation, we evaluated the analysis of variance (ANOVA), revealed that the mean sum of squares was found highly significant for all the traits in E1, E2, and E3 along with pooled data (Table 1–4) represents the presence of variability among the genotypes. Similar findings were reported by Thapa et al. (2019) for all the traits under study.


    PCV and GCV demonstrate the measure for comparison of variability present in yield and yield attributing traits. PCV is always higher than GCV due to the impact of environmental factors. The higher genetic variability is helpful in the selection of yield attributing traits (Sandeep et al., 2018; Thakur et al., 2020). The high (>15%) GCV and PCV was recorded for grain yield plant-1 (26.01%, 26.77%), biological yield plant-1 (21.04%, 21.39%) and sedimentation value (18.77%, 19.05%), number of ears plant-1 (17.81%, 21.09%) and number of tillers plant-1 (16.67%, 20.85%) in E1. In E2, the high GCV and PCV was  recorded for grain yield plant-1 (23.26%, 24.07%), biological yield plant-1 (22.13%, 23.01%), number of ears plant-1 (19.41%, 22.48%) and number of tillers plant-1 (18.63%, 21.79%), harvest index (18.37%, 19.22%), sedimentation value (16.13%, 16.30%). whereas in E3, grain yield plant-1 (29.04%, 30.34%), biological yield plant-1 (26.21%, 29.81%), number of ears plant-1 (26.03%, 29.39%) and number of tillers plant-1 (24.47%, 27.52%) and peduncle length (17.50%, 21.63%) had high GCV and PCV respectively. The pooled data shows high GCV and PCV for grain yield plant-1 (22.56%, 27.34%), biological yield plant-1 (19.46%, 24.58%), number of ears plant-1 (18.85%, 24.18%) and number of tillers plant-1 (18.06%, 23.14%). Similar results was also reported by Bhushan et al. (2013) for grain yield plant-1 and biological yield plant-1; Thakur et al. (2018) for grain yield plant-1; Meena et al. (2014) and Sandeep et al. (2018) for grain yield plant-1; Soumitra et al. (2016) for plant height;Thapa et al. (2019) for grain yield plant-1 and number of grain ear-1; Thakur et al. (2020) for grain yield plant-1 and number of ears plant-1.   The moderate (10−15%) GCV and PCV was recorded for peduncle length (13.96%, 19.45%), wet gluten content (13.45%, 13.83%) in E1. In E2, peduncle length (13.08%, 18.76%), wet gluten content (11.78%, 12.46%) was recorded for moderate GCV and PCV. Whereas, 1000 grain weight (13.70%, 14.38%), harvest index (13.39%, 16.43%) and sedimentation value (11.46%, 11.70%) has moderate GCV and PCV as per E3. The pooled data shows the moderate GCV and PCV for sedimentation value (13.72%, 15.51%), peduncle length (13.5%, 19.85%) and harvest index (12.47%, 16.78%) and wet gluten content (10.91%, 12.23%). All the remaining traits was having low (<10%) values of GCV and PCV in E1, E2, and E3 represented in Table 5.


    Similar findings was also recorded by Kumar et al. (2014) for 1000 grain weight; Khairnar et al. (2018) for days to 50% heading and number of grains ear-1

    Heritability is an important tool for inheritance of a character and high heritability values indicate least influence of environment. The high heritability (>60%) was found in sedimentation value (98.0%), biological yield plant-1 (96.7%), wet gluten content (94.6%), grain yield plant-1 (94.4%), chlorophyll content (88.1%), plant height (84.4%), harvest index (82.9%), 1000 grain weight (81.0%), days to 50% heading (72.2%), number of ears plant-1 (66.2%), number of tillers plant-1 (63.9%), starch content (62.9%), hectoliter weight (62.7%) in E1. In E2, high heritability was recorded for sedimentation value (97.9%), biological yield plant-1 (97.0%), grain yield plant-1 (93.4%), harvest index (91.3%), wet gluten content (89.4%), plant height (86.5%), 1000 grain weight (81.5%), chlorophyll content (75.9%), number of tillers plant-1 (73.1%), days to 50% heading (72.1%), number of ears plant-1 (71.1%) and hectoliter weight (63.0%). Whereas in E3, high heritability was recorded in sedimentation value (96.0%), biological yield plant-1 (95.6%), grain yield plant-1 (91.6%), chlorophyll content (90.9%), 1000 grain weight (90.8%), wet gluten content (86.7%), hectoliter weight (80.4%), number of tillers plant-1 (79.0%), days to 50% heading (78.5%), number of ears plant-1 (78.4%), plant height (74.1%), harvest index (66.4%) and peduncle length (66.0%). The pooled data of all the three environments had shown high heritability for wet gluten content (79.5%), sedimentation value (78.3%), biological yield plant-1 (69.9%), grain yield plant-1 (68.1%), 1000 grain weight (63.3%) and number of tillers plant-1 (60.9%). Similar findings for high heritability was also demonstrated by Kumar et al. (2015) for grain yield plant-1 and wet gluten; Thakur et al. (2018) for 1000 grain weight; Soumitra et al. (2016) for grain yield plant-1 and number of tillers plant-1; Thakur et al. (2020) for plant height. The moderate heritability (45−60%) in E1 was observed in days to maturity (59.9%), number of grains ear-1 (59.2%), protein content (53.7%), peduncle length (51.6%), number of spikelets ear-1 (49.8%) and ear weight (48.0%). In E2, protein content (55.5%), starch content (50.6%), peduncle length (48.6%) and days to maturity (48.3%) was recorded for moderate heritability. Where as in E3, protein content (54.9%), and number of grains ear-1 (46.2%) had shown moderate heritability. The pooled data of all the three environmental conditions had shown moderate heritability in number of ear plant-1 (59.4%), plant height (57.2%), harvest index (55.3%), days to 50% heading (51.8%), hectoliter weight (50.3%), protein content (48.7%), and peduncle length (46.3%). The moderate heritability was also represented Sandeep et al. (2018) for number of grains ear-1 and number of spikelets ear-1; Khairnar et al. (2018) for harvest index. Remaining all other traits had low heritability i.e.., (<45%) has been represented in Table 6.


    Heritability includes the effect of both the additive and non-additive genes. Thus, heritability alone is not sufficient for the selection processes. Genetic advance is the result of additive gene action. Thus, heritability along with the genetic advance as percentage of mean (genetic gain) is essential for the effective selection. The characters having high heritability along with high genetic advance as percentage of mean are effective for selection. The high (>15%) genetic advance as percentage of mean was recorded for grain yield plant-1 (52.06%), biological yield plant-1 (42.61%), sedimentation value (38.29%), number of ears plant-1 (29.84%), number of tillers plant-1 (27.44%), wet gluten content (26.97%), harvest index (24.07%), peduncle length (20.66%), and chlorophyll content (19.09%) in E1. In E2, grain yield plant-1 (46.29%), biological yield plant-1 (44.89%), harvest index (36.15%), number of ears plant-1 (33.72%), sedimentation value (32.86%), number of tillers plant-1 (32.8%), wet gluten content (22.94%), peduncle length (18.77%), 1000 grain weight (16.93%), and plant height (15.81%) had shown the high values of genetic advance as percentage of mean. Whereas, in E3, the high genetic advance as percentage of mean was recorded for grain yield plant-1 (57.27%), biological yield plant-1 (52.79%), number of ears plant-1 (47.49%), number of tillers plant-1 (44.82%), peduncle length (29.39%), 1000 grain weight (26.89%), sedimentation value (23.13%), harvest index (22.47%), chlorophyll content (19.05%) and wet gluten content (18.96%). The pooled data had represented high genetic advance as percentage of mean for grain yield plant-1 (38.34%), biological yield plant-1 (33.52%), number of ears plant-1 (29.93%), number of tillers plant-1 (29.03%), sedimentation value (25.00%), wet gluten content (20.03%), harvest index (19.10%) and peduncle length (18.92%) as represented in Table 6. Similar findings was recorded by Yadav et al. (2011) for grain yield plant-1 and biological yield plant-1;  Mishra and Shukla (2013) for protein content and sedimentation value; Kumar et al. (2014) and Khairnar et al. (2018) for number of tillers plant-1. Soumitra et al. (2016) for grain yield and number of tillers plant-1; Sandeep et al. (2018) for grain yield; Thakur et al. (2020) for grain yield plant-1; Thapa et al. (2019) for grain yield plant-1 and number of grains ear-1.


  • CONCLUSION

    High GCV and PCV was observed among genotypes with nine important traits having high broad sense heritability and high genetic advance as percentage of mean viz., grain yield plant-1, biological yield plant-1, harvest index, sedimentation value, wet gluten content, number of ears plant-1, number of tillers plant-1, chlorophyll content, and 1000 grain weight in all the three sowing times. Thus, selection based on these traits would be effective for improvement of grain yield and quality attributes in bread wheat.


  • ACKNOWLEDGEMENT

    Author is thankful to Department of Science and Technology (DST) for supporting with Inspire fellowship scheme under the Ref.no: DST/INSPIRE/03/2016/000698


  • Reference
  • Bharat, B., Gaurav, S.S., Ravindra, K., Rishi, P., Manoj, P., Anant, K., Sonu, B., Nagar, S.S., Rahul, V.P., 2013. Genetic variability, heritability and genetic advance in bread wheat (Triticum aestivum L.). Environmental and Ecology 31(2), 405–407.

    Bharat, B., Sonu, B., Ashish, O., Manoj, P., Shailendra, S.G., Bhudeva, S.T., Gyanendra, S., 2018. Genetic variability, Correlation coefficient and path analysis of some quantitative traits in bread wheat. Journal of Wheat Research 5(1), 24–29.

    Bhushan, B., Bharti, S., Ojha, A., Pandey, M., Gourav, S.S., Tyagi, B.S., Singh, G., 2013. Genetic variability, correlation coefficient and path analysis of some quantitative traits in bread wheat. Journal of Wheat Research 5(1), 21–26.

    Burton, G.W., 1952. Quantitative inheritance in grasses. Proceedings of Sixth International Grassland Congress (1), 277–283.

    Dargicho, D., Sentayehu, A., Firdisa, E., Ermias, A., 2015. Genetic variability in bread wheat (Triticum aestivum L.) germplasm for yield and yield component traits. Journal of Biology, Agriculture and Healthcare 5(17), 2015.

    Falconar, D.S., 1989. Introduction to quantitative genetics. 2nd Edition, English Language Book Society/Longman, 288.

    Gillies, S.A., Futaro, A., Henry, R.J., 2012. Gene expression in developing aleurone and starchy endosperm of wheat. Plant Biotechnology Journal 10(6), 608–679.

    Gopal, K., Patel, J.A., Prajapati, K.P., Patel, P.J., 2020. Estimation of genetic variability, heritability and genetic advance for seed yield and its attributes in sesame (Sesamum indicum L.). International Journal of Bio-resource and Stress and Management 11(3), 219–224. 

    Hanson, W.D., Robinson, H.F., Comstock, R.E., 1956. Biometrical studies of yield segregating population konrean lespandeza. Agronomy Journal 48, 268–272.

    Johnson, H.W., Robinson, H.F., Comstock, R.E., 1955. Biomaterial studies of yield in segregating population of Korean lespedeza. Agronomy Journal 48, 268–272.

    Khairnar, S.S., Bagwan, J.H., Yashavantha, K.K.J., Baviskar, V.S., Honrao, B.K., Surve, V.D., Khade, V.M., Chavan, A.M., Bankar, B.N., 2018. Studies on genetic variability parameters and character association in bread wheat (Triticum aestivum L.) under timely and late sown environments of irrigated conditions. Electronic Journal of Plant Breeding 9(1), 190–198.

    Kumar, A., Harshwardhan, K.A., Prasad, B., 2015. Combining ability and gene interaction study for yield, its attributing traits and quality in common wheat. Journal of Applied and Natural Science 7(2), 927–934.

    Kumar, Y., Sethi, S.K., Lamba, R.A.S., 2014. Genetic analysis for economic traits in wheat under salt affected soil. Journal of Wheat Research 6(1), 81–85.

    Lafiandra, D., Riccardi, G., Shewry, P.R., 2014. Improving cereal grain carbohydrates for diet and health. Journal of Cereal Science 59, 312–326.

    Liu, K., 2011. Comparision of lipid content and fatty acid composition and their distribution with in seeds of 5 small grain species. Journal of Food Science 76(2), 334–342.

    Lush, J.L., 1945. Intrawire correlation or regression of offspring on dam as a method of estimating heritability of characteristics. 33rd Annual Procedure of American Society for Animal Production, 293–301.

    Meena, H., Kumar, D., Siddegowda, R., 2014. Genetic variability and character association in bread wheat (Triticum aestivum). Indian Journal of Agricultural Sciences 84, 487–491.

    Mishra, D.K., Shukla, R.S., 2013. Genetic study of root, quality and yield characteristics for drought tolerance in advance generation of bread wheat. Annals of Agricultural Research 34(1), 72–76.

    Negasa, D., Kumar, C.D., 2016. Variability, heritability and genetic advances in wheat (Triticum aestivum L.) breeding lines grown at Horro Guduru Wollega zone, Western Ethopia. International Journal of Advanced Scientific Research and Management 1(1), 23–28.

    Nukasani, V., Potdukhe, N.R., Bharad, S., Deshmukh, S., Shinde, S.M., 2013. Genetic variability, correlation and path analysis in wheat. Journal of Wheat Research 5(2), 48–51.

    Patricia, G., Elena, B., Francisco, M.A., Estela, G., 2019. Worldwide research trends on wheat and barley: A Bibliometric comparative analysis. Agronomy 9, 352.

    Panse, V.G., Sukhatme, P.V., 1967. Statistical methods for agricultural workers. 2nd edition, ICAR, New Delhi, India. 

    Regvar, M., Eichert, D., Kanlich, B., Gianoncelli, A., Pongrac, P., Vogel-Milcus, K., Kreft, I., 2011. New insights into globoids of protein storage vacuoles in wheat aleurone using synchrotron soft x-ray microscopy. Journal of Experimental Botany 62(11), 3929–3939.

    Sabesan, T., Suresh, R., Saravanan, K., 2009. Genetic variability and correlation for yield and grain quality characters of rice grown in coastal saline low land of Tamilnadu. Electronic Journal of Plant Breeding 1, 56–59.

    Sandeep, K., Pradeep, K., Kerkhi, S.A., 2017. Genetic analysis for various yield components and gluten content in bread wheat (Triticum aestivum L.). Journal of Applied and Natural Science 9(2), 879–882.

    Soumitra, M., Subhra, Mukhopadhyana, S.K., Dash, A.P., 2016. Genetic variability, correlation and path analysis of bread wheat (Triticum aestivum L.) genotypes under terminal heat stress. International Journal of Bio-resource and Stress Management 7(6), 123 –1238.

    Susmita, D., Rakesh, K., Battan, K.R., Chhabra, A.K., Lokeshwar, A.R., 2021. Study of coefficient of variation, heritability and genetic advance for different traits of rice genotypes grown under aerobic condition. International Journal of Bio-resource and Stress Management 12(5), 426–430.

    Thakur, P., Prasad, L.C., Prasad, R., Chandra, K., Rashmi, K., 2020. Estimation of genetic variability, heat susceptibility index and tolerance efficiency in wheat (Triticum aestivum L.) for timely and late sown environments. Electronic Journal of Plant Breeding 11(3), 769–775.

    Thakur, P., Upadhyay, P., Rashmi, K., Namrata, Prasad, R., Chandra, K., Madhukar, K., Prasad, L.C., 2018. Study of genetic variability path analysis and diversity of selected germplasm lines of wheat (Triticum aestivum L.) under very late sown condition. International Journal of Bio-resource and Stress Management 9(2), 203–208.

    Thapa, R.S., Sharma, P.K., Pratap, D., Singh, T., Kumar, A., 2019. Assessment of genetic variability, heritability and genetic advance in wheat (Triticum aestivum L.) genotypes under normal and heat stress environment. Indian Journal of Agricultural Research 53, 51–56. 

    Yadav, A.K., Maan, R.K., Kumar, S., Kumar, P., 2011. Variability, heritability and genetic advance for quantitative characters in hexaploid wheat (Triticum aestivum L.). Electronic Journal of Plant Breeding 2(3), 405–408.


Cite

1.
Tolwani S, Shukla RS. Role of Genetic Variability, Heritability and Genetic Advance for Various Traits of Bread Wheat (Triticum aestivum L.) under Variable Sowing Times IJBSM [Internet]. 18Feb.2022[cited 8Feb.2022];13(1):122-130. Available from: http://www.pphouse.org/ijbsm-article-details.php?article=1569

People also read

Research Article

Ichthyofaunal Biodiversity of Kharakuva Fish Market, Veraval, Gujarat, India

Arti Joshi, Ejaz A. Rahim Parmar, G. S. Temkar, A. Y. Desai and A. J. Bhatt

Ichthyofaunal, fish diversity, kharakuva fish market, veraval

Published Online : 11 Oct 2018

Editorial

Editorial

Published Online : 07 Jun 2010