Assessment of genetic variability, heritability, and genetic advance for yield and yield-attributing traits in kodo millet (Paspalum scrobiculatum L.) germplasm

Introduction

Kodo millet (Paspalum scrobiculatum L.), a tetraploid cereal (2n = 4x = 40), belongs to the family Poaceae and is one of the most ancient small millets, domesticated in tropical Africa and later introduced to India, where it has been cultivated for nearly 3,000 years (Burton, 1940; Malleshi and Hadimani, 1993; Upadhyaya et al., 2016) [2,9,20] . It is predominantly grown in the states of Madhya Pradesh, Chhattisgarh, Tamil Nadu, Karnataka, and Maharashtra, and is also cultivated in several Asian and African countries (De Wet et al., 1983) [4] . Kodo millet is well adapted to marginal soils and low-input farming conditions, making it an essential cereal for smallholder and rainfed farming systems (Harinarayana, 1989; Padulosi et al., 2009; M'Ribu and Hilu, 1996) [6,11,8] . Despite its resilience, the average productivity of kodo millet in India remains low (~312 kg/ha) compared to its potential yield of 2000 kg/ha under improved agronomic practices (Bondale, 1994; Singh, 1994) [1,17] . Limited genetic improvement and lack of systematic breeding efforts are significant reasons for this wide yield gap. Since genetic variability forms the foundation of crop improvement, the assessment of variability, heritability, and genetic advance in morphological and yield-related traits is crucial for identifying promising genotypes and designing effective breeding strategies (Johnson et al., 1955; Panse and Sukhatme, 1985; Ragini et al., 2015; Thakur et al., 2020) [7,12,14,19] . Previous studies in kodo millet have reported considerable diversity in morphological attributes, including plant height, panicle length, tillering ability, and yield-related characters (Sharma et al., 2017; Patil et al., 2020) [16, 13] . However, systematic information on the nature and magnitude of these genetic parameters is still limited. Therefore, the present investigation was undertaken to study the extent of genetic variability, heritability, and genetic advance in kodo millet for morphological and yield traits, to identify superior germplasm accessions for future crop improvement programs.

Materials and Methods

The field experiment was conducted during the Kharif season of 2024-2025 at the ICAR-Indian Institute of Millets Research (IIMR), Rajendranagar, Hyderabad, India. The primary objective was to evaluate the morpho-agronomic diversity of kodo millet germplasm accessions at the Research Farm of IIMR, Hyderabad, situated at an elevation of 535 m above mean sea level (17.45° N latitude and 78.47° E longitude). The experimental site receives an average annual rainfall of 854.6 mm.

Experimental material and design:

The study comprised 60 kodo millet germplasm accessions, including four checks (GPUK 3, TNAU 86, JK 41, and JK 36) (Table 1). Each accession was planted in two rows of 2.0 m length, with a spacing of 45 cm between rows and 10 cm between plants within rows. The experiment followed an Augmented Randomized Complete Block Design (Augmented RCBD) with seven blocks, where the check varieties were replicated across all blocks.

Traits recorded: Observations were recorded on a set of morphological and yield traits, including number of tillers per plant, panicle length (cm), thumb length (cm), peduncle length (cm), plant height (cm), days to 50% flowering, days to 100% flowering, days to maturity, 1000-seed weight (g), grain yield per plant (g), fodder yield per plant (g), and harvest index (%).

Statistical analysis:

The collected data were subjected to analysis of variance (ANOVA) under the augmented design. Genetic parameters were estimated, including heritability, genetic advance, and genetic advance as a percentage of the mean, phenotypic coefficient of variation (PCV), and genotypic coefficient of variation (GCV). Further, mean performance and variability analyses were conducted using INDOSTAT and R software.

Results and Discussion

Based on the observations of various quantitative and qualitative characteristics studied, the results of this experiment are grouped into 1 Analysis of variance (ANOVA) 2 Mean performance, descriptive statistics, and variability, and 3 Analysis of genetic variability, heritability, and genetic advance

Genetic Variability and Heritability of Yield and Grain Quality Trait 1. Analysis of variance (ANOVA)

The analysis of variance (ANOVA) under an augmented randomized complete block design involving 60 kodo millet genotypes (56 germplasm accessions and four checks) revealed significant variability for all 12 morpho-agronomic traits studied (Table 2). The study highlighted several key findings related to agricultural performance metrics. Significant variation was observed for grain yield and harvest index across blocks, entries, and genotypes, as well as in the interactions between genotypes and checks. For days to flowering (50% and 100%), differences were likewise detected among blocks, entries, genotypes, and checks. In contrast, the number of tillers and peduncle length differed significantly only when genotypes were compared with checks. Variation was also evident among entries, genotypes, checks, and their interactions for panicle length and plant height. Days to maturity showed significance across blocks, entries, genotypes, and interactions, while test weight differed among blocks, entries, and genotypes. A highly significant response was recorded for fodder yield among entries, genotypes, and checks. In comparison, no meaningful differences were observed for thumb length. These results highlight the presence of wide genetic variability, providing opportunities for identifying superior genotypes through selection, in agreement with earlier reports by Sao et al. (2017) [15] , Nirubana et al. (2017a) [10] , and Suthediya et al. (2021) [18] .

Mean performance of genotypes

The mean performance and descriptive statistics of 60 kodo millet germplasm accessions were assessed for 12 yieldrelated traits using an augmented design with seven blocks. Parameters, including mean, range, standard error, standard deviation, and coefficient of variation (CV%), provided insights into variability and distribution patterns (Tables 3 and4). There are wide ranges and higher CV% for traits such as fodder yield, grain yield, harvest index, and number of tillers per plant. Conversely, traits with lower CV%, such as early maturity, test weight, days to flowering, thumb length, peduncle length, panicle length, and plant height, showed relative stability across genotypes. These findings offer a valuable baseline for identifying superior genotypes in kodo millet improvement programs.

Analysis of genetic variability, heritability, and genetic advance

Genetic parameters (Table 5) indicated that the phenotypic coefficient of variation (PCV) was generally higher than the genotypic coefficient of variation (GCV) for all traits, confirming the influence of environment. However, the differences were narrow for traits such as days to maturity, days to flowering, and test weight, suggesting strong genetic control. High GCV was observed for grain yield per plant, fodder yield per plant, and harvest index. NT-No. of tillers per plant, PL-Panicle length (cm), ThL-Thumb length (cm), PDL-Peduncle length (cm), PH-Plant height (cm), DFF-Days to 50% flowering, D100F-Days to 100% flowering, DTM-Days to maturity, TSW-1000 Seed weight (g), GYP-Grain yield/plant (g/plant), FYP-Fodder yield/plant (g/plant), HI-Harvest index (%).

Conclusion

This study demonstrated that kodo millet possesses a broad genetic diversity across agronomic traits, underscoring its potential for yield improvement. The observed variation in flowering behavior and yield components suggests that different genotypes can be strategically utilized depending on production environments and breeding goals. The moderate to high heritability estimates coupled with substantial genetic advance for key traits indicate that meaningful progress can be achieved through selection. Overall, the findings reaffirm the value of kodo millet as a resilient, climate-smart crop with scope for dual-purpose use. Future breeding efforts should focus on combining early maturity and high yield to deliver varieties that meet both farmer and consumer needs, thereby strengthening the role of kodo millet in food and nutritional security.

Acknowledgement

AcknowledgementThe authors sincerely acknowledge Professor Jayashankar Telangana Agricultural University (PJTAU), Rajendranagar, Hyderabad, for providing the academic guidance and institutional support necessary for this research. We are deeply grateful to the ICAR-Indian Institute of Millets Research (IIMR), Rajendranagar, Hyderabad, for extending the field facilities that enabled the successful execution of the study. Special thanks are due to the faculty members, technical staff, and field assistants of the Department of Genetics and Plant Breeding, as well as the staff of the Research Farm, for their dedicated assistance during experimentation and data collection. The encouragement and constructive suggestions from colleagues and fellow researchers are gratefully recognized. Finally, we extend our appreciation to all individuals, directly and indirectly, who contributed to the smooth progress and completion of this research work.

References

1. Bondale KV. Status of small millets in India. In: National Seminar on Ragi and Small Millets; 1994 Jan;
2. Burton GW, De Vane DE. Estimating heritability in tall fescue (Festuca arundinacea) from replicated clonal material. Agron J. 1953;45:478-481.
3. Glenn WB. A cytological study of some species in the genus Paspalum. J Agric Res. 1940;60:193-218.
4. de Wet JM, Brink DE, Rao KP, Mengesha MH. Diversity in kodo millet (Paspalum scrobiculatum). Econ Bot. 1983;37(2):159-163.
5. Falconer DS. Introduction to quantitative genetics. 4th ed. Harlow: Pearson Education; 1996.
6. Harinarayana G. Breeding and varietal improvement of small millets in India. In: Riley KW, Gupta SC, Seetharam A, Mushonga JN, editors. Small millets in global agriculture. New Delhi: Oxford & IBH; 1989. p.59-70.
7. Johnson HW, Robinson HF, Comstock RE. Estimates of genetic and environmental variability in soybeans. Agron J. 1955;47:314-318.
8. M'Ribu HK, Hilu KW. Application of random amplified polymorphic DNA to study genetic diversity in Paspalum scrobiculatum L. (kodo millet, Poaceae). Genet Resour Crop Evol. 1996;43(3):203-210.
9. Malleshi NG, Hadimani NA. Nutritional and technological characteristics of small millets and preparation of value added products from them. In: Riley KW, Gupta SC, Seetharam A, Mushonga JN, editors. Advances in small millets. New Delhi: Oxford & IBH; 1993. p. 270-287.
10. Indian J Plant Genet Resour. 2009;22(1):1-6.
11. Panse VG, Sukhatme PV. Statistical methods for agricultural workers. 2nd ed. New Delhi: ICAR; 1967. [Edition/year may need confirmation]
12. Patil RB, Vijayalakshmi KG, Vijayalakshmi D. Physical, functional, nutritional, phytochemical and antioxidant properties of kodo millet (Paspalum scrobiculatum). J Pharmacogn Phytochem. 2020;9(5):2390-2393.
13. Ragini S, Subramanian A, Nirmalakumari A, Bapu JK. Genetic diversity in kodo millet (Paspalum scrobiculatum) relative to culm strength and yield. J Crop Improv. 2015;29(4):420-431.
14. Sao A, Singh P, Kumar P, Pradhan A. Estimates of genetic parameters for yield and contributing traits in kodo millet (Paspalum scrobiculatum L.). Res J Agric Sci. 2017;8(1):120-122.
15. Sharma S, Sharma N, Handa S, Pathania S. Evaluation of health potential of nutritionally enriched finger millet (Eleusine coracana) grown in Himachal Pradesh, India. Food Chem. 2017;214:162-168.
16. Singh SV. Seed improvements in small millets and role of minikit programme in their development. In: National Seminar on Ragi and Small Millets; 1994 Jan;
17. Thakur J, Kumar V, Kanwar RR. Genetic divergence studies in kodo millet (Paspalum scrobiculatum L.). J Pharmacogn Phytochem. 2020;9(6):1373-1377.
18. Upadhyaya HD, Vetriventhan M, Dwivedi SL, Pattanashetti SK, Singh SK. Proso, barnyard, little, and kodo millets. In: Singh M, Upadhyaya HD, Kumar J, Bisht IS, editors. Genetic and genomic resources for grain cereals improvement. London: Academic Press; 2016. p. 321-343.