Genetic variability and heritability studies for yield and yield contributing traits in finger millet (Eleusine coracan L.) genotypes under sub-montane agroclimatic zone of Maharashtra

Introduction

Finger millet (Eleusine coracana L.), frequently termed "Ragi" is a self-pollinating allotetraploid monocot (2n = 4x = 36, AABB) within the Poaceae family. Its common name reflects the characteristic finger-like branching pattern of its panicle structure. It serves as a vital crop in the arid and semi-arid expanses of Asia and Africa, with major production centered in countries like India, Uganda, Ethiopia, Kenya, and Nepal. It is very adaptable to a wide range of environmental and climatic conditions and thrives at higher elevations than most other tropical cereals and ability to withstand salinity better than most cereals. Globally, finger millet is the third most vital millet crop after sorghum and pearl millet (Indian Farming (ICAR) article (2025) [7] . It represents 20% and 26% of the world's total area covered and production, respectively, making it the most important small millet grown in tropical regions (FAOSTAT, 2020) [4] . In India, finger millet ranks first in importance among all small millets with a share of 81% in production (Sajja et al. 2025) [16] . It is cultivated over an area of more than 11.45 lakh hectares with 16.25 lakh tones and 1419 kg/ha of production and productivity, respectively in India. While in Maharashtra, it is cultivated in 74.5 thousand hectares with a production and productivity of 69.30 thousand tonnes and 930 kg/ha, respectively (Ministry of Agriculture and Farmers' Welfare, 2025-26) [10] . In Maharashtra, finger millet locally known as nagli or nachni serves as a staple food and economic backbone for rural communities, particularly within the Sub-Montane Agroclimatic Zone. This agro-ecological region, situated along the eastern foot-slopes of the Sahyadri mountain range, is characterized by heavy monsoon rainfall, undulating topography, and shallow, lighttextured, acidic soils with poor moisture retention. While such harsh soil and terrain conditions, coupled with occasional mid-season dry spells, restrict the performance of most conventional field crops, finger millet stands out for its extraordinary hardiness and adaptability. With its deep, fibrous root system, exceptional soil-binding capacity, and high water-use efficiency, it thrives on marginal, sloped lands where other cereals fail. As a result, finger millet serves as a dependable, low-input crop that ensures food and nutritional security for smallholder farming communities across the sub-montane belt. Finger millet is highly nutritious as it is rich source of calcium (344 mg/100 g) and also contains 65-75% carbohydrates, 5-8% protein, 15-20% dietary fibre and 2.5-3.5% minerals (ICAR IIMR, Annual report 2024-25) [7] . Due to its gluten free and low fat, it is easy to digest and non-allergic and that is why finger millet is also called "super cereal" (Singh et al., 2023) [17] . Broadening the germplasm's genetic base depends entirely on a comprehensive evaluation of the genetic variability present within existing genotypes, as progress through selection and breeding is impossible without underlying variation. When phenotypic and genotypic coefficients of variation (PCV and GCV) are integrated with heritability (h 2 ) and genetic advance (GA), they provide a reliable framework for assessing selection efficiency, particularly for complex quantitative traits like grain yield. Because yield is inherently complex and cannot be effectively improved through direct phenotypic selection alone, breeding strategies must target highly heritable, yield-correlated secondary traits. Furthermore, evaluating genetic advance allows to quantify the expected genetic gain or progress achievable through targeted selection for a specific trait.

Materials and Methods

The experiment was laid out in randomized complete block design (RCBD) with two replications at AICRP on small millets, Botany Farm, Rajashree Chhatrapati Shahu Maharaj Government College of Agriculture, Kolhapur during Kharif 2025. The experimental material consists of 24 finger millet accessions including four local checks which were collected from different states of India which are mentioned in Table 1. The size of the plot was 2.40 x 4.00 m. The spacing between the rows was 30 cm and 10 cm between plants. There were 8 rows per entry. All the recommended agronomic packages of practices were followed during the entire crop period. In each replication, five random plants were chosen and observations were recorded on 15 yield and yield contributing characters viz., days to 50% flowering, plant height (cm), flag leaf blade length (cm), flag leaf blade width (cm), peduncle length (cm), ear length (cm), finger length (cm), finger width (cm), finger number on main ear, number of productive tillers per plant, days to maturity, thousand grain weight (g), fodder yield (kg/plot), grain yield (kg/plot) and harvest index. The analysis of variance for each character was calculated as per the standard statistical procedure given by Panse and Sukhatme (1978) [11] . Phenotypic and genotypic coefficients of variation (PCV and GCV) were computed as per Burton (1952) [2] . Heritability in broad sense was computed as per Hanson (1956) [6] . Heritability and genetic advance were categorized into low, medium and high as per Johnson et al. (1955) [8] .

Results and Discussion

Analysis of Variance

The analysis of variance (ANOVA) revealed highly significant differences (𝑝 < 0.01) among the 24 finger millet genotypes across all 15 evaluated traits, indicating substantial underlying genetic variability (Table 2). Ranking the traits by the magnitude of their genotypic mean sum of squares (MSS), plant height exhibited the highest variation at 205.69, followed by harvest index at 79.

Parameters of Genetic Variability

Various genetic variability parameters, including the range of variation, variance components, estimates of genotypic coefficients of variation (GCV) and phenotypic coefficients of variation (PCV), broad-sense heritability, genetic advance (GA) and expected genetic advance as a percentage of the mean, were estimated and are summarized in Table 3. Assessment of variability forms the basis of a successful breeding programme aimed at improving yield and quality attributes. Hence, estimation of genotypic and phenotypic coefficients of variation is necessary to understand the nature and magnitude of variation.

Coefficients of Variation

Genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) are important measures used to assess the magnitude of variability present in a population. Estimates of PCV, GCV and heritability help predict the effectiveness of selection and the expected genetic improvement in a trait.

PCV [15] for fodder and grain yield per plot; Hansalia et al. (2024) [5] [5] for number of fingers per earhead. Low PCV and GCV was recorded for productive tillers per plant (8.08% and 6.57%), finger width (6.85% and 6.47%), finger length (6.34% and 5.63%), flag leaf blade width (7.00%, 5.84%) and thousand seed weight (5.34% and 4.76%), indicating relatively narrow variation for these traits. These results are in accordance with previous reports of Ulaganathan and Nirmalakumar et al. (2014) [18] for finger width; Prajawala et al.

(2025) for thousand seed weight; Bhagyasri et al. (2025) [1] for flag leaf blade width and Patel et al. (2025) [12] for productive tillers per plant.

Heritability

The estimates of broad-sense heritability exhibited considerable variation among the traits studied (

Genetic advance

The estimates of genetic advance (GA) and genetic advance as per cent of mean (GAM) exhibited considerable variation among the traits studied (Table 3). Among the field traits, the highest genetic advance was recorded for plant height (24.09), followed by harvest index ( In contrast, comparatively low GAM was observed for days to 50 per cent flowering (10.67%) and days to maturity (5.65%).

Assessment of heritability provides an idea into the extent to which a trait is governed by genetic factors and plays a crucial role in determining its response to selection. When combined with the genetic advance as per cent of mean, heritability estimates become more useful in predicting gain under selection than heritability estimate alone. High heritability along with high genetic advance as per cent of mean (GAM) was observed for grain yield, fodder yield, harvest index, earhead length, finger width, peduncle length, thousand seed weight, finger length, number of fingers per earhead, flag leaf blade width, number of productive tillers per plant, plant height and flag leaf blade length. This pattern indicates the predominance of additive gene action controlling these traits, suggesting that phenotypic selection would be effective for their improvement. Similar conclusions were reported by Bhagyasri et al. (2025) [1] for finger length, finger width, earhead length, number of productive tillers per plant, thousand seed weight; Priyadharshini et al. (2011) [14] for plant height, number of fingers per earhead, harvest index; Ulaganathan and Nirmalakumar et al. (2014) [18] for flag leaf blade length, flag leaf blade width; Meera et al. (2021) for peduncle length; Raulwar et al. (2025) [15] for fodder and grain yield per plot. In contrast, high heritability coupled with low genetic advance as a percent of mean was recorded for days to 50% flowering and days to maturity, indicating significant environmental influence and non-additive gene action governing this trait, thereby limiting the scope of direct phenotypic selection. Similar findings were reported by Ulaganathan and Nirmalakumar et al. (2014) [18] .

Conclusion

This evaluation of 24 finger millet genotypes under the submontane agroclimatic conditions of Maharashtra revealed significant genetic variability across all 15 studied quantitative traits. The predominance of genotypic variance over environmental effects highlights a strong genetic basis for character expression. High broad-sense heritability coupled with high genetic advance as a percentage of mean was observed for grain yield, fodder yield, harvest index, earhead length, peduncle length, finger width, and 1000-seed weight. This combination confirms that these economically important traits are governed primarily by additive gene action and can be effectively improved through direct phenotypic selection. Conversely, phenological traits such as days to 50% flowering and days to maturity exhibited lower genetic advance as a percentage of mean, indicating non-additive gene influence and environmental sensitivity.

The identified genetic variation and superior high-yielding genotypes particularly FM-02 and FM-07 serve as valuable genetic resources for future finger millet breeding programs. These findings provide a concrete basis for selecting elite parents in future hybridization programs aimed at developing highyielding, climate-resilient cultivars tailored to the sub-montane region.

References

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