Correlation and path coefficient study in finger millet (Eleusine coracana (L.) Gaertn.)

Introduction

Finger millet (Eleusine coracana (L.) Gaertn.) is a nutritionally rich and climate-resilient cereal that plays a significant role in sustaining agriculture across diverse agro-ecological zones of India. Globally, it ranks as the fourth most widely produced millet, following sorghum, pearl millet, and foxtail millet. This annual allotetraploid, self-pollinating crop possesses a chromosome number of 2n = 4x = 36. Native to Africa (Abyssinia), it is

Materials and Methods

The investigation was undertaken during Kharif 2023-24 at the Educational and Research Farm of the Department of Agricultural Botany, College of Agriculture, Dapoli, Ratnagiri, Maharashtra. The study utilized a collection of 30 finger millet genotypes, comprising 26 germplasm lines and 4 standard checks, all maintained at the Department of Agricultural Botany, reflecting the rich germplasm diversity of the crop. The experiment was implemented as a Randomized Block Design (RBD) with two replications. Each genotype was transplanted in plots of 3.0 × 1.0 m size, accommodating three rows per plot, with a spacing of 22.5 cm between rows and 10 cm between plants. Each row contained 20 plants, making a total of 60 plants per genotype. Recommended checks such as Dapoli-1, Dapoli-2, Dapoli-3, and Dapoli Safed were included for comparative evaluation.

Cultural Practices

The crop was raised under uniform agronomic conditions. Standard land preparation practices were followed to achieve a fine tilth. Fertilizers were applied at the rate of 80:40 kg N:P₂O₅ per hectare. Half of the nitrogen dose was applied as basal at sowing, and the remaining half was topdressed 30 days after transplanting. Gap filling was done 10 days after transplanting to maintain uniform plant stand. Irrigation, weed control, and plant protection measures were carried out as per the recommended package of practices to ensure healthy crop growth.

Statistical Analysis  Genotypic and phenotypic correlation coefficients

were calculated following Johnson et al. (1955) [6] to determine the degree of association between grain yield per plant and its component traits.  Path coefficient analysis was carried out as per the method of Dewey and Lu (1959) [3] to partition correlation coefficients into direct and indirect effects, considering grain yield per plant as the dependent variable. The residual effect was computed to account for unexplained variation. For interpretation, the scale suggested by Lenka and Mishra (1973) [8] was followed:  Negligible: 0.00 -0.09  Low: 0.10 -0.19  Moderate: 0.20 -0.29  High: 0.30 -0.99  Very High: >1.00

Results and Discussion Correlation analysis: Phenotypic Correlation Coefficient

Grain yield per plant exhibited highly significant positive correlation with number of fingers (0.503) and straw yield per plant (0.914). It showed significant positive correlation with number of tillers per plant (0.262), number of productive tillers per plant (0.429), finger length (0.424), harvest index (0.395), calcium content (0.346) and iron content (0.149). Non-significant positive correlation was recorded with days to 50% flowering (0.164), days to maturity (0.158), plant height (0.146), test weight (0.132), protein content (0.209) and fibre content (0.039). Negative significant correlation was observed with scoring of blast disease (-0.949), while zinc content showed a negative nonsignificant correlation (-0.311) (Table 1). Fig. no.1 depicts the shaded correlation matrix showing the phenotypic correlations among the studied traits. Devaliya et al. (2017) [2] reported a positive highly significant association for straw yield per plant and Jadhav et al. (2015) [5] observed a positive highly significant association for number of fingers. Madhavilatha et al. (2021) [9] reported a positive significant correlation with number of productive tillers per plant and a positive but non-significant correlation with plant height. Suman et al. (2018) [12] also reported a similar finding for days to 50% flowering, number of productive tillers per plant and scoring of blast disease. Patel et al. (2023) [10] reported a positive but non-significant association for days to maturity, along with a significant positive correlation for finger length, calcium content, and iron content. Additionally, a negative non-significant correlation was observed with zinc content. The number of tillers per plant exhibited a highly significant positive correlation with the number of productive tillers per plant (0.585). It also showed a significant positive association with straw yield per plant (0.380), protein content (0.262), calcium content (0.301), fibre content (0.346), and grain yield per plant (0.262). Number of productive tillers per plant exhibited a positive significant correlation with straw yield per plant (0.477) as well as with grain yield per plant (0.429). Number of fingers exhibited a highly significant positive correlation with finger length (0.708) and grain yield per plant (0.503), along with a significant positive association with straw yield per plant (0.459), protein content (0.454), and iron content (0.259). Finger length possessed a positive as well as significant correlation with straw yield per plant (0.362), protein content (0.257) and grain yield per plant (0.424). Harvest index (%) possessed a positive significant correlation with grain yield per plant (0.395). Protein content exhibited a positive significant correlation with zinc content (0.433). Calcium content revealed a positive significant correlation with grain yield per plant (0.346). Fibre content showed a positive non-significant association with zinc content (0.042), as well as with grain yield per plant (0.039). Iron content exhibited a positive and significant correlation with grain yield per plant (0.149). Zinc content had a negative non-significant correlation with grain yield per plant (-0.311). [2] observed a highly significant positive correlation with the number of productive tillers per plant and straw yield per plant, and also reported a positive significant correlation with protein content and calcium content. Jadhav et al. (2015) [5] reported a positive highly significant association for number of productive tillers per plant and number of fingers. Chavan et al. (2020) [1] disclosed a positive but non-significant correlation with days to 50% flowering and test weight. Patel et al. (2023) [10] reported a positive but non-significant association for days to maturity, along with a positive significant association with finger length and calcium content. Simultaneously, a negative non-significant correlation was observed with zinc content. Number of tillers per plant showed a highly significant positive correlation with number of productive tillers per plant (0.758), and also exhibited significant positive correlations with straw yield per plant (0.400), protein content (0.297), calcium content (0.312), fibre content (0.358), and grain yield per plant (0.270). Number of productive tillers per plant disclosed a highly significant positive association with straw yield per plant (0.941), zinc content (0.567), and grain yield per plant (0.811), while it also exhibited significant positive correlations with number of fingers (0.269), protein content (0.356), calcium content (0.398), and fibre content (0.277). Number of fingers revealed a highly significant positive correlation with finger length (0.735) and grain yield per plant (0.536), and also exhibited significant positive correlations with straw yield per plant (0.484), protein content (0.479), and iron content (0.273). Finger length possessed a positive as well as significant correlation with straw yield per plant (0.365), protein content (0.260) and grain yield per plant (0.428).

Phenotypic correlation matrix

Harvest index possessed a positive significant correlation with grain yield per plant (0.433). Protein content featured a positive significant correlation with zinc content (0.479) and grain yield per plant (0.216). Calcium content revealed a positive significant correlation with grain yield per plant (0.350). Fibre content showed a positive but non-significant association with zinc content (0.043), as well as with grain yield per plant (0.037). Iron content had a positive but nonsignificant correlation with grain yield per plant (0.152). Zinc content showed a negative and non-significant correlation with grain yield per plant (-0.332). Harvest index (0.2680), number of productive tillers per plant (0.0507), finger length (0.0429), calcium content (0.0410) and plant height (0.0302) also showed positive direct effects, though of relatively smaller magnitude (Table 3). Similar results were reported by Chavan et al. (2020) [1] for straw yield per plant, harvest index and plant height in finger millet. Days to maturity (0.0292), iron content (0.0280), and protein content (0.0028) exhibited negligible but positive direct effects on grain yield per plant.

Genotypic correlation matrix

Negative direct effects were observed for number of fingers (-0.0015), days to 50% flowering (-0.0049), number of tillers per plant (-0.0083), zinc content (-0.0188), test weight (-0.0240), fibre content (-0.0262) and scoring of blast disease (-0.2567). Negative direct effects of test weight and number of tillers per plant were earlier reported by Sapkal et al. (2019) [11] . Overall, straw yield per plant emerged as the most influential trait directly contributing to yield, while other traits largely contributed through indirect effects. -0.0049 -0.0047 -0.0016 -0.0004 -0.0003 -0.0028 -0.0021 0.0012 -0.0007 0.0001 0.0003 -0.0012 0.0001 -0.0006 -0.0009 -0.0004 0.1642 DM 0.0282 0.0292 0.0095 0.0027 0.0005 0.0157 0.0123 -0.0079 0.0037 -0.0002 -0.0020 0.0067 -0.0008 0.0035 0.0050 0.0027 0.1583 PH 0.0099 0.0098 0.0302 -0.0137 -0.0034 0.0096 0.0097 0.0036 0.0016 0.0050 -0.0033 0.0045 -0.0038 -0.0018 0.0044 0.0044 0.1463 NT -0.0007 -0.0008 0.0038 -0.0083 -0.0049 -0.0003 0.0006 0.0018 -0.0032 0.0015 0.0017 -0.0022 -0.0025 -0.0029 0.0017 -0.0018 0.2619* NPT 0.0029 0.0009 -0.0057 0.0297 0.0507 0.0066 0.0028 -0.0005 0.0242 -0.0015 -0.0189 0.0101 0.0101 0.0069 -0.0099 0.0119 0.4291** NF -0.0009 -0.0008 -0.0005 -0.0001 -0.0002 -0.0015 -0.0011 0.0001 -0.0007 -0.0002 0.0007 -0.0007 0.0001 -0.0002 -0.0004 -0.0003 0.5026** FL 0.0185 0.0181 0.0137 -0.0030 0.0023 0.0304 0.0429 -0.0042 0.0155 0.0068 -0.0161 0.0110 -0.0047 -0.0085 0.0101 0.0052 0.4241** TW 0.0059 0.0064 -0.0028 0.0051 0.0002 0.0013 0.0024 -0.0240 -0.0025 -0.0044 0.0053 -0.0002 0.0035 0.0058 -0.0040 -0.0019 0.1320 SY 0.0830 0.0786 0.0323 0.2342 0.2941 0.2825 0.2228 0.0647 0.6160 0.0307 -0.5418 0.1898 0.2878 0.1016 0.0590 0.1970 0.9141** HI -0.0009 -0.0016 0.0441 -0.0494 -0.0080 0.0423 0.0425 0.0496 0.0133 0.2680 -0.1104 -0.0424 -0.0484 -0.0863 0.0180 0.0351 0.3945** BS 0.0171 0.0174 0.0284 0.0526 0.0956 0.1129 0.0961 0.0568 0.2258 0.1058 -0.2567 0.0369 0.0638 -0.0103 0.0365 0.0800 -0.9489** PC 0.0007 0.0006 0.0004 0.0007 0.0005 0.0013 0.0007 0.0001 0.0009 -0.0004 -0.0004 0.0028 0.0002 0.0005 -0.0005 0.0012 0.2090 CC -0.0012 -0.0011 -0.0052 0.0123 0.0081 -0.0022 -0.0045 -0.0061 0.0192 -0.0074 -0.0102 0.0024 0.0410 0.0080 -0.0034 0.0063 0.3463** FC 0.0034 0.0031 -0.0016 0.0091 0.0036 0.0035 -0.0052 -0.0063 0.0043 -0.0084 0.0010 0.0045 0.0051 -0.0262 -0.0016 0.0011 0.0393 IC 0.0049 0.0048 0.0041 -0.0056 -0.0054 0.0072 0.0066 0.0046 0.0027 0.0019 -0.0040 -0.0049 -0.0023 -0.0017 0.0280 -0.0102 0.1489* ZC -0.0016 -0.0017 -0.0027 -0.0041 -0.0044 -0.0039 -0.0023 -0.0015 -0.0060 -0.0025 0.0059 -0.0081 -0.0029 -0.0008 0.0069 -0.0188 -0.3114 *Significant at 5 per cent **Significant at 1 per cent

Genotypic Path Coefficient Analysis

At the genotypic level, straw yield per plant exerted the highest positive direct effect (2.5701) on grain yield per plant, followed by scoring of blast disease (1.7474). Harvest index (1.0698), days to maturity (0.2101), number of productive tillers per plant (0.0450), iron content (0.0653), protein content (0.0077) and finger length (0.0008) also exhibited positive direct effects (Table 4). Patel et al. (2023) [10] also observed similar findings in finger millet with respect to straw yield per plant, harvest index, and iron content. Likewise, Keerthana et al. (2019) [7] highlighted the positive direct effect of number of productive tillers per plant and finger length. Test weight (-0.0136), zinc content (-0.0178), fibre content (-0.0311), number of fingers (-0.0732), plant height (-0.1207), calcium content (-0.1832), number of tillers per plant (-0.3094) and days to 50% flowering (-0.3378) recorded negligible negative direct effects on grain yield per plant. Patel et al. (2023) [10] further reported negative direct effects of days to 50% flowering, plant height, test weight, and zinc content in finger millet. Overall, the findings revealed that straw yield per plant, harvest index and number of productive tillers per plant exerted the prominent positive direct effects on grain yield per plant at the genotypic level. Therefore, these traits emerge as key selection criteria for enhancing grain yield in finger millet breeding programmes.

Conclusion

On the basis of correlation and path analysis, grain yield per plant in finger millet can be enhanced through simultaneous selection for traits such as number of tillers per plant, number of productive tillers per plant, number of fingers, finger length, test weight, straw yield per plant, harvest index, protein content, calcium content, and iron content. These traits exhibited significant positive correlations and direct effects with grain yield per plant, indicating their potential utility in yield improvement breeding programmes. It is desirable to give more magnitude of weightage to these characters during selection programme.

References

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