Maize is one of the most essential fodder crops, particularly for milch animals. The crop is grown in over 0.9 million ha in different parts of the country throughout the year. It is a C4 plant having high fodder production capacity in a short duration. The maize plant provides excellent fodder for livestock, particularly from the tasseling stage onwards. Its demand is increasing very fast, particularly with dairy, poultry, and maize-based industries [1]. Maize whose ears are at the doughy stage of grain development provides for the best fodder; at this stage, maize surpasses all other fodder crops for dry matter production and digestible nutrients per hectare. Forage maize is quick growing, succulent, sweet palatable, high yielding, nutritious and free from toxicants and can be safely fed to animals at any stage of crop growth [2]. It is utilized in the form of grains, green fodder, silage, Stover and pasturage. Green fodder provides adequate energy and proteins for growth of animals and milk production [3]. Corn is an important feed for animal and poultry with high net energy content and low fibre content. Germplasm, a prerequisite for any breeding programme, serves as a valuable source material as it provides scope for building genetic variability. The crop has tremendous genetic variability, enabling it to thrive well in tropical, subtropical, and temperate climates.

[9] Mahalanobis (1936) D² statistics is a handy tool to study the nature and magnitude of diversity present in the available germplasm. The Knowledge of genetic variability is a pre-requisite for any breeding programme since it helps in choosing the best yield attributes either for selection or hybridization. Keeping this in view, the present investigations were undertaken with the following objectives:

1. Study of economically important traits, which could be directly used as the donor’s in the future breeding program.

2. To develop improved varieties through selection and hybridization.

MATERIAL AND METHODS

The present investigation was carried out at Fodder Farm (RVC) of Birsa Agricultural University, Jharkhand. Geographically, the Ranchi district is situated in a plateau region with latitude 23°17’ N, and 85°10’ E longitude at an altitude of about 625 metres above mean sea level. The area, on average, receives 1398 mm of rainfall. The climate of the site is sub-tropical humid. The experimental materials in the present study comprised of two composite forage as check varieties viz., African Tall and J-1006, along with 17 maize entries tested in different part of India, where each entry was accommodated in a 7.2 m² plot size containing 6 rows of 4 m length with an inter-row spacing of 30 cm with three replications. The recommended dose of fertilizer N : P : K, 80 : 40 : 20 kg/ha was given to achieve average growth of the crop. Full dose of phosphatic and potassic fertilizers and a half dose of nitrogenous fertilizer were applied at the time of final land preparation as basal dose. The remaining half of nitrogenous fertilizer was top-dressed 40 days after sowing. Five randomly selected plants from the rows of a plot for each genotype were tagged for recording the observations on plant population (m²), days to 50 per cent flowering, plant height (cm), green fodder yield (q/ha), dry matter yield (q/ha/day), dry matter yield (%), leaf /stem ratio, green forage yield (q/ha/day) and crude protein content (%). D² statistics given by [9] was used for the analysis. Seventeen genotypes were grouped into five clusters as per Tocher’s method described by [4]. The intra and inter-cluster distance were worked out by using Mahalanobis D² statistics.

Results and Discussion

The genetic divergence can be estimated by using an effective statistical tool, Mahalanobis D² statistics, which gives a clear idea about the diverse nature of the population. The analyses of variance were carried out for all the seven quantitative traits among seventeen genotypes are presented in Table-1. The mean sum of squares due to genotypes showed significant differences for all the seven traits under study. Hence, a large amount of variability might be due to the diverse source of materials taken for the present study. This indicated ample scope for selecting promising lines from the current gene pool for green forage yield and yield attributing traits. Significant differences among forage maize genotypes for forage yield and yield contributing traits were also reported by [5-6].

Table 1:  Analysis of variance for 7 characters in Fodder Maize.

Table 2:  Range and mean of 7 characters in Forage Maize.

Table 3 : Estimation of genetic parameters of 7 characters of Forage Maize

Table 4 : Phenotypic and Genotypic Correlation coefficient  between 7 component characters of Forage Maize

   *Significant at  P = 0.05

 ** Significant at P = 0.01

Table 5 : Direct and Indirect effects of 7 component traits on Forage Maize

Residual effect:        Phenotypic  (P) = 0.9130

                                      Genotypic   (G) = 1.0606

The knowledge of genetic diversity among the genotypes is essential for selection of parents for hybridization programme, especially in a cross pollinated crop like maize. seventeen genotypes were grouped into 5 clusters (Table-7) as per Tocher’s method described by [7]. Cluster I was the largest with 13 genotypes, followed by cluster II with 2 genotypes, followed by cluster III, and V was mono-genotypic. Distribution of genotypes in different clusters was random but it has clearly shown relationship with the characters for which they were bred. It indicates that genetic diversity and geographic diversity are not related. The pattern of group constellation proved the existence of significant amount of variability. Earlier workers [8] grouped 45 forage maize genotypes into 7 clusters, [10] grouped 30 genotypes into 6 clusters, and [11] 54 genotypes of maize into 7 clusters.

Table 6 :  Cluster mean for 7 characters in Forage Maize

Table 7 : Number and name of genotypes in different cluster

The intra and inter-cluster distance values were worked out using Mahalanobis D² statistics. The mean D² values (Table-6) cluster elements were used as measures of intra and inter-cluster distance. The maximum inter-cluster distance was observed for cluster between II & IV (265.469) followed by cluster III & V (249.469), followed by cluster I (271) indicating that the genotypes of these clusters might be differing marginally in their genetic architecture. In the case of clusters III, IV & V the intracluster distances are zero because of its mono-genotypic nature. These results suggest that maximum divergence between genotypes of these indicating the fact that the genotypes present in one cluster differ entirely from those present in other clusters. While lowest divergence was noticed between cluster I and II (59,265).

Table 8 : Inter and Intra Cluster Distance

Table 9 : Independent character contribution towards divergence.

The present study revealed that CP (%) contributed maximum (40.35%) for divergence followed by plant height (cm) (35.67%), Days to 50% flowering (20.85%) and GFY (q/ha)(1.17%). to total divergence. This result was in accordance with [12] and [13] reported high contribution to the divergence by days to 50 % flowering, high contribution due to plant height was reported by [14] and [15].

The cluster means for seven quantitative traits studied in seventeen genotypes of maize revealed considerable differences among the entire clusters. Cluster wise mean and over all cluster mean for the characters are presented in Table-6.The maximum intra cluster distance was observed for cluster I (D=59.68) followed Cluster II (D=29.95)indicating that the genotypes of these clusters might be different marginally in their genetic architecture .In the case of clusters III,IV and V the intra cluster distances are zero because of its monogenotypic nature. Cluster II exhibited highest character means for plant height (cm) and DMY (q/ha) .Cluster V showed highest character flowering, CP% and leaf stem ratio. Hence, it is obvious from the result that, Cluster II may be used as one of the parent in crossing programme to enhance the plant height and DMY(q/ha),Cluster IV may be used as the parent for improving days to 50% flowering ,CP% and leaf stem ratio . High contribution to the divergence was due to green forage yield as reported by [16].

On the basis of cluster mean and divergence observed in the present study, the genotypes viz PFM-13, VL-117 and PMC -13 were distinct and diverse and could be classified as promising genotypes. These genotypes may be used in crossing programme to achieve the desired segregants in forage maize.

References

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