Thirty two progenies of Gmelina arborea were collected from different places in Tamil Nadu, Pondicherry, Kerala and Karnataka. The seedlings were raised and systematic progeny test was carried out during the period between 2016 and 2022. The parental pedigree of the identified progenies are furnished in Table 1. These progenies were evaluated through progeny test in a Row Column Design with a spacing of 2 m x 2 m with three replications for the assessment of analysis of variance as suggested by Panse and Sukhatme (1967). The progenies were

assessed periodically for various growth attributes such as tree height, clean bole height, girth at breast height, basal girth, volume and clean bole volume.

The data gathered from the evaluation were analyzed using AGRES software and tabulated. Estimates of mean, variance and standard error were worked out as per the procedure described by Panse and Sukhatme (1978).The significance test was carried out by referring to the standard ‘F’ table of Snedecor (1961). The observations recorded at 5 years after planting were subjected to variability (Burton and Devane, 1953), heritability (Lush, 1940) and association studies (Goulden, 1952). The Principal Components Analysis (PCA) was carried out to establish the numbers of clusters using Statistical Package for Social Studies (SPSS) version 16.0.1 software in order to identify the patterns of variation (PCA).

The progenies of Gmelina arborea were collected from different ecological sources in India and the growth performance was estimated. The progenies of Gmelina arborea differed significantly for various growth attributes like height, clean bole height, girth at breast height, basal girth, volume and clean bole volume and the results are furnished in table 2. Among the progenies evaluated, the highest mean height was exhibited by FCRI GA 18 (13.33 m) and lowest was exhibited by FCRI GA 27 (5.90 m). Five progenies viz., FCRI GA 18 (13.33 m), FCRI GA 09 (10.94 m), FCRI GA 31 (10.83 m), FCRI GA 29 (10.50 m) and FCRI GA

08 (10.13 m) showed significant and higher tree height. With respect to clean bole height, two progenies FCRI GA 25 (5.09 m) and FCRI GA 26 (4.89 m) registered superior clean bole height compared to the average clean bole height (4.16 m). The girth at breast height and basal girth showed non-significant observations. The girth at breast height ranged from 29.61 cm (FCRI GA

22) to 40.33 cm (FCRI GA 14) and the basal girth ranged between 39.89 cm (FCRI GA 22) and 54.78 cm (FCRI GA 14). Compared to the population mean volume (0.0551 m3), six progenies viz., FCRI GA 08 (0.0886 m3), FCRI GA 09 (0.0823 m3), FCRI GA 24 (0.0704 m3), FCRI GA 18 (0.0748 m3), FCRI GA 13 (0.0727 m3) and FCRI GA 14 (0.0744 m3) exhibited significantly higher volume. However, among these top six significant progenies, the superiority of two progenies viz., FCRIGA 08 and FCRIGA 09 was very well witnessed. Though the clean bole volume registered non- significant observations, the two progenies namely FCRI GA 08(0.0342 m3 and FCRI GA 09 (0.0308 m3) registered maximum values.

The variability and heritability estimates indicated the presence of wider variation among the growth attributes investigated. In general, the PCV values are higher than their corresponding GCV values for all growth attributes. In the current study, high phenotypic coefficient of variation was observed in volume (36.14%), clean bole volume (31.5%) and tree height (22.47%) whereas girth at breast height (13.35%), basal girth (12.75%) and clean bole height (12.57%) showed moderate PCV. In case of GCV, moderate genotypic coefficient of variation was exhibited by tree height (18.39%), clean bole volume (17.53%) and volume (14.87%). Clean bole height, girth at breast height and basal girth recorded low GCV of 7.27%, 6.53% and 5.10% respectively. High heritability was recorded in tree height (67.00%) and moderate heritability for clean bole height (33.39%) and clean bole volume (30.90%) whereas girth at breast height (23.95%), basal girth (16.00%) and volume (16.93%) exhibited low heritability range. High genetic advance as per cent of mean was observed in tree height (31.00%) and clean bole volume (20.08%). Volume (12.61%) registered moderate genetic advance as per cent of mean. All other traits viz., clean bole height (8.65%), girth at breast height (6.59%) and basal girth (4.20%) exhibited low genetic advance as per cent of mean (Table 3).

The phenotypic and genotypic correlation coefficient of morpho-metric traits on clean bole volume is furnished in table 4. The genotypic correlation coefficients were found to be higher than the phenotypic correlation coefficients. Girth at breast height (0.930** and 0.910**) and basal girth (0.774** and 0.834**) showed positive and significant correlation at genotypic and phenotypic levels on clean bole volume. Clean bole height (0.804**) exhibited significant and positive correlation on clean bole volume at genotypic level and volume (0.623**) showed positive and significant correlation at phenotypic level. Tree height had negative correlation on clean volume but significant as observed at genotypic level (-0.702**). Tree height showed negative significance through clean bole height (- 0.693**), girth at breast height (-0.593**), basal girth (-0.773**) whereas through volume (0.707**) showed positive significant correlation on clean bole volume. Positive significance at phenotypic level from volume through tree height (0.646**), girth at breast height (0.732**) and basal girth (0.655**) on clean bole volume was also witnessed.

Table 2. Biometric attributes of Gmelina arborea genetic resources

The estimates of direct and indirect effect of growth attributes on clean bole volume are furnished in table 5.

The residual effect was observed as 0.1320. Among the growth attributes investigated, volume (0.6499), clean bole height (0.6356) and basal girth (0.3040) showed

Table 4. Phenotypic and Genotypic correlation coefficient of morphometric traits

Table 5. Path coefficient analysis of morphometric traits on clean bole volume

high positive direct effect whereas tree height (- 0.5433) showed negative direct effect on clean bole volume. High positive and indirect effect was exhibited by tree height through volume (0.4594) and negative through clean bole height (-0.4405) and basal girth (-0.2351) on clean bole volume. Girth at breast height recorded high positive indirect effect on clean bole volume through tree height (0.3221), clean bole height (0.3416) and moderate indirect effect on basal girth (0.2732). Volume alone exhibited negative indirect effect through tree height (-0.3841), clean bole height (-0.2771), girth at breast height (-0.0134) and basal girth (-0.0605) on clean bole volume

The genetic divergence studies resolved 32 progenies into 6 clusters wherein the cluster I was largest with 17 progenies followed by cluster IV with 6 progenies; cluster VI with 3 progenies and cluster II, III & V

represented two progeny each (Table 6). The inter and intra cluster D2 and D values among the six clusters are presented in Table 7. The maximum intra cluster distance was observed in cluster IV (28.548) followed by cluster VI (24.260) and cluster I (8.879). The maximum inter cluster distance was observed between cluster V and cluster VI (35.414) followed by cluster IV and cluster VI (33.524) and cluster I and cluster IV (21.384). The minimum distance was observed between cluster II and cluster III (3.065) followed cluster I and cluster III (6.659) and cluster I and cluster II (6.861). The cluster mean values for morpho-metric traits are presented in Table 8. The highest cluster mean for tree height was observed in cluster V (10.888) followed by cluster IV (9.261) and cluster II (8.195) and lowest was observed in cluster III (7.412). For clean bole height, the highest mean was recorded in cluster VI (4.574) and lowest mean in

Table 6. Clustering pattern of Gmelina arborea genetic resources

Table 7. Inter (diagonal) and intra cluster D2 and D (parentheses) values of Gmelina arborea for morphometric attributes

Table 8. Cluster mean values for morphometric attributes

cluster IV (3.939). Cluster VI (37.640) and cluster III (31.388) exhibited maximum and minimum cluster mean for girth at breast height. For basal girth and volume, cluster V (48.472, 0.074) exhibited highest cluster mean and lowest was observed in cluster III (42.538, 0.042). The maximum and minimum cluster mean for clean bole volume was recorded in cluster VI (0.037) and cluster III (0.023). The percentage contribution of morphometric traits towards genetic divergence are depicted in Table 9. Among the six traits studied, maximum divergence was contributed

Table 9. Percentage contribution of morphometric traits to genetic divergence

by girth at breast height (26.01%) followed by clean bole volume (24.60%), basal girth (19.36 %) and minimum divergence by volume (6.65%).

The Principal Component Analysis, is one of the multivariate analysis that provides easier understanding of impacts and connections among different traits and also help to identify the best genotypes for selection in breeding programme. To find the extent of variability in the progenies, PCA was estimated for all six growth traits. The Number of Principal Components calculated from correlation matrix was six. Six principal components were grouped, in which two components PC1 and PC2 exhibited more than one Eigen values and contributed 86.72 per cent of total variability among the progenies (Table 10). In biplot diagram (Fig.3.), the traits and progenies were scattered around the origin. Based on the biplot, tree height below the origin and having variation. All other remaining traits were above the origin and exhibited positive variation. The progenies FCRI GA 17, FCRI GA 18, FCRI GA 19,

FCRI GA 22, FCRI GA 25 and FCRI GA 26 recorded more variation for all the traits observed.

The Gmelina arborea progeny evaluation test indicated significant variation among the progenies due to growth attributes. Among the 32 progenies evaluated, six progenies viz., FCRI GA 08 (0.0886 m3), FCRI GA 09 (0.0823 m3), FCRI GA 24 (0.0704

m3), FCRI GA 18 (0.0748 m3), FCRI GA 13 (0.0727

m3 ) and FCRI GA 14 (0.0744 m3 ) exhibited significantly higher performance in terms of growth attributes. Among these six progenies two progenies viz., FCRI GA 08 (0.0886 m3), FCRI GA 09 (0.0823

m3), recorded increased volume and reigned supreme and extend scope for its early deployment. The variation among the progenies / clones / genotypes / seed sources are commonly used as estimates of total genetic variation and used to calculate the degree of genetic control for a particular trait (Foster and Shah, 1988). The analysis of variance for 32 different progenies showed that all the growth attributes intended for study exhibited significant variability. A plethora of workers indicated variations in growth attributes due to progenies viz., Casuarina (Parthiban et al., 2018), Thornless bamboos (Krishnakumar et al., 2017) Melia azedarach (Meena et al., 2014), Albizia lebbeck (Takur et al., 2014) and Eucalyptus tereticornis (Kumar et al., 2010). Generally, variation is a prerequisite for genetic improvement of any species and desired improvement is achieved only through exploitation of genetic variation. Hence the variations recorded for growth attributes like tree height, clean bole volume, girth at breast height, basal girth, volume and clean bole volume in the present study extend scope for selection of progenies with increased values for growth attributes. Among the 32 progenies evaluated two progenies viz., FCRI GA 08 and FCRI GA 09 registered significantly higher values which could be deployed for immediate adoption in Agroforestry promotional programme. The evaluation of juvenile plantation is an early starter to raise agroforestry plantations to satisfy the demands of both domestic and industrial utility as evidenced in Toona ciliata (Parthiban et al., 2019).

1.1. Variability is the key for progressing tree improvement program. Selection of any trees is based on phenotypic

superiority. However the phenotypic superiority needs

to be tested for its genetic superiority. For this purpose, the genetic estimates are very useful tool in predicting amount of gains expected in a short period (Foster and Shaw., 1988). The genetic estimates in the current study revealed that the PCV values are higher than their corresponding GCV values and suggest that these characters are influenced by the environment. Among the growth attributes, volume followed by clean bole volume and tree height exhibited higher PCV values with a moderate GCV values. Similar higher PCV values than their corresponding GCV was also reported in Kadam (Parthiban et al., 2019) which lend support to the current investigation. The influence of environment was attributable to the higher PCV than their corresponding GCV for all the growth attributes studied was also reported in various species viz., Sandalwood

Table 10. Eigen values, % variance and cumulative variability of Gmelina arborea

(Krishnakumar et al., 2017) and Salix alba (Paray et al., 2017). Hence the higher PCV exhibited in the current investigation for various growth attributes might be due to the influence of environment.

Heritability is an important indicator for a breeder for selection and it may provide more reliable conclusion along with genetic gain. High heritability along with the high genetic gain is known to be good selection indicator and is controlled by additive genes. In the current study, tree height, clean bole height and clean bole volume recorded high heritability values and tree height and volume exhibited high genetic advance as mean values which indicated that these traits are under strong genetic control and could be reliable indicators in Gmelina tree improvement program. It is also observed that heritability estimates accompanized by high genetic advance are more reliable (Burton and Devana, 1953) which lend support to the findings of current study. Such a high heritability coupled with high genetic advance for various growth parameters have been witnessed in the same species Gmelina arborea (Kumar, 2007) which also support the results of current findings. In the present study, high heritability accompanied by high genetic advance for the growth attributes might be due to additive gene effect and play a vital role in Gmelina improvement program.

Selection will be effective when the traits exhibit high heritability. Heritability estimates in broad sense will be reliable if accompanied by genetic gain. In the present investigation, high to low estimates of heritability along with genetic gain were observed for six traits under study. This indicates the higher proportion of additive gene effects for expression of these traits. Hence individual clone selection would be effective for improvement of these characters. High heritability with high genetic advance is observed for tree height which indicates that the trait is controlled by additive genes and selection may be effective. The present results are in accordance with Behara et al. (2017) in Eucalyptus. Reports of Lokmal (1994) presented low heritability for tree height and girth at breast height in Gmelina.

The path analysis gives an insight into a complex relationship between different characters in a biological system. The overall correlation observed between two variables is a function of series of direct and indirect relationship. In the current investigation, wide ranges of results were found for many characters with direct negative effects and indirect positive effects. Among the characters, clean bole height, basal girth and volume showing high positive direct effect on clean bole volume whereas tree height showed negative and high direct effect on clean bole volume. This suggests that these traits will be used as selection criteria for Gmelina breeding programme. High and positive indirect effect of clean bole height, girth at breast height, basal girth through tree height on clean bole volume was recorded in this study. Remaining traits showed high to negligible indirect effects on clean bole volume. Similar results were indicated by Ashok kumar and Paramathma (2005) in Casuarina, Kumaran et al., (2010) in Simarouba glauca and Parthiban, (2001) in Teak. The results of current study indicated that the biometric attributes like clean bole height, diameter and volume are reliable factors in Gmelina arborea improvement programme as evidenced in Kadam (Parthiban et al., 2019)

The genetic diversity analysis studies among 32 progenies were grouped into six different clusters. Most forest trees are long lived, out breeding and generally highly heterozygous, which have developed a number of natural mechanisms to maintain heterozygosity and intra specific variations. These genetic mechanisms combined with the often variable environment, in which forest trees occur, have contributed to the fact that, with a few exceptions,forest trees seem to be among the most genetically variable of all organisms studied to date (Libby, 1987). In the current study, genetic diversity existed among the 32 selected genotypes of Gmelina arborea had been assessed through D2 analysis which resolved 32 progenies into six clusters. Out of 32 progenies, 17 progenies were grouped in cluster I. The progenies were collected from different districts of Tamil Nadu were grouped in cluster I which indicates that grouping will not be influenced by location from where it was collected. The clustering pattern of the obtained results coincides with Deve and Parthiban (2014) in Dalbergia sisoo and Selvan and Parthiban (2018) in Neolamarckia cadamba. Cluster IV, cluster VI and cluster I exhibited maximum intra cluster distance. Hence, based on desirable traits, selection within these clusters may be exercised for Gmelina improvement. The maximum inter cluster distance was observed between cluster V and cluster VI and cluster IV and cluster VI. In the present investigation it could be seen that the progenies from different locations got clubbed together to form a single major cluster as evident in cluster I and therefore the pattern of divergence was not depended on the geographic locations. The above findings also confirmed the earlier report of Vennila, 2009 in

EucalyptusLeucaena leucocephala (Chavan and Keerthika 2013) and Melia dubia (Saravanan, 2012). The inclusion of geographically divergent provenances in the same cluster may be attributed to the fact that the factors other than geographic distribution might be responsible for their genetic similarity and hence the divergent progenies used in the current project and grouped under one cluster might be due to the factor other than the geographical distribution as evidenced in Santalum album (Manojkumar, 1994) and Prunus armeniaca (Singh and Chaudhary, 1992). Based on the cluster mean performance, cluster V recorded maximum for tree height, basal girth and volume and cluster VI for clean bole height, girth at breast height and clean bole volume. Hence, the genotypes in these clusters may be selected for trait improvement. Girth at breast height contributed more divergence than other traits in the studied progenies (Fig.1). The obtained results were in accordance with the results of Pande et al., (2013) in Leucaena leucocephala