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The total area under garlic cultivation in India is (2.45 million hectare) and production is (3.65 million tonnes) with productivity of (18.72 million tonnes/hectare) (NHRDF, 2020). With respect to its production and economic value, garlic is one of the main Allium vegetable crops in the world and used as a seasoning in many food throughout the globe. Garlic has also medicinal value which is well recognized in the control and treatment of hypertension, worms, germ, bacterial and fungal diseases diabetes, cancer, ulcer, rheumatism etc.

(Kilgori et al., 2007(b) Samavatean et al., 2011, & Kamenetsky et al., 2006) Many people perceived and appreciated garlic for its many medicinal attributes (Rabinowitch & Currah, 2002).

MATERIALS AND METHODS

The field experiment was conducted at Horticulture Research Farm (HRF) at R.S.M (PG) College, Dhampur, Bijnor, Uttar Pradesh India. Geographically it is situated between 290 15’ 27.5328” latitude in the north and 78o 30’ 0.2196” longitudes in the eastern elevation of about 235 m above mean sea level. The experimental materials of garlic used in the present study were collected from different places of India. The experiment was laid out in Randomize Block Design (RBD). These 21 genotypes were evaluated and studied for their growth, yield and quality performance based on morphological and agronomical measurements. The following observations were recorded during the course of experimentation on following characters like-Plant height (cm), number of leaves/plant, length of leaf (cm), width of leaf (cm), plant pseudo stem height (cm), plant pseudo stem diameter (mm), equatorial diameter of bulbs (mm), polar diameter of bulbs (mm), weight of fresh bulbs (g), weight of dry bulbs (g), number of cloves/bulb, yield (q/ha), total soluble solids (%). protein (%), sulphur contain (%). These observations were recorded on five randomly selected plants of each row. Averages of data from the sampled plant of each treatment were used for statistical analysis in order to draw valid conclusion. The statistical parameters like- mean, ranges were calculated as per the standard methods of analysis.

RESULTS AND DISCUSSION

The analysis of variance for the design of experiment indicated that the mean squares due to genotypes were highly significant for most of the characters indicating a wide genetic variability among the genotypes in Table 1. The variation due to checks were also highly significant for are the characters like- plant height (58.91 cm), Plant pseudostem height (3.87 cm), number of leaves per plant (1.06), length of leaf (15.68 cm), width of leaf (6.72 mm), Plant pseudostem diameter (3.97 mm), Equatorial diameter of bulbs (25.71 mm), Polar diameter of  bulbs (20.07 mm),  number of cloves per bulb (22.96), weight of fresh bulbs  (152.72 g),  weight of dry bulbs (122.57 g), Yield quantal/ha (1573.66),  total soluble solids (9.25%), Sulphur contain (0.0005 %), Protein (0.30 %). Mean performance serves as an important criterion in eliminating the undesirable types in a selection progrmme.Tesega K and Tiwari (2016)10. The phenotypic  correlation coefficients were worked out to measure the association among the fiften characters under study. The estimates of these correlation coefficients are presented in table-2. Plant height showed highly positive and significant correlation at phenotypic level with weight of fresh bulbs (0.562), leaf length (0.459), weight of dry bulb (0455), Equatorial Diameter of bulbs (0.440) and polar diameter (0.313), whereas sulphur content (-246) showed negative and significant correlation with the trait.Plant pseudo-stem height showed positive and significant correlation with number of leaf (0.567), leaf width (0.319). Whereas negative and significant correlation with polar diameter (-0.484), total soluble solids (-0.273).Number of leaf showed positive and significant correlation with leaf width (0.708), polar diameter (0.541), weight of dry bulbs (0.478), pseudo-stem diameter (0.436), yield q/ha (0.427), weight of fresh bulbs (0.415), equatorial diameter of bulbs (0.364), and total soluble solids (0.247). Leaf length showed positive and significant correlation with weight of fresh bulbs (0.437), plant pseudo-stem diameter (0.433), weight of dry bulbs (0.377), leaf width (0.284) and equatorial diameter of bulbs (0.261).  Leaf width showed positive and significant correlation with plant pseudo-stem diameter (0.583), yield q/ha (0.494), total soluble solids (0.436), polar diameter (0.425), weight of dry bulbs (0.411), weight of fresh bulbs (0.397), and equatorial diameter (0.343). All other traits were not found to be significantly correlated with the leaf width. Plant pseudo-stem diameter showed positive and significant correlation with weight of fresh bulbs (0.673), weight of dry bulbs (0.659), yield q/ha (0594), equatorial diameter of bulbs (0.511), number of cloves/ bulbs (0.444), polar diameter (0.382), protein content (0.348), and total soluble solids (0.338). Equatorial diameter of bulbs showed positive and significant correlation with weight of dry bulbs (0.764), weight of fresh bulbs (0.755), polar diameter (0.370) and yield q/ha (0.323), whereas positive and non significant correlation with protein (0.175) and sulphur content (0.001) and total soluble solids (-0.81). Polar diameter showed positive and significant correlation with weight of dry bulbs (0.493), weight of fresh bulbs (0.462) and yield q/ha (0.258) whereas negative and significant correlation with sulphur content (-0.276). Number of cloves/plant showed positive and significant correlation with yield q/ha (0.362), sulphur content (0.338), weight of dry bulbs (0.328), weight of fresh bulbs (0.287), and protein (0.296).Weight of fresh bulbs showed positive and significant correlation with weight of dry bulbs (0.562), leaf length (0.437), yield q/ha (0.450) and protein (0.320) whereas positive and non significant correlation with total soluble solids (0.156) and sulphur content (-0.131) was recorded. Yield q/ha showed positive and significant correlation protein (0.428) highly significant and total soluble solids (0.300) significant. Total soluble solids showed positive and significant correlation protein (0.429) highly significant whereas positive and non significant correlation was found with sulphur contain (0.023). The genotypic correlation coefficients were worked out to measure the association among the fifteen characters under study. The estimates of these correlation coefficients are presented in table-3 Plant height showed positive and significant correlation with weight of fresh bulbs (0.663), Equatorial diameter (0.608), weight of dry bulbs (0.595), leaf length (0.504), sulphur contain (0.406) whereas negative and significant correlation with total soluble solids (-0.305) and protein content (-0.259). Plant pseudo-stem height showed positive and significant correlation with leaf width (0.922), number of leaf (0.889), protein content (0.481), total soluble solids (0.439), weight of dry bulbs (0.354), number of cloves/plant (0.347) and sulphur content (0.326) whereas genotype negative and significant correlation polar diameter (-0.708) highly significant and weight of fresh bulbs (-0.305). Plant pseudo-stem height showed positive and significant correlation with leaf width (1.031), polar diameter (0.757), weight of dry bulbs (0.564), yield q/ha (0.526), plant pseudo-stem diameter (0.512), weight of fresh bulbs (0.437), protein (0.362), equatorial diameter of bulbs (0.348) and total soluble solids (0.306). Leaf length showed positive and significant correlation with weight of fresh bulbs (0.756), weight of dry bulbs (0.744), plant pseudo-stem diameter (0.582), equatorial diameter bulbs (0.530) highly significant, yield q/ha (0.261) and polar diameter (0.258). Leaf width showed positive and significant correlation with plant pseudo-stem diameter (0.874) highly significant, weight of dry bulbs (0.846) highly significant, yield q/ha (0.832), polar diameter (0.771), weight of fresh bulbs (0.693), protein (0.585), equatorial diameter of bulbs (0.524), total soluble solids (0.463), number of cloves/plant (0.282). Plant pseudo-stem diameter showed positive and significant correlation with yield q/ha (0.833), weight of dry bulbs (0.825), weight of fresh bulbs (0.823), protein (0.694), equatorial pseudo-stem diameter (0.649), number of cloves/plant (0.576), number of cloves/plant (0.576), number of cloves/plant (0.576), number of cloves/plant (0.576), polar diameter (0.484).Equatorial diameter of bulbs showed positive and significant correlation with weight of dry bulbs (0.947), weight of fresh bulbs (0.931), yield q/ha (0.507) ), polar diameter (0.483) ), protein (0.409) ) and  total soluble solids (0.341) ). Polar diameter showed positive and significant correlation with weight of dry bulbs (0.651), weight of fresh bulbs (0.585) ), protein (0.530) ), yield q/ha (0.467) ) and sulphur contain (0.436) ). Number of cloves/bulbs showed positive and significant correlation with protein (0.716), yield q/ha (0.606), sulphur contain (0.490), weight of dry bulbs (0.470), and weight of fresh bulbs (0.368). Weight of fresh bulbs showed positive and significant correlation with weight of dry bulbs (0.961), yield q/ha (0.628), protein (0.557). Weight of dry bulbs showed positive and significant correlation with yield q/ha (0.694), and protein (0.559). Yield q/ha showed positive and significant correlation with protein (0.759) and total soluble solids (o.534). Total soluble solids showed positive and significant correlation with protein (0.819); and Sulphur contains showed positive and significant correlation with protein (0.399). In general the estimates of genotypic correlation coefficients between different characters showed close parallelism in direction with their corresponding phenotypic correlation coefficients presented in Table 2 and Table 3. Similar results were reported by, Tiwari et al. (2014), Tsegas & kasshum (2011), Yadav & Singh (2007), Yadav & Singh, (2012), Pense et al. (2014) and Peryin et al. (2014).

Table 1: Mean sum squares genotypes

Table 2: Phenotypic correlation

Table 3: Genotypic correlation